We often pick up hobbies to add some fun to our lives. We join a book group, take up knitting, or commit to finally learning how to play pickleball. But before long, what started out as leisure can begin to feel like just another obligation to execute and perfect: We fall behind in the reading, can’t stop dropping stitches, or the tournament schedule gets overwhelming.

It’s a tale as old as time, or at least as old as the United States. Our obsession with productivity may feel new, especially when it crosses over to our hobbies, but according to Gary Cross, a historian and author of the book Free Time: The History of an Elusive Ideal, Americans have been trying to make the most of our time for a while now. “A lot of it is that old Protestant work ethic that was part of the early migration to the United States,” he told Vox. “They were predominantly Protestant Christians who saw work as a kind of a special calling from God.”

As Cross explains, this attitude kicked into high gear alongside industrialization. “The capitalists really were all about increasing productivity. Time away from work begins to be seen as in some ways wasted time,” Cross said. And when the labor movement helped win workers some free time for hobbies around the turn of the 20th century, the same mentality made the jump into our leisure time.

That time is something that writer Jenny Odell has thought a lot about and explored in her books Saving Time: Discovering a Life Beyond the Clock and How to Do Nothing: Resisting the Attention Economy.  “I think both of my books came out of observing the daily experience that I and the people I knew were having, where our relationship to time felt so painful — this unending intensity that was so exhausting,” she said. “There has to be another way.”

Odell says that one of the ways to shift our relationship with time is through cultivating hobbies — without falling into the trap of relentless quantification and optimization. So how do we learn to truly enjoy our leisure time, and why should we all consider failing a little more along the way? We learn that and more on the latest episode of Explain It to Me, Vox’s weekly call-in podcast. 

Below is an excerpt of my conversation with Odell, edited for length and clarity. You can listen to the full episode on Apple Podcasts, Spotify, or wherever you get your podcasts. If you’d like to submit a question, send an email to askvox@vox.com or call 1-800-618-8545.

How is our pursuit of hobbies connected to how we think about time?

Hobbies are a place where you can see different ways of thinking about time battling each other. There’s a very fine line between someone who pursues a hobby for the sake of doing it versus someone who feels that they need to optimize it, perhaps even make money off of it. There’s nothing wrong with that, but these are different ways of thinking about the activity that you’re doing.

People read the title How to Do Nothing and they think that I’m a person who literally doesn’t do anything. I love to do things and I love to learn things. I think a lot of people start hobbies because they want to learn. 

In American culture, a lot of us stop being given opportunities to learn after we’re children or after we’re students. I think it’s really beautiful that adults seek out ways to learn, often leaning into communities where they’re learning with other people. And learning has progress in it. You do get better at things when you learn them. 

My feeling is just that that sense of forward movement and learning gets co-opted by this larger culture that we exist in that is also very American: needing to have something to show for your time. What starts out as wanting to learn something turns into something that you’re giving yourself a score on, without your ever having decided to do that.

I spoke with a historian who said part of the reason that we relate to our free time in this particular way in America specifically is the history of the Protestant work ethic. It’s just so ingrained in us. How do you help yourself break out of that mentality?

I have to shout out this book called The Score by C. Thi Nguyen. He talks about this very question. In that book he talks about games and how when you play a game, you take on a whole new set of values, and you do that for whatever couple of hours and then you put it away. It’s kind of this practice in taking values, putting them on, taking them off, putting them away. 

For me, either literally playing games or trying to have a more playful, experimental mindset about what it is that I’m doing can break that cycle. When you get closer to [a goal], it gets more and more seductive. Like “I want a higher number.” You just need something to break you out of that and be like, “What is this number even measuring?” 

For me, I’m a writer. Words per day are a measure. You think you want more words per day, but all words are not the same. There have been moments where I was trying to optimize words per day. I have to stop myself and think about what other ways I could value the situation. Like, “What were those words? Did I make some sort of breakthrough?” 

There’s all these other different ways that you could think about what it is that you’re doing.

Something I think a lot about when it comes to hobbies is failure. For instance, I’m getting back into photography. I did film photography in high school and this year I picked it back up with the goal to shoot a roll of film per month. 

The year’s almost over. I’ve done three rolls of film, one of which I must have unloaded incorrectly because it was completely blown out. What role does failure play in our hobbies and how we interact with that?

I love failure. I think it’s so underrated and games are very useful here. A good sports person is open to failure and knows that that’s fun.

I think that along with not having opportunities to learn as adults, we also aren’t given opportunities to fail. That’s probably been the case for a long time, but now with social media and things being more visible for a lot of people, we really are not used to failing. We think we don’t want it. 

I feel like I am actively now seeking out things that I’m bad at just so I can have that feeling. I’m a failure addict.

That is true. Once we leave school, what opportunities do we have to safely learn things and fail and try it again?

I don’t know how else to describe it: It’s really fun to be bad at something. Once you accept that you are bad at it, your reason for doing it has to be something else. 

I’ve been going to this native plant restoration thing for two and a half years now, so I definitely know my weeds and I am better than the day that I showed up, but I don’t go there to be the best at something. 

I showed up on day one and I wasn’t wearing the right clothes. I didn’t have gardening gloves. I had never gardened in my life. I had no idea what I was doing. It was this fascinating feeling. It’s just so different from being an adult who’s specialized in something.

What’s a way to help yourself fall back in love with hobbies if it’s been a while or if you’ve optimized so much, you want to find the joy in it again?

It’s like the equivalent of being right-handed and trying to write with your left hand. Anything you can do to relax the perfectionist grip that you have on this thing. 

That means throwing obstacles in your own way or trying to do things in a way you’ve never done them before. Rediscover the same thing from a new angle or in a different context with new people.

In the last month or so, President Donald Trump’s on-again-off-again relationship with Ukraine — which has ranged from kicking Ukrainian President Volodymyr Zelenskyy out of the White House in early 2025 to promising new air defense missiles this summer — has once again run cold. Trump has excoriated Zelenskyy for successful Ukrainian strikes on Russian oil and gas infrastructure, called for Zelenskyy’s ouster, and gifted Russia a sanctions reprieve.

Trump also hasn’t had much success brokering a ceasefire, much less an end to the war (an announced “energy ceasefire” fell apart-near instantly earlier in October). First Lady Melania Trump, however, has.

She reportedly played a (limited) role in arranging a partial ceasefire for the frontline Ukrainian city of Oleshky, which has been hit especially hard by the war and is currently occupied by Russia. 

The pause, which is scheduled to run through the weekend, allows food and aid to get in and for a civilian evacuation. While limited, it also shows that both Ukraine and Russia are potentially willing to come to the negotiating table. 

After the Trump-Vladimir Putin rapprochement, though, some critics worry that the US is more likely to take Russia’s side — or at least step away from Ukraine’s — both in the war and in any possible peace talks. 

To break down what the Trumps are up to, how serious the concerns of Trump abandoning Ukraine for Putin actually are, and what could come next, Today, Explained co-host Sean Rameswaram spoke with Alex Ward, a national security reporter for the Wall Street Journal.

Below is an excerpt of Sean’s conversation with Ward, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

Let’s start with the most unexpected news out of this war in recent days: that Melania Trump brokered a ceasefire.

It’s possible she had a role. I’m going to personally, without too much reporting, say that it was probably more Pope Leo.

Melania stole Pope Leo’s ceasefire?

I think a little bit. Look, this ceasefire is not a small thing. It is a humanitarian ceasefire in the southern Ukrainian city of Oleshky. It allows humanitarian aid to get in. The critics would say this allows the Russians to re-arm and regroup, and I guess at the same time also the Ukrainians. 

The question is, does it actually have that much influence over the war? No, it’s a very, very small targeted ceasefire. But it is a potential signal that deals can be made. 

The Russians are very much saying, look at Melania Trump, look at how important she was to all this. And if I’m the Russians, I would love to be saying things like that because then President Trump feels like the Russians are being very generous towards my wife and to my family, and therefore I side with them. 

It feels very convenient that the Russians are pumping that up and that even the White House is pumping up Melania Trump’s influence. I don’t want to discredit her. I’m sure she did work on this.

When did she become a negotiator in this war?

From the beginning, she has been trying to get children kidnapped by Russia back to Ukraine.  That has been a major focus of hers in this war. 

Is she the driving force behind this ceasefire? Is she the number one reason it happened? It’s totally possible. There’s just a lot of skepticism out there about whether Kyiv and Moscow were brought to the table and browbeaten by the First Lady. Again, very possible, but both sides, being Ukraine and Russia, have an incentive to play up her role.

The ceasefire is just relegated to one city. How come?

That’s all they could agree to. If we’re looking at this war at a bigger scale, there’s been a massive discussion about how to get an end to the Ukraine-Russia war. 

The US last week was able to broker a commitment to have trilateral talks between the Ukrainians, Russians, and the Americans with the goal toward ending the war. And you’ve heard President Zelenskyy of Ukraine say, “We can call it ceasefire. We can call stop the killings. We can call freeze the conflict.” 

Putin goes, ‘No, thank you. I would like basically a handover of the territory that I want, even though I’ve been unable to conquer it after nearly five years.’ It’s unclear if they’re even going to get into the room for those trilateral negotiations. Even if they do, it’ll probably be at a lower technical level. 

So are we ever going to get to the point that Putin and Zelenskyy and Trump get in a room, all hold hands and say ‘war over’? I highly doubt it, but that is the goal they’re after. You see the Trump administration, the Kremlin, and Kyiv all point to this Oleshky ceasefire as, like, ‘Hey, this could be a model for the much bigger deal.’

I want to be clear that this Oleshky thing is important. It really is aimed at a humanitarian ceasefire since there’s a lot of food that isn’t getting in, a lot of people are suffering and this potentially leads to some relief. But there are a lot of people around Ukraine and many bombed-out cities that are going, “Hey, what about us? We are hungry too. We don’t have certain services.” 

Winter is coming, and the Russians have bombed out a lot of Ukraine’s energy infrastructure, which is going to make this winter potentially very brutal, as a lot of folks will not have heating or the necessities they need to survive really cold temperatures.

Steve Witkoff called Vladimir Putin a humanitarian, which had a lot of people shook because, famously, Vladimir Putin also started this war.

Yeah, it’s like calling Freddy Krueger a nails enthusiast. It doesn’t make a lot of sense. 

Has Vladimir Putin released Americans that he took hostage? Yes. Has he returned some children that his government, his forces have taken? Yes. I don’t know if that makes a humanitarian. That’s kind of like praising the arsonist for throwing a bucket of water on the house fire.

It’s not just calling him a humanitarian; it’s getting rid of the Lindsey Graham sanctions on Russia, which is essentially like handing Russia billions of dollars, right?

There’s a lot of weirdness here. First of all, on the Graham bill, it’s a weird bill, and frankly it’s a pretty bad bill despite the fact that Democrats and Republicans love it. 

What it basically calls for is tariffs on countries that purchase Russian energy. The way that Trump explains it is he waived the economic punishments, because otherwise the Russians would not have returned Stephen Hubbard and there might not have been this Oleshky ceasefire and there might not have been a bunch of other benefits.

Another argument President Trump was making for removing these tariff sanctions on Russia was that it would lower diesel costs here in the United States. Has that actually happened?

The Russians agreed to a diesel deal where they would basically export diesel to the United States. And in President Trump’s mind, that will lower costs because President Trump and political allies of his like Elon Musk of SpaceX say that is the reason diesel prices have skyrocketed across the US. 

However, when you talk to analysts and look at the data, it is the Iran war that has had a greater effect on diesel prices. Not to say that the Russia-Ukraine war hasn’t had any, but it’s much less because there is just very little Russian diesel in the American market, but also in the global market. 

What the US is receiving from Russia is not nothing, but effectively nothing because it’s just not enough to alleviate the diesel concerns across the country and to lower prices to a meaningful amount. And we can see President Trump is effectively scrambling to make good on his promises of lowering prices as the midterms approach, to the point that he’s willing to make a deal with the invading country in the war he’s trying to end in order to lower gas prices at home.

A lot of people see these developments and think that the United States’ allegiances have shifted, that we’ve maybe abandoned Ukraine at the moment. Is that fair?

I don’t think we can say that with any sense of certainty. President Trump has actually been on Ukraine’s side in certain cases, even rhetorically during a UN meeting, I believe it was last year. President Trump was presented with intelligence about how the Russians have been struggling to invade Ukraine. And then he released a statement saying basically, ‘Go Ukraine, go. Russia, you’re kind of losing here.’ And that made people go, ‘Oh, he’s on Ukraine’s side.’ 

And of course, after that whole Oval Office blowup with Zelenskyy, that relationship improved. But everyone’s always been kind of like, ‘Well, we know where Trump’s feelings are here. He wants a big deal with Russia. He wants an economic deal with Russia. He wants to improve relations with Vladimir Putin, and so he always returns to the mean, even if he flirts with Ukraine.’ 

But below President Trump’s unique style of dealmaking, the US intelligence community is helping Ukraine to defend against Russia. The US is selling weapons to Europeans for the Europeans to deliver to Ukraine. It is nowhere near the level of weapons support during the Biden administration, but that intelligence support seems to be at a higher level than during the Biden years. 

And it’s not like President Trump has purposefully hampered Ukraine’s defenses a lot. There are some questions about sudden intelligence shutoffs and delays of important weapons. I am not saying President Trump has been a staunch defender and a staunch supporter of Ukraine here. But if you look at the grand totality, Ukraine is still being defended by the United States. 

It almost seems like President Trump has an inability to pick a side. He’s playing both. In his mind, he thinks that’s the best way to get them both to the table and get a deal. But this is also the man that said he could do it in 24 hours and we’re nearly two years into his presidency. And right now the best we can get is, ‘Hey, maybe we can get the Russians, Ukrainians, and Americans to meet in a room for technical talks.’ 

It’s not nothing. And also, hey, we got a ceasefire in a town in Ukraine. It’s not nothing, but it’s nowhere near the big, potentially Nobel Peace Prize-winning deal that he’s searching for.

The iPhone has more screens! The MacBook has a touchscreen! The HomeView does CarPlay apps! For the first time in a long time, Apple is in a period of unabashed gadget experimentation, and while the final results aren't always perfect, it's fun to watch the most successful product maker try some new things again. Even when, in this case, "trying" amounts to just slapping a touch panel on a lovely new MacBook Pro - just to see if you might use it.

On this episode of The Vergecast, David and Nilay debate the merits of a touchscreen laptop, Nilay explains why he is absolutely positively going to buy the new MacBook Pro with PROLED XDR Display, …

Read the full story at The Verge.

President Donald Trump is approaching the halfway point of his second term, raising the question of what — and who — comes next. And, more existentially: Can the MAGA movement survive without him?

To answer that question, some younger conservatives on the “New Right” are looking to a past US president for inspiration: Richard Milhous Nixon. 

In June, Vice President JD Vance spoke at the Richard Nixon Presidential Library and Museum in California, downplaying the scandal that ended Nixon’s presidency. If Watergate happened today, Vance said, it would be “like a 12-hour news story. Like, the idea that it would have taken down a presidency is crazy.”

Watergate, of course, is the most famous scandal in presidential history and the reason so many of our contemporary imbroglios get tagged with the -gate suffix. It began with a 1972 break-in at the Democratic National Committee’s headquarters in Washington’s Watergate complex by operatives linked to Nixon’s reelection campaign. Investigations — and a huge volume of Oval Office tapes recorded by Nixon — exposed Nixon’s involvement in the cover-up, and he resigned in 1974 facing the prospect of impeachment and removal from office.

Nevertheless, some conservatives are now embracing a rehabilitation of Nixon’s image dubbed “Nixonmaxxing.” They portray him as a president brought down by the “deep state” — an entrenched network of unelected government officials that they believe also tried to undermine Trump during his first term (and is still trying today).

Today, Explained co-host Noel King spoke with political historian Michael Koncewicz, the associate director of New York University’s Institute for Public Knowledge, about what actually brought Nixon down, why Watergate was, in fact, a big deal, and why some conservatives are undeterred and looking to the 37th president for inspiration today.

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify. 

Because we live in a fallen world, we are here today to talk about something they’re calling Nixonmaxxing. Why are young conservatives interested in former President Richard Milhous Nixon? 

Nixon’s ultimately known for Watergate, and Watergate for decades was the ultimate scandal in American politics. And younger conservatives are starting to revisit this history and they’ve started to compare the Watergate scandal to numerous attempts to bring down the Trump presidency. 

Nixon is a martyr for the cause. Nixon is the guy who was successfully brought down by the liberal establishment. And so if younger conservatives can rescue Nixon from liberal historians and liberal journalists, they think that they can protect the current president for decades to come. 

In the last decade or so, more and more media figures — and this has seeped down into conservative activists — have questioned a story that most Americans accept, which is that Watergate was a moment where the system worked. It’s a moment where Congress, the media, and the American public helped bring down a corrupt president. 

Conservative activists want you to believe that that’s not true. And the main reason is that if they can make you believe that that’s a lie, then they can make you question any future scandal that could affect any one of their guys.

What was the Watergate scandal? What did Richard Nixon actually do?

Watergate can best be understood as a story that begins, at least, in the summer of 1971. After the release of the Pentagon Papers, which was a secret history of the Vietnam War compiled by figures in the Johnson administration, Richard Nixon is enraged. 

In the summer of 1971, the reason that this matters and why it’s linked to Watergate is that in the wake of the Pentagon Papers coming out, Nixon authorizes the creation of the “Plumbers” unit: a group of shady guys with CIA and FBI on their resume, people who have experience doing black bag jobs.

“It remains to be seen how influential Nixonmaxxing is as a political phenomenon. Richard Nixon is still seen as one of the worst, most corrupt presidents in American history.”

The first operation that they pull off is breaking into Daniel Ellsberg’s psychiatrist’s office — he’s the man who leaked the Pentagon Papers. It’s referred to by Nixon historians as Watergate West. But when they pull this off, they are not caught and it’s dismissed as just a weird moment. No one knows that at the time these are guys being paid by the White House to break into buildings and spy on political opponents. 

There’s a lot of other activities that happened between summer of ’71 and June of ’72, but the Watergate burglars, the Plumbers, are caught at the Watergate Hotel. And what is at the Watergate Hotel? It is the offices of the Democratic National Committee.

They’re caught in June of ’72, and even then it’s dismissed as a so-called third-rate burglary because this just seems like some overeager campaign staff members who have nothing to do with the Nixon White House.

But on the tapes, we know that Richard Nixon, even if he didn’t have any link to the Watergate break-in, knows that he created this team. He knows that his advisers are aware of different parts of their activities over the previous year. That was not uncovered until 1973, which is when most of the American people and most people in Congress started to take this scandal seriously. Watergate ends Nixon’s presidency when it becomes clear to the American people that he has something to hide. 

The famous phrase attached to Watergate is that it was not the crime, it’s the coverup. That’s true to an extent, in terms of what was on the tapes that made it very clear that Nixon was obstructing justice. But he was covering up pretty serious crimes. He was covering up a lot of improper uses of presidential power. 

And so in the summer and fall of 1973, that is when Richard Nixon’s approval rating started to decline — a 25 percent approval rating. And when people ask why Richard Nixon stepped down, that’s the No. 1 reason. When his approval rating is that low, members of Congress feel the pressure to take on an unprecedented action, which is impeachment. The House was going to impeach Richard Nixon and the Senate was going to convict Richard Nixon. 

And so in subsequent years and decades, there’s this understanding that Watergate was a bad thing. Watergate was a serious constitutional crisis and that it was good that Richard Nixon stepped down, that our democracy was strengthened as a result of Watergate. And today’s conservatives are increasingly questioning that narrative.

Richard Nixon wouldn’t be in the position he is in currently if he hadn’t done some things that a certain type of conservative today thinks is noble or laudable or important. 

What was he doing at the time that makes a guy like Chris Rufo or the vice president say, “Hey, you know what? We need to reconsider Nixon”?

Figures like Christopher Rufo are drawn to Richard Nixon because the historical record shows that behind the scenes, he was a fierce culture warrior. 

Other presidents in the post-World War II era were certainly guilty of improper uses of presidential power. Nixon’s key difference was he wanted to bring that into the White House and micromanage the hell out of it. And Christopher Rufo loves that about Richard Nixon. He believes that presidents should use their powers to go after groups that he thinks are hurting the country. 

We now know that Nixon was a far more aggressive culture warrior behind the scenes. 

He was someone who wanted to create a new establishment, one that would weaken liberals in the media. Richard Nixon said on the Nixon tapes in a meeting with his closest advisers, [“The professors are the enemy. Professors are the enemy. Write that on the blackboard 100 times and never forget it.”]

Both Christopher Rufo and our current vice president, JD Vance, love the quote. JD Vance, when he was running as a Senate candidate in late 2021, gave a speech at the National Conservatism Conference and he used that quote.

This was just five years ago, and it would’ve been unthinkable for any conservative politician to favorably quote Richard Nixon, especially if they had aspirations to be president of the United States someday. But our current vice president, JD Vance, someone who will likely run for president in 2028, has publicly embraced Richard Nixon’s legacy.

President Trump is apparently in decline and his hold on the Republican Party over the next couple years will weaken, right? With so many of these stories, you wonder whether it’s like a handful of coconuts being nutty or whether this kind of effort means something for the future of the Republican Party. 

Do you think that this is notable, important, or significant?

It remains to be seen how influential Nixonmaxxing is as a political phenomenon. Richard Nixon is still seen as one of the worst, most corrupt presidents in American history. 

I used to lead school tours at the Richard Nixon Library 10, 15 years ago, and I would regularly talk to high school students, sometimes even middle school students, and they came in with a little bit of knowledge about Richard Nixon, and that knowledge was usually centered around the fact that Nixon got in trouble and Nixon was bad.

I am slightly encouraged by that fact because it shows you that Watergate is still viewed as an exceptional period of time. 

However, as I told people during Trump’s first administration, Watergate should be seen as a product of a very different political culture. It wasn’t just that the system worked — it did — but it worked because our democratic culture was far stronger than it is today. Our civic institutions were far stronger than they are today. You had a broader culture of dissent and a broader culture of questioning our president that contributed to Nixon’s downfall. 

Unfortunately, our political culture today is far more divided and far less willing to rally around a single narrative that would lead to another Watergate resignation happening in the same way [as] what we saw in the summer of 1974.

Today on Decoder, I’m joined by Joey Brookhart, an analyst at the chip and AI research firm SemiAnalysis, to help me dig into the story inside the numbers of the Anthropic IPO filing — a document known as an S-1.

Anthropic just filed its S-1 to go public on the Nasdaq, and it could start trading as soon as next month at a valuation of anywhere between $1.5 trillion and $2 trillion. That would immediately make it one of the most valuable companies on the planet.

But the price tag really isn’t the whole story here. The S-1 document published earlier this week is hundreds upon hundreds of pages filled with details that finally paint a picture of the economics of a frontier AI lab. As you might imagine, that picture is both really complicated and built on a series of very, very ambitious assumptions about the future and what AI will do to it.

So I wanted to have Joey on the show to help break down what this document tells us, both about Anthropic’s finances and the broader AI economy. Joey and his colleagues at SemiAnalysis actually built a model of Anthropic’s finances from the outside back in July, so he’s been waiting for this filing about as eagerly as anyone, and I was excited to hear his take on what we’ve learned and, importantly, what we still don’t know.

Okay: SemiAnalysis’ Joey Brookhart on the Anthropic S-1 and the costs and risks of building frontier AI. Here we go.

This interview has been lightly edited for length and clarity.

Joey Brookhart, you are an analyst at SemiAnalysis. You’re also co-lead on SemiAnalysis’ Tokenomics model, which is going to come up a lot in this episode. Welcome to Decoder.

Yeah, thanks so much, Nilay.

I am very excited to talk to you. We’re talking just a couple days after the big Anthropic S-1 was filed. It’s our first look inside of the finances of one of the leading frontier models. What’s your take? What’s your read into it?

It was an awesome S-1. It’s been a rough three weeks since the investor day. Some people were somewhat disappointed in the September [annualized recurring revenue] numbers, but what we saw here was a company that has efficiently scaled to an amazing level, with a $1 trillion-plus valuation, $70 billion-plus of ARR in a very short amount of time.

In gross margins, compute margins, and free cash flow, everything is what you’d want to see. So I don’t think there was much to nitpick in this filing. It’s the reason you’ve seen a lot of the semiconductor complex, and the neoclouds and compute stocks, really rally again in the last two days.

It’s funny, I don’t think I can nitpick the S-1 itself. I want to get into some of the details because there are a lot of numbers in there that are worth thinking about. I actually just want to start at the really big picture. You run a thing called Tokenomics. I’m going to explain what Tokenomics is to people.

I look at Anthropic and where it could go. I look at Dario Amodei saying that he can see his way to $1 trillion in revenue. Where does that money come from? Because so much of these businesses are about eating every other business and it feels like someone else has to make some money to pay Anthropic to generate these revenues. I haven’t actually seen that laid out very clearly.

It’s so interesting. Today, because even the scale we’re at is $120 billion of ARR between the two leading labs, it’s still an extremely narrow market. The top 1 percent of customers are the ones that are spending $50,000 to $100,000 per employee. Your broader Fortune 500 or Global 2000, which typically do a lot of IT spend, isn’t spending much.

A lot of the spending, especially at Anthropic, is coding-specific. It’s almost a single vertical company. We look in the future to 2027, you think to this broader adoption and white collar work. This typical enterprise Q4 budgeting season, we actually haven’t gone through with one of these labs yet in any meaningful way because their ARR did really start to accelerate until the beginning of the year. We think of other cases like cyber, which can be similar to coding, where these are eight-figure-plus contracts with leading enterprises that can scale very quickly due to all the cybersecurity incidents we’re seeing. You get to other verticals like bio.

To get to $1 trillion, we do have to move to some of that white collar work, where it goes from AI augmentation to labor saving or replacement in some areas. You look at things like Microsoft’s buyout offers to employees as an example of this, but there’s no wealth of other verticals that they can get into and really start to move the needle.

This is the single biggest question I have, not just about the S-1, but the entire industry. I would understand that if there are one or two leading labs. There are two big companies that have a technology that can automate a whole bunch of things. We will see how well that automation goes sector by sector, but there are not just two leading labs. There are quite a few of them. There are open weight models.

I’ve heard from a lot of CEOs who are very nervous about giving all their data to an OpenAI or Anthropic and they would like to run some things on-prem. There are law firms running on-prem AI now, which is the funniest turn in maybe all of history.

How do you see that playing out? Because so much of the pressure on this S-1 was the numbers themselves, which I want to talk about, but then there’s the external pressure of, “You’ve got to grow and growth is not as short.” So how do you see all of that playing out?

It’s very interesting because when we look at coding today, for example — and I think we saw this in Q3 with OpenAI kind of catching up — there are areas of coding where there are very low switching costs, and I can just move between that. What we hear from enterprises and maybe, too, on the OpenAI side — obviously I think they somewhat botched the Fable release, and the lack of zero data retention is why we saw some of the slowdown. That’s something they can fix with Fable 5.5 and maybe drive more enterprise adoption there.

That’s a huge thing for enterprises when we talk with them. We definitely see enterprises now, and more so, too, a lot of the AI natives, doing custom training and post-training on open weight models, and then running either their inference off of that or even their products for internal or external use cases.

Obviously, DeepMind at Google and [Meta Superintelligence Labs] are very well-funded labs that have pretty similar training compute capacity, and they’re bringing on a ton of it. Not even to mention SpaceX as well, with what Elon said on [about] 10 net new gigawatts next year and half of that is the long-term internal use case.

In the first half of the year, Anthropic ran away with it. They were 90 percent of the industry’s net new ARR. We saw in Q3 that OpenAI was probably actually the majority of industry net new ARR. Open-source has grown from probably $1 billion of token inference costs, ARR, in Q1 to $10 billion-plus here in Q3.

So yes, the industry’s gotten much more competitive, but there are all these new use cases, too, and some of these verticalized use cases are really where we’re going to see the growth going forward. Because it’s obvious coding isn’t going to power us to even triple from here.

It’s interesting. The concept is called Tokenomics. You run that practice alongside another co-lead at SemiAnalysis. Explain what it is because to me it’s such a smart way of thinking about, “We’re going to put some money in and maybe we’ll get some money out.”

I think of it as the unit economics [of AI], or even just the broader idea — everything from a macro- to microeconomics of running an AI business or even looking at AI demand. So we cover the hyperscalers, now some of the neoclouds as well in a separate product.

But then just the AI labs, too. For investors, or just people that are interested in the business, Anthropic had negative 94 percent gross margins on inference two years ago. Now they have a positive 85 percent margin, and people don’t understand how they allocate compute. How do we think about the inference business model?

Part of that gross margin conversation is the revenue per megawatt in inference. Why are all companies that are running inference seeing massive gains in inference and compute efficiency? So we try to model out these businesses and obviously when Anthropic was private, we’re dealing with information we can get from the press and things like that.

But now that we have concrete audited numbers, it’s easy to explain the unit economics of this. And also how the businesses differ. OpenAI is a much different business than Anthropic just in both their consumption versus subscription and then historical weight versus consumer versus enterprise. [We are] trying to understand across the demand level the economics of these businesses.

Several years ago when I talked to Google CEO Sundar Pichai about the cost of inference, I said, “How are you ever going to make money?” He was just very clear. He said, “If there’s one thing Google’s good at, it’s bringing this stuff down the cost curve.”

It was a very blunt answer. I understand how Google can do it. They make their own chips. Anthropic is running on everyone else’s clouds. The core part of the S-1 is how much they’ve committed to spend on other people’s clouds: SpaceXAI, Google, Amazon. Where does their efficiency come from?

There’s really token throughput. They have a very diverse chip fleet. Between Trainiums, TPUs, and GPUs, across all of those, we see a ton of token efficiencies. Token throughput, for example, on Trainium chips is up 5x to 10x year-over-year right now.

Dealing with both the hardware level efficiencies and the software — and how the model interacts with the hardware — there are a lot of token throughput gains where if you’re doing X tokens per second, now you’re doing five or 10 times that just a year later. What they’ll tell you is they see continued compute efficiencies as well going forward.

Max Kan, who co-leads Tokenomics model with me at SemiAnalysis, and I have even published some research on this. Right now, if Anthropic’s at $65 million of revenue per inference megawatt, this was mid-teens last year at this time. What we’ve said on maybe Opus 5.5 on a [Nvidia] Blackwell, you can get to $100 to $120 million of revenue per megawatt.

The big thing here is they’re paying on average now just a little over $10 million per megawatt in [cost of goods sold], or just in compute costs. What you can do with those margins is then reinvest in training.

People don’t realize this, but only about 30 percent of the compute is actually in inference-serving revenue. The rest is for experimentation and research, training models, and post-training models. So there’s a lot of compute that is building the next model and that’s more of the R&D side and where you actually get your returns and defensibility in this business.

Actually, what I was expecting to see in the S-1 was that dynamic play out much more strongly — that Anthropic makes a bunch of money selling the models they have now and there are more customers in the future for the models they have now. That’s going to throw off a whole bunch of margin. And then, because it is Anthropic and they think they’re building a digital god, they’re going to train the next models as much as they can.

That is a very particular Anthropic story. The company is chasing AGI. The people who work there will happily tell you that in the S-1 that Claude might be conscious and this could all go to hell. Anthropic is a very unique company in its conception of itself. But you don’t really see that dynamic playing out in the S-1. They’re managing their training costs against their inference margin pretty well. Do you see that going up or changing in any way?

I agree. Long term, and we’ve even said this internally, they want to actually increase the percentage of training. If you believe you’re building a digital god or going towards AGI, and as long as you have the gross margins of 85 percent-plus on inference to do so, you can.

They’ve grown a lot faster than they thought, and they didn’t expect to be at 11 percent non-gap EBITA margins. They’d love to be closer to zero, or even below that if they could get that compute and allocate it towards training and continue to see these compute efficiencies.

They’ve messaged that, too, to investors in the roadshow. You can look at this S-1 and just the curve of profitability over the last few years and how little cash they burned to get to this point and you can say, “This is a good business model, but we’re going towards AGI. Don’t expect the margin leverage we’re seeing to continue to this level, even though long-term margins can be quite a bit higher.”

There are some real shades of Amazon there. Jeff Bezos famously told investors he wasn’t going to make money until he could make a lot of money. Obviously, Amazon and Anthropic have a lot of back and forth. Maybe there’s some family resemblance there.

But I’m curious, there’s a point of model capability that would allow you to go into more verticals than just coding, right? We might be at it now. The idea of capability overhang exists, the idea that the models we have today could go and take over bio research. They’re taking over mathematics today. There’s a point at which the smartest business decision is to stop training and to just sell your profitable model into more and more companies. Anthropic as a public company will face that pressure.

Do you think they’re organized or structured to fend it off?

Yeah, I think they’re structured well. With some of the voting stock in areas like that, they definitely are. We’ve seen this in tech before and even publicly when Mark Zuckerberg has made these decisions before to invest heavily.

It didn’t always pay off. I just want to point out, it didn’t always pay off.

Yeah, it did not always pay off.

Although you and I technically are in the metaverse right now, by some definition.

[Laughs] Right. But I think that’s something, and there’s an interesting number in the S-1 that 80 percent of revenue in the last three months comes from models released in the last six months.

So then you say, “Okay, 20 percent of the models are like Opus 4.5 in earlier versions.” One thing going forward is that if you’re a frontier model company, you always need to be at the frontier and it’s incredibly competitive.

Wait, can I ask a really dumb question about that?

Yeah.

Why? I think the heart of my curiosity about the industry right now is if you enabled some bleeding-edge technology that could revolutionize the entire world, at some point, the most profitable thing to do is to just go play it out in all the different verticals, right? It’s not to go make the next one. It’s actually to run an efficient model in legal services and medicine and wherever else that there hasn’t been diffusion of AI yet.

This idea that you always have to be at the frontier, that Anthropic always has to be competing with Google and OpenAI and whoever else, I get it from their self-conception. But from a business point of view, an AI-enabled business is going to throw out more money and spend more money with me, the AI provider, and that isn’t necessarily related to being at the frontier.

There are a few portions of that. For new verticals, and this is very cyber specific, if an adversary is using a frontier model, you need to be defending with a frontier model.

Fair enough.

When we talk to some enterprises, it’s not like an email summary where I can run that on open source or Sonnet. There are just certain verticals where having… [For example,] if you were in a legal case as a defendant, would you be okay if your lawyer was using a non-frontier model if the prosecution—

[Laughs] I got bad news for you about what’s going on in the legal market right now.

The competitive dynamics do dictate that. I think from a go-forward perspective, we’ve seen this with open source too catching up in one point, but the demand will be there. [SemiAnalysis CEO] Dylan [Patel] says this a lot. The demand will always be there for frontier intelligence, especially in competitive industries. And there are certain tasks, as you go towards more labor replacement versus labor augmentation, where that also is the case.

At the same time, they are getting more vertical. If you go look at job postings or what they’re hiring for, they’re putting out more of these SKUs and areas, and there’s a lot of beta testing going on like Claude for financial services, Claude for legal, their cyber program. They’re giving away 25,000 of credits per month for people in their cyber program.

That’ll be a huge SKU for them in 2027. Those verticalized areas and then ones that are specifically where you need to be… It’s more adversarial, I should say, or competitive, are the main reasons why. But we can both agree there are areas like email summary and work that definitely doesn’t need to happen [at the frontier].

I’ll just make a dumb comparison to the iPhone. It’s iPhone season. I just reviewed the iPhone Duo. Apple kept the iPhone looking the same for several years now. They build all of the tooling for the new iPhone and then they just reuse it for two or three or four models to get all the value out of that investment back before they move on to the next thing. Apple puts out a new iPhone, and it keeps selling the old iPhone for a while to get more value out of that investment and that development program.

The AI industry does not seem to be doing that. All of their emphasis is on developing the next new thing, deprecating the old thing pretty fast, and moving you onto the new expensive product, while at the same time they’re building the next new expensive product.

At some point it feels like that will rationalize, that there will be something that is worth just collecting margin from while they go invest in the new thing. I just can’t figure out where Anthropic sits in that cycle.

I mean, we do see this. Open source token volumes are picking up and there’s a lot of areas, yes, where the open source models have become good enough. I think on a go-forward basis, you’re like, “Okay, was that because of distillation?” And then the frontier labs have some defensibility actually going forward. I think when we talk to clients, it’s also about how we actually think about frontier versus open source. So something like a Sonnet type model, if you want to do the iPhone 18 versus the SE type analogy.

We do see that dynamic, and obviously with open source, it’s a question of how much that can take. Two, because we’re so early in these verticals, we don’t know what’s going to be fully agentic. There’s no human in the loop where the harness actually has, I should say, some value and defensibility to it.

The big area I’d look at here, especially when we talk to enterprises today, is only the coders are allowed to use the frontier models at a lot of these enterprises. If you’re a non-coder, some of these companies just limit you to Sonnet, if you’re an Anthropic customer. That’s reflective of how management views and wants to budget for this, what frontier intelligence is actually worth to them in certain areas.

In my financial analyst brain, Claude could not build a good financial model six months ago. It’s getting better if you connect it to the right areas, but we’ve gone from something like, “I needed a junior analyst six months ago,” to, “Maybe I don’t as much anymore,” and then, “Will I have a full junior analyst at my disposal anytime or multiple pretty quickly, if I have unlimited token budget?” We just look at that across every vertical and major job category.

The time horizon in each of those categories is going to be different. That’s just one of the bigger questions I have: How quickly do they get to where they think they can go?

I want to dig in on some of the numbers here. The one that jumped out in all of the comment sections on all of the forums and all of our articles yesterday was $80 billion. Anthropic lost $80 billion [in the first half of 2026]. That is related to a technical charge. Can you just explain the $80 billion? Because it doesn’t seem particularly relevant to the revenue and profits they’re talking about.

Yeah, it’s a non-cash charge because their valuation has gone up so much and they’ve issued warrants or convertible notes. You have to account for that in your balance sheet. It’s just a non-cash charge because their valuation has gone up so much since they issued these warrants and notes.

That’s something you would always back out. You can argue on stuff like stock-based compensation. Should we really be thinking about that on a non-GAAP cash basis? Because it’s non-cash, if I just hand employees shares, I have to account for that on my income statement, but I’m not actually handing them pure cash out of my bank balance. So it’s not an area like that. It gets the accounting, the high level. If you don’t know accounting, it looks bad, but it’s because they’ve grown so much and their valuation has gone up so much.

Some of the argument here about that charge is that Amazon was the other party there. Obviously Amazon’s very happy because Anthropic is buying a ton of AWS and sure they’re happy the valuation has gone up, but over time Amazon’s going to get diluted this way. That’s part of the dynamic there.

Anthropic is going to obviously IPO. They’re going to put a bunch of shares in the market. It’s very clear that over time they will issue more shares to raise more money. It doesn’t seem like they’re going to stop wanting to raise money anytime soon.

How are you thinking about that in terms of just investment into a company like Anthropic, that your valuation might be going up, but your actual ownership stake might be getting diluted over time?

The deals have always been very creatively structured.  The number is they’ve actually only burned $10 billion of cash. They have $120 billion-plus of cash and marketable securities in the balance sheet today, and post-IPO, probably another $100 billion.

It’s a great deal for both parties. They only really rent compute. It’s not like they have these massive capital outlays or even rent-to-own. You can make some arguments about certain accounting and there are these massive compute commitment obligations and that’s technically future debt, or that is sitting somewhat off balance sheet essentially. But from a dilution perspective, all tech companies dilute. Are they going to need to raise another $100 billion of debt or equity at some point? Possibly. Can they continue to creatively structure and finance future compute buildouts? Probably as well.

I know there’s been a lot of angst about the future of compute financing and data center financing in the last few weeks. But if you’re Anthropic, if you’re a major lab, a hyperscaler or Broadcom or Nvidia that are backstopping a lot of these deals, that’s probably not going to change anytime soon. So I’m not particularly worried.

As an equity investor, would I be worried about getting super diluted? I don’t think so. If you believe in this long-term AGI bull case and that Anthropic is going to be a leader in this, that probably shouldn’t worry you. You’re probably looking at a $10 trillion-plus business. They can outrun dilution at that point.

Let’s talk about the compute commitments. I saw at least one analysis saying over the next 10 years, it’s $800 billion-plus in commitments to the various hyperscalers and neoclouds. That’s a lot. You’re saying that they don’t have that much money. They haven’t even spent that much money yet. Do you see them generating the revenues to pay off those commitments?

Yeah. I think when people look at the headline commitments, the $500 to $600 billion number over 7 to 10 years, let’s call it, what they’re paying for compute today actually isn’t that many gigawatts. If you think about their spending right now, on average they’re close to $11 million per megawatt in spend, or $11 billion per gigawatt.

If you take that back to the annual level and say, “Okay, the $520 billion number is over 70 years, for example, that’s really not that many gigawatts and they’re going to be well beyond…” When they get to something like 20 gigawatts, the future compute commitments that they’re running essentially is going to be well into the trillions.

So yes, they are going to have the revenue to do so. It’s more about how much revenue they are going to have relative to how much compute. Two, the compute efficiency equation. If they keep getting a lot more revenue out of every inference megawatt, how much do you really want to invest in training and take margins to zero from a rental perspective? Because you can get to something where even 80 percent to 85 percent of their fleet is just on training and research at these kinds of margins.

The revenue is going to scale pretty well. They’re not in any dire situations there. Unless we realize all this revenue disappears or people churn. It’s not like they have to hit a trillion dollars of revenue extremely, extremely quickly to achieve all this and pay for this.

Unless you’re trying to build digital God and unless it doesn’t diffuse across the economy as fast as everyone wants it to. Those are bets, right?

They’re huge bets. The numbers you look at, if you’re really bullish on this ramp into the digital economy, is Anthropic saying within their Fortune 500 customers, they have 50 percent of the Fortune 500 and that is just 0.1 percent of their total customers’ operating expenses. When you look at that on a per user basis, it’s like $8 a month if you believe OpEx doesn’t include the cost of goods sold. If you believe they include the cost of goods sold, it’s sub-$50 per month.

They said the same thing. Of the top 5 percent of Claude Code users, they’re spending $18,000 a year on average, the top 5 percent of users. Their non-Claude Code users spend under $75 a month, well under $75. There’s this huge opportunity, especially when we talk to enterprises and these traditional buyers of IT software.

Penetration is extremely low in traditional white collar work. That’s the big point, too, that there is a large ramp period here of both seats adoption and usage. You can make arguments of who’s going to win in this, but it’s obvious the frontier labs are going to get some portion of this and it’s going to be pretty material to net new ARR next year.

One of the things that’s really interesting about that is we talk about the frontier labs, we talk about the hyperscalers — Anthropic has a lot of wild risk factors in this S-1, including that Claude might be conscious and kill us all.

But one of the most direct and maybe easiest to understand is that AWS, Azure, and Google Cloud are both suppliers and competitors in some real way, particularly Google. And they say, “These relationships could turn.” They have a big relationship with SpaceXAI. Elon Musk is going to train Grok. They’re going to compete with SpaceXAI at some point. That relationship might become precarious.

As you say, they’re only renting their compute. At some point, the market might force them to own more of their compute because their own competitors don’t want to lease their capacity to the leading company. How do you see that playing out?

We definitely see both OpenAI and Anthropic going more direct and not owning the compute, but more rent-to-own, or going through an SPV as some financial sponsors do and producing the compute more directly versus renting.

There are two points to this. Google, from one perspective, is also selling its external chips to customers and saying, “We don’t care to monetize this within Google Cloud or even allocate the share… If you think we’re very chip-constrained, we don’t even care that these are going to DeepMind or internal GCP compute for us to monetize. We’re just willing to become a chip seller.”

Anthropic loves TPUs and there are 3.5 to 4 gigawatts-plus, and probably more in the pipeline, in terms of orders there of Anthropic buying these chips directly to then rent. So yes, the market is good.

Wait, it’s not buying them directly to rent. So they’re buying them into a neocloud?

Yeah, they buy them through an SPV, or the SPV buys them and then they rent it from the SPV.

Got it. Okay.

Even within Google Cloud or AWS or Foundry, Anthropic is massive — 48 percent of their business comes through the Bedrock Foundry and Vertex where people are paying through their existing cloud relationship to access these models. They’re not even talking to Anthropic. You don’t have to interact with the Anthropic sales force.

You mentioned this earlier. This marketing channel where Anthropic gets a rev share.

Right. If you’re AWS and you’re saying, “I’m running Anthropic compute for, let’s say, $10 million per megawatt, but now I’m getting 16 percent of $65 billion-a-megawatt plus the compute costs as well,” so we’re seeing margins at all the clouds go up right now. Part of it is CPU utilization is going up because of all the coding and then some on the [reinforcement learning] side, but these token-as-a-service businesses as we call them — so AWS Bedrock, Microsoft Foundry, Google Gemini Agent Enterprise platform, which is formerly Vertex — are actually massively increasing the margins on AI at these clouds.

They’re benefiting as well when shareholders are giving them credit for this recently. In Q2, both Azure and AWS had extremely, extremely strong quarters, AWS specifically, on the back of Anthropic’s growth on Bedrock.

Do you think that will keep Amazon from ever wanting to train its own frontier models? They’re doing a good job of letting AWS be the infrastructure for everybody else, but they’re one of the only big tech companies that hasn’t felt the insecurity of not having their own models.

Yeah, it’s interesting. Amazon is very happy to serve a wide variety of customers and they have very little [frontier capability]. When we look at our estimates of training compute, they have the least of any hyperscaler, except maybe Oracle. It doesn’t seem like there’s much strategy there.

I know Microsoft in the last two quarters has been talking about it a little more. AWS on the call has been talking about it a little more, but it’s not huge. They’re not doing it to the same extent that Meta is or trying to be competitive here or even Google with Gemini. Especially someone like Dylan will tell you, if you’re not trying to compete at the frontier, there’s really not a place for you, especially if you’re only dedicating a few hundred megawatts internally. One, internal use case is like serving Amazon retail, but then two, training. There are a lot of commitments to make to be good at this.

It’s a conversation for a different day, but I look at these Microsoft job cuts and I see it as the glimmer of evidence that they’re going to try to compete in the future. They obviously got burned pretty badly by OpenAI.

Yeah. They have, in the new agreement that they signed, the right to monetize OpenAI models for essentially not paying OpenAI anything within that agreement. They’re going to have some interesting things ahead where they monetize the OpenAI models or even through Microsoft 365 Cowork and Copilot applications where they’re not paying OpenAI anything for a frontier model.

The other dynamic here, and you brought it up earlier, is over the last few weeks, there’s just been a lot of stress about neoclouds — whether they will succeed, whether they will fail. I think Elon Musk said there will be a guppy-like extinction event, which is just a brutal metaphor to use to describe a bunch of data centers.

But this is a bunch of circular financing and Nvidia stood a bunch of them up and maybe the hyperscalers are just going to run away with it. Maybe Anthropic’s demand, because maybe they will want to own more of their own compute because renting it is precarious in all these ways.

What do you make of the neoclouds? Do you think they’re going to survive the market actually shaking itself out as these companies go public?

Elon obviously has some incentive to say neoclouds are going to be extinct. ClusterMAX said something else and just does amazing ratings of the neoclouds. There are a lot of neoclouds that are ex-crypto miners that are not good businesses and are not good at operating clusters.

I just want to point out CoreWeave is an ex-crypto mining company, right?

Yeah. I don’t mean CoreWeave, but there are others further down the list. CoreWeave, Nebius, and anyone that has backing or backstops from one of the major labs, hyperscalers, Nvidia, or Broadcom is going to be okay.

It’s that longer tail. Hyperscalers have been 65 percent of CapEx and net new compute brought online. There’s 35 percent of the market that doesn’t have the balance sheets that the hyperscalers have. Both Google and Meta have recently raised or announced they’re going to raise. When we look at the big four hyperscalers, they don’t actually need to raise that money over the next two years, even though CapEx is growing from $1.2 to $2 trillion pretty quickly.

But for a lot of these other neoclouds, if you don’t have that sort of backing, I think it is very hard, even right now, and becoming extremely difficult if you don’t have the backing or backstops from those players to keep building compute. It’s a very, very tough financing market.

One of the things I think is really interesting about Elon in particular talking about neoclouds dying and obviously hyping up his own data center business is he’s trying to put them in space and to get away from the backlash in the United States around data centers in particular.

We have a lot of coverage about data center backlash in the United States, it is slowing down a lot of projects. But at the rate we’re going, if you think the neoclouds are shaky, you might actually end up abandoning a bunch of GPUs and half-built data centers or have them tied up in financing agreements where they can’t be lit up.

What do you make of that? Do you think we actually just need to go to space? Or do you think the market is going to rationalize and actually take advantage of all the compute that is currently allocated but not being used?

We’ll rationalize more so. The market is very good at finding places to put chips here on the ground. Politically, we’ll see what happens next week with midterms and the fallout from that. Obviously, there are some very large sites that still have massive permitting problems. There’s the entire power equation as we look towards next year.

The data centers will be built. There will be a method to get these built. The biggest thing — and the hyperscale CFOs have said this — from an overbuilt perspective and on a relative basis, it’s pretty cheap to build the data center shell. What they can do if they overbuild is they’re going to say, “We’re just not going to take delivery of the chip. We’re not going to buy chips. We’re not going to fill them up.” They’ll just sit empty and chipless. But the majority of the spend is on the chip side.

So if we do end up in a place where we’re actually oversupplied from a data center perspective, I know that’s a little bit different. It’s the exact opposite of what the question was. They have said that from an ROI perspective. This comes back to that larger question of whether we are still going to be super supply constrained. A lot of people now, especially in the last three weeks, are talking about, “Are we in this massive glut of compute as we look towards 2028 actually?”

Because the same thing we talked about from Anthropic going from negative 94 percent margins to positive 85 percent and compute efficiencies mean as you bring on more inference megawatts that are making a lot more revenue per megawatt, all else SQL, you need less compute. So it’s a question of whether we we going to have enough revenue in 2028 to justify the ROI on $2 trillion plus of CapEx.

This is why I spent so much time asking about capability overhang and how good the models are today, because you can see some competitor that is less idealistic about AGI saying, “Actually, we’re going to do a bunch of forward-deployed engineers in all of these verticals where they haven’t taken advantage of AI and sell them high-margin inference because we’ll automate big chunks of their business and they’ll see the return.” Right now, a bunch of the Fortune 500 has not seen a return on AI spending.

So if you’re actually just better at customer service and deployment and productizing the model, you might get way ahead of where Anthropic needs to be because they’re still thinking about AGI every single minute of every single day. I look at Dario standing next to Marc Benioff at Dreamforce and that dude does not want to be there right now. He wants to be thinking about the machine god.

There’s something there where you can just see competitors coming up with an open source model and saying, “We’re actually going to productize this and we will actually take the revenue that everyone else is depending on.”

Yeah, it’s extremely, extremely interesting. In the interim, that’s why it is getting more verticalized because you need something to bridge AGI where it just fully does the job, you need something to bridge the actual model today.

[Laughs] Yeah. We’ll just take that for granted.

To get there, you need some bridges of where it sits with the actual end user at some point. Everything is going to come down to this: Is there going to be some timing or adoption mismatch where we just don’t get the revenue at a certain point of time to justify that chase of “train and compute towards AGI”? That’s a risk.

The other risk we look at is whether we get more models at the frontier even at the open source that are as competitive in coding, where token pricing across the frontier needs to be taken down, because like I mentioned earlier, there are lower switching costs. Even at SemiAnalysis, we went from 95 percent or 90 percent-plus of our usage at the end of Q2 was on Anthropic’s models down to 70 percent after the release of OpenAI’s ChatGPT 5.6 and Astra. And then with Opus 5.5, it’s gone back to 90 percent-plus roughly.

It does come back. Even the base of revenue today — and they’ve said that we have net revenue retention of 900 percent, so they’re seeing this massive, massive growth. This isn’t a traditional software business like ServiceNow or Workday, where you have just an incredible logo or gross retention of 95 percent to 98 percent and customers sign these nice three-year contracts, they never churn, they add some seats, and maybe they adopt another product that is being upsold. This is purely consumption.

The other portion was the 20 percent drop in the last two weeks of the year versus the prior two weeks last year in token spend, because of the holiday season. You’re not going to do work code stuff, you’re not going to be coding for work during the holidays. This is extremely, extremely pure consumption business, even different from how we think about Snowflake or Datadog today in public markets.

Obviously, Anthropic is not the only company that’s going to have an IPO. OpenAI is right next to them. They’ve delayed theirs. You mentioned earlier Anthropic is much more enterprise focused. I think OpenAI for a long time thought that Google wouldn’t react to them and they would just take the search business away and everything would be fine. Google obviously reacted for better or worse. Search is now AI Overviews.

Looking at the Anthropic S-1, what are you looking ahead to with OpenAI? Because they are a more consumer facing company.

OpenAI was 60-40 consumer, 60 percent consumer and 40 percent enterprise at the end of Q1. That didn’t flip for the first time until January or August to be enterprise focused. What they’ll tell you is enterprise business — because it was so consumer and subscription focused, this consumption business that’s 80 percent of Anthropic’s revenue — didn’t take off until a release of 5.6 and then with Astra.

Those are really great models. OpenAI took the majority of actual net new ARR in Q3, but it’s going to take some time because what’s been in the Wall Street Journal, like negative 100 percent EBITA margins versus we’re seeing positive 11 percent here.

There are some differences, some pretty big differences, in the business model where they just don’t monetize at the same rate that Anthropic does. That’s a little bit because the business makeup — the verticals, that consumer-versus-enterprise split — and that’s changing.

What they’ll tell you is they see a really good Q4 and they have a much stronger enterprise sales function than Anthropic has. I expect them to come up, but I don’t think the financials are going to look as good as this even when they drop their S-1 maybe in early 2027.

Do you think that’s why they delayed it? To get their financials looking better?

Yeah, I think OpenAI had a really strong Q3. Enterprise grew 100 percent quarter-over-quarter versus the total business which was 77 percent. You get another strong quarter of enterprise here. If Opus 5.5 didn’t take a ton of share, that would put OpenAI in a much better position to tell the story.

There are some other turns here between now and when Anthropic actually goes public. They’re going to do a roadshow. There’ll be some pricing events. What are you looking for from Anthropic?

They did an investor day two or three weeks ago where they did give some more color. I think they’ll walk through why Q3 was so weak. Meta was a very, very large customer, probably over 10 percent. What’s been publicly reported is they went from 60,000 Claude Code seats down to 30,000. These token volumes didn’t disappear, they just shifted into Meta’s internal models.

Anthropic started cracking down on anti-distillation, and that was 5 percent of revenue prior. I think they said 5 percent to 7 percent of revenue in the S-1 and stuff against their terms of service. So what’s here on the roadshows is a lot of this October acceleration after Opus 5.5. We believe that they’re back on track.

If they were doing $10 billion of net new ARR per month in Q2 and that fell down to $4 billion in Q3, that they’re getting back on that $8 billion to $10 billion pace here in Q4. People want to hear about these new verticals, specifically cyber. They’re doing some patching until they have that full cyber SKU rolled out, but they’re definitely monetizing cyber today for vulnerability code scanning. These are not small contracts, I should say, with existing customers.

I think they’ll start to message what the 2027 ARR growth path looks like. The other thing too is expectations management, keeping numbers low enough, not talking about AGI as much.

[Laughs] It’s hard to do expectation management when your risk factors are like, “We could pose an existential risk to all of humanity.”

[Laughs] Right. And so saying you do that — you’re going to achieve AGI at some point, you’re going to replace everyone’s jobs — but then trying to keep numbers low enough for Q4 and to have this massive beat the first quarter you become public and have a decent guide for 2027, it’ll be a nice mix of seesawing between that long-term vision and short-term expectations management.

There’s a lot going on. Joey, this has been great. We’re going to have to have you back as these companies barrel towards actually being public and their economics become much more visible. Thank you so much for being on Decoder.

Thank you so much. I appreciate it.

_{Questions or comments? Hit us up at decoder@theverge.com. We really do read every email!}

Texas Attorney General Ken Paxton could have picked any number of messages for his first Senate campaign ad of the general election back in May. Texans care a lot about cost of living, border security, healthcare, and corruption, among other issues. But Paxton’s very first ad went with something that pollsters don’t generally ask about. He accused his opponent, Democratic state Rep. James Talarico, of being “Too Low-T for Texas.” Too low in testosterone. Not manly enough. 

Voters generally don’t rank masculinity as a top issue in any race, but Paxton’s opening salvo wasn’t completely out of left field. Young men broke for President Donald Trump by a shocking margin in 2024. During that campaign, Trump played to the “manosphere”, appearing on many a bro-y podcast and leaning on his macho, politically incorrect image for an audience burned out on the politics of Woke 1. 

Paxton, whom Trump endorsed over incumbent Republican Sen. John Cornyn (R-TX) in the primary, is as closely linked to the president as any candidate on the ballot — so it’s not all that surprising to see him attempt the same strategy.

And Texas, after all, has its stereotypes: rugged individualism. Cowboy boots. Smoked meats. Texas Rangers. The list goes on.

Starting with the “Low-T” ad, the Paxton campaign has been all in on exploiting the politics of masculinity and traditional ideas about gender and gender roles to cast Talarico as not man enough to serve as senator — and the rest of the Republican ecosystem has followed suit. 

In May, Trump policy adviser Stephen Miller tweeted that “The Democrats made history in Texas by nominating their first transgender senate candidate.” Vice President JD Vance recently walked right up to the line of calling Talarico gay at a rally in the state. Elon Musk’s super PAC has flooded the state with AI slop commercials like this one, in which an adult drag queen in a sparkly jersey dunks on some female athletes. The commercial attacks Talarico for being supportive of trans athletes. Trump himself has also weighed in, accusing Talarico of veganism — fighting words in some Texas circles. (Talarico, 37, is a cis man, says he has a girlfriend, and denies being a vegan.)

Attacks are one thing, though, and an effective political strategy another. To figure out whether Paxton’s masculinity campaign is working, the Today, Explained team headed to Texas.

“People are mad about other things”

At a Paxton rally in Fort Worth, Texas, on a recent Monday night, Jacenta and Susan Sims were riling each other up, seeing who could get the best dig in at Talarico’s manhood. 

Susan pointed to her own chest. “My shirt says ‘No Tala-freaking-way.’ Because he is kind of a freak,” she said. She listed some of Talarico’s past comments on gender to support her statement. “Like, how are you talking about God like he’s nonbinary and there’s six sexes?” 

Talarico said God was nonbinary during a Texas legislative session in 2021, making what he later described as a “cringey” point about God being above human categorization. Also in 2021, he claimed during a debate over trans kids in sports that there were six sexes. He recently walked that statement back, saying there were only two sexes.

Jacenta Sims at the Paxton rally wasn’t having it: “If you really had to look deep, he’s probably got some lace on his panties. There’s nothing masculine about him.” Susan piped in, “He looks like a little boy. He’s not tough enough.” Back to Jacenta: “And we need masculinity back in Texas.”

Perhaps it’s not surprising that voters who are already all in on Paxton would also be all in on this line of attack. But those are not the voters Paxton needs to convince.

“I don’t care if Talarico’s gay or not. I don’t believe he is, but it wouldn’t matter to me if he is.” Jesse Sandoval said outside the Tarrant County Elections Center in Fort Worth. He’d just cast his ballot in early voting. “I just felt that they were doing that to try to deflect from the real issues.” 

Another early voter, Michael, didn’t want to give his last name, and works as a cook at a local restaurant. “I just feel like this whole toxic masculinity thing is so unnecessary,” he said. “I was raised by someone who was very, very aggressive and just a very macho man. And I feel like you have to educate yourself as to why those things are not — why saying stuff like that isn’t okay, you know?”

Walt Thompson, also at the polling place, said, “Because he’s soft-spoken, they feel that he’s gay. And you know, he’s not. He’s just not this big rugged looking guy. They can’t accept that.”

Nate, a 32-year-old construction worker who also declined to share his last name, said 2026 is a whole different moment from the last presidential election. “If this was 2024, those [messages] are effective. But I think this year it’s not gonna be effective,” he said. “People are mad about other things. When people care about gas prices, they can’t run on that.”

In other words, the culture wars hit differently when you can’t afford to feed your family or drive to work. 

It’s (still) the economy, stupid

Matt Angle is director of the Lone Star Project, a Democratic research PAC and communications firm. He says these attacks on Talarico’s masculinity are a tell from Republicans. 

“What the Republicans are worried about is people staying home,” Angle told Today, Explained. “Those people, they’re mad about the economy, they’re mad at Trump, and [Republicans] are trying to motivate them by playing to their prejudices. … They desperately need fear to be the motivator rather than anger and frustration.” 

So far, it doesn’t seem to be working. Most recent polling puts Talarico in the lead. The Cook Political Report is calling the race a toss-up. The last time Texas elected a Democratic senator was 1988, but Talarico appears to have a real shot at breaking decades of Republican dominance. 

Angle says Talarico’s laser focus on a message of affordability is breaking through to voters.  

“They’re understanding that their salaries aren’t going as far as they should. And they like that somebody’s talking to them about the cost of groceries, the cost of housing, the cost of healthcare,” he said. 

Who gets to own masculinity, anyway?

There’s another key factor in how the GOP’s masculinity attacks are landing: the messenger. Paxton, after all, isn’t exactly a paragon of traditionally masculine virtue. (Just ask Trump, who can’t stop needling his hand-picked candidate for the way he dresses, looks, and talks.)

According to Jill Tate, president of the Texas Federation of Republican Women, many of her members had grown skeptical of Paxton’s candidacy. That’s because his wife, Texas state Sen. Angela Paxton, filed for divorce last year on what she described as “biblical grounds.” The actual filing listed adultery as the reason for divorce. 

“I’ve been involved in Texas politics over 30 years,” Tate said, “and this is the first time I’ve truly been concerned we could lose a statewide [race] since the Republicans took over in the ’90s.” 

Angela Paxton recently did her ex a solid, giving a speech to the Republican women in Tate’s group called the “elephant in the room” speech. She also cut an ad boosting “the Republican ticket,” though not Paxton by name.

“She talked about the fact that while our candidates may fall down and they may do things that are disappointing and morally wrong, it is extremely important to remember that that is the human side. And that’s not what they’re going to do in office,” Tate said of the speech, which urged the audience to vote for the team — for Republicans — rather than on the moral failings of one person. 

Tate believes that the speech changed some minds and could push women in the room to vote for Ken Paxton instead of just staying home. But outside of a room of diehard Republicans, that message — vote for Ken Paxton despite Ken Paxton — may not be a compelling one, no matter how much ads try to paint his opponent as less masculine.

“Texas is a knife fight uphill every day for Democrats,” Angle, the Democratic strategist, said. But in 2026, the mix of a weak Republican candidate and anger at the economy might be enough to give Democrats a chance — and help neutralize Paxton’s efforts to turn the race into a referendum on a very specific view of masculinity.

Ryan Rusak, a veteran Texas politics writer, agrees. “I think that where Talarico can use this to his benefit is to turn it around to say, ‘Okay, well, these guys who wear the boots and eat all the brisket are the ones that got us $5 gas. They’re the ones that got us into a war in Iran. They’re the ones that have gotten it to where you can’t buy a house even in a place where we still make it fairly easy to build houses.’”

“Had we not had an environment like this,” Angle said, “I think it might have been harder for James to break through.”

If you were anything like me as a kid, trick-or-treating meant one, maybe two, pillowcases full of candy every Halloween. 

And as fun as collecting all that candy could be, the real fun began when I got home and dumped my winnings onto my bedroom floor. That’s when the sorting began.

I had some very specific rules: The usual suspects — think Smarties, Tootsie Rolls, and Dum Dums — went into one pile. Fun-size chocolates, like Snickers, Reese’s Peanut Butter Cups, and Baby Ruths, went into another. And then there was my prized pile: Skittles, Warheads, Starbursts, and Sour Patch Kids. Those were meant to be eaten slowly throughout November. The rest was fair game. 

The ways we sort and eat our Halloween candy are decided by some very particular, personal rules. But Health and Human Services Secretary Robert F. Kennedy Jr. would like to add another distinction: Which candies are made with artificial dyes?

Kennedy’s ire for synthetic food dyes is years old, and they’ve become a major target of his Make America Healthy Again movement. Last year, he announced a plan to remove “petroleum-based synthetic dyes” from foods, arguing that companies “shouldn’t be feeding it to the rest of us.”

That plan has become a multimillion-dollar problem for Mars, the maker of M&Ms, which promised customers last year that they would create an all-natural version of their tasty chocolatey treats. As the Wall Street Journal reported this summer, however, its latest offering is missing one of the most iconic colored M&Ms — the blue M&M. 

M&Ms aren’t the only snack food in Kennedy’s crosshairs: He has called out Doritos, Cheez-Its, Cap’n Crunch, and gummy bears, saying their ingredients include “a lot of poisons.” On Fox News, he described what children eat as “food-like substances” and also said that “some of it was made in petroleum refineries.” 

In reality, the evidence is more complicated, because the Food and Drug Administration has long considered many of these approved synthetic dyes to be safe under its rules, while acknowledging that some children may be sensitive to them. Kennedy’s sweeping accusations go much further. 

Still, pressure from Kennedy and those in the MAHA movement has led many companies to rethink the recipes of your favorite snacks. But producing those alternatives isn’t easy or cheap, as the story of the blue M&M illustrates. 

Jesse Newman, a food reporter for the Wall Street Journal, went inside a Mars factory in Topeka, Kansas, to see the process for herself. She spoke with Today, Explained co-host Noel King about why blue is so difficult to produce naturally, and what changing a candy’s color actually accomplishes. 

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get your podcasts, including Apple Podcasts, Pandora, and Spotify.

The Secretary of Health and Human Services, RFK Jr., has some issues with the blue M&M. What, what exactly happened? How did it draw his attention? 

He is not a fan of any sort of chemical. He’s really concerned about toxins in our food. And Blue 1, which is the food dye that makes blue M&Ms blue, is a synthetic chemical. 

He really takes issue with artificial dyes. He believes that they cause hyperactivity in kids, some neurological challenges. He thinks artificial dyes are linked to cancer. 

As a member of the Trump administration, he formally set out to get them removed, didn’t he? 

Oh yeah. He’s been putting a lot of pressure on the industry to strip artificial dyes from all kinds of products.

What do we know factually about artificial dyes? We hear that they’re bad for us. We hear that a lot of things are bad for us. We’re all still alive and kicking. Are artificial dyes really detrimental to our health? 

The FDA for decades has said that there are nine artificial dyes approved for use in food. And they said that those artificial dyes are safe and have said so for years and years and years, as have other global bodies, so long as they’re used in accordance with some of the standards that the FDA laid out. 

A California state agency has found that dyes are linked again to hyperactivity in children. And the FDA itself has said, ‘Okay, we think that these dyes are safe for the vast majority of kids, but some kids might be more sensitive to them than others.’

So I think the real issue is that it’s a chemical doing it. They’re purely cosmetic. They don’t do anything except color food. There is no nutritional benefit that you are getting from these dyes. And so do we need them? Absolutely not. 

I think one of the issues is that if you’re looking at the ways our food contributes to health problems, artificial dyes are probably pretty low on the list.

You went inside a factory where they make M&Ms, and you looked at how they’re trying to make this happen. Tell me everything. 

I went to this plant in Topeka, Kansas, to see how they were made. And it’s a massive industrial food plant, where they mix these colors and spray them onto these small chocolate orbs, which they refer to as lentils.

The M&Ms move through the plant, and they arrive at these massive [machines] that they call pans, but they look like big tumble dryers. And the M&Ms just tumble around in these pans, and the color is sprayed on. It’s a very, very industrial process, millions of M&Ms a day. And the challenge that Mars has now is making that happen with a natural dye instead of an artificial one. 

A blue natural dye is the challenge. What are the problems?

They’ve been working on this for years. And they went with a product called spirulina, which is made from algae. But spirulina comes with a host of problems that they are now dealing with. 

Blue 1, which is the artificial dye, arrives at the factories as a liquid. And they pour it into these mixers and they mix it up with this sugary syrup and it’s pretty easy to handle. Spirulina arrives as a powder. So now you’re mixing a powder into this same mixture, into the same recipe, and that is very different. 

Because spirulina is a protein, the resulting mixture becomes a lot thicker. What they found was that the mixture containing spirulina would really clog up the piping. It was getting stuck. It moved less smoothly through the pipes. 

Also because it is a protein, it was starting to coat and build up on the inside of the machinery. And when that happens, it’s a food safety hazard. It can mold; it can cause problems. For many reasons, it was a challenge to handle. 

How much did this all cost? 

I should say it’s not done. Mars wouldn’t give me an official figure for how much they spent. But they said that they are spending millions and millions of dollars. 

They’re having to retrofit their plants, essentially. Mars said that they’re having to change about 300 types of machinery in their plants. It’s a real investment. And at the end of the day, it all comes down to cost. 

What did they actually end up getting done? What was the outcome here? 

Mars said what they committed to was that they were going to release a new version of their M&Ms and a few other of their products this year that were made with natural dyes instead of artificial dyes.

They didn’t come out and say we’re eliminating artificial dyes. And so folks should be really clear about that: Their artificially dyed M&Ms aren’t going anywhere. They are still on shelves. 

What they said is that they’re going to come out with an option that is naturally dyed. So they tried to do that. And what they found was that they couldn’t do it at a cost that was acceptable to them. With the blue and with the spirulina, it would have been far too expensive to make it work at scale. We’re talking millions and millions and millions of M&Ms per day.

They had problems making the green, the blue, and the brown M&M because, if you go back to your elementary school color theory, they needed blue to make all of those M&Ms. Ultimately they said, “Okay, we can do green. There’s little enough spirulina in the green to make the green M&M.” But blue and brown, they are not able to get there yet due to the amount of spirulina that those colors require.

And so earlier this year, they launched their naturally dyed version of M&Ms with red, orange, yellow, and green M&Ms. And if you take a look at this bag, my colleague referred to these as autumnal. They look very autumnal.

They look sort of muted.

You know, it really isn’t the same. It looks like a mature person’s M&M.

At the end of the day, what are the changes to the M&Ms? Let’s say I go online and get the natural dyed ones. What does that mean for my health? Am I now a healthy and virtuous person if I’m eating the autumnal M&Ms? 

It means very little. 

I would say you are, hopefully, still enjoying that sugary treat and the pick-me-up in the afternoon as you’re starting to tire. But you’re still eating candy; you’re still eating sugar. It really hasn’t changed very much.

Democrats have been emphasizing lots of issues in the runup to the 2026 midterms: The Iran war. The state of the economy and healthcare. Corruption. And…hotness.

Specifically, their candidates: The internet is awash in clips of Michigan candidate Abdul El-Sayed pumping iron and podcasters proclaiming that “America deserves a hot president” in a video interspersed with photos of Georgia Sen. Jon Ossoff.

Having a good-looking candidate is by no means a new tactic — famously, it may have helped John F. Kennedy win election over Richard Nixon — but the online left is adapting that strategy for the internet and fandom age. 

Grace Panetta, a politics reporter for The 19th, wrote about how “thirst edits” of Ossoff in particular are proliferating online. Panetta says the organic origins of a lot of these videos are of particular interest to Democratic operatives, who see it as a way to gain back ground they lost on the internet after the 2024 election. 

Panetta spoke with Today, Explained co-host Sean Rameswaram about who’s thirsting over Democratic politicians in the first place, how 2026’s hot candidates are different from those of yore, and whether it’s actually giving them a boost. 

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get your podcasts, including Apple Podcasts, Pandora, and Spotify.

Where are these edits coming from?

Regular online creators. And it’s important to note at the outset that these are not paid partnerships. The campaign is not paying these influencers to make edits about how they think their candidate’s really attractive. 

That’s partly why I wanted to dig into it, because it’s organic. These are just online creators wanting to draw visibility and attention to a candidate that they really like.

Jon Ossoff is currently running for reelection in these midterms. How do we know for sure that he isn’t somehow behind the campaign?

I spoke to several creators who make these videos and they said that they’re doing it for the love of the game and they’re just supporters. His campaign did not give me a quote or a statement for this story. So it’s fair to assume that he’s not directly involved and he doesn’t repost these videos. 

But as people pointed out to me, his campaign knows that they have an attractive, compelling candidate. And they’ve previously been vaunted for their digital strategy this cycle of putting out very high-quality livestreams of his rallies. There’s a lot of material for an enterprising TikToker who wants to make these edits or clips. They have a lot to work with. 

His campaign, as one person put it, is definitely playing into that, but not directly engaging. It’s a fine line to walk.

Is it just an Ossoff thing or is this going on with other candidates? I do recall that Abdul El-Sayed hits the gym.

Famously so. Yes, he hits the gym. I just watched so many videos for this story. I also came across a fair number of Gavin Newsom edits. There are people who think he gives sort of a Patrick Bateman, American Psycho vibe.

There are also official Democratic accounts, including the TikTok account for the DNC, the headquarters account, which was formerly Kamala HQ, who have been posting edits of Ossoff and also Abdul El-Sayed, who kind of leans into this gym-bro persona. 

The headquarters account posted a side-by-side of Ossoff and Abdul El-Sayed with the caption, “There are 69 days until election day.”

Nice.

Yes. There are also lots of edits of Mamdani, and former President Barack Obama. Obama nostalgia content goes hard on the internet. So you’re seeing these more official side Democratic campaign accounts leaning into it and playing up their candidates.

Having an attractive candidate is nothing new. You mentioned Obama. JFK was famously dashing. What feels different about what you’re seeing now on social media?

I think this is really a culmination of a lot of different things happening right now in politics and specifically within the Democratic Party. 

After their loss in 2024, there was a lot of conversation about the gerontocracy, how we’re governed by a lot of really old people, for the most part, in this century. And also about Democrats’ digital strategy and the aftermath of 2024. 

One thing that a lot of people in that digital space have been talking about is how Republicans and the Trump campaign really capitalized on getting that organic engagement on platforms like TikTok and Instagram, where a lot of Americans are now going to get at least some of their news, and also engaging with and encouraging the creation of this kind of organic content on platforms and from creators that are not always expressly political or official-side. 

“A candidate’s messaging strategy is only as good as the content and only if it meets people where they are and actually speaks to a real need people have.”

As one Democrat I talked to put it, she thinks it’s a way for Democrats to win back the internet and to really create a contrast with the Republicans. And she said to have fun on the internet because Republicans are having fun on the internet and it appears to be working for them, or at least it was in 2024.

Is there something about this being something on the left that makes it sort of tricky? This is, broadly speaking, objectification, right?

It is a fine line between thirst and objectification. And there is also a gendered element to it that it is mostly men that these types of videos are being made about. 

Now, granted, a lot of people make sort of hype edits or positive content about AOC because she’s a very popular female politician on the left, but it’s true that women candidates are held to higher standards in terms of how they present themselves and how their supporters portray them. 

It is a very real dynamic that you could have all these videos about Jon Ossoff, and it’s not seen as detracting away from his overall message or his seriousness as a politician.

Is there a drawback of focusing on looks? Does it make the Democratic Party or these candidates seem superficial or not that serious?

President Trump has been the defining figure in our politics for 10 years now. And he is famously very, very image focused and image obsessed. We live in a very image-obsessed society, and I think there’s kind of a bipartisan acknowledgement of that. 

And looks matter to people in all kinds of ways. They do matter in politics, they do matter to voters. Whether you like that that’s the case or not, it is the reality. And I think the way that a lot of people on the left see this is, people want to look at attractive people. People take attractive people more seriously and are more willing to listen to them. So we should play into that and play that up. 

That’s also been the case on the right. President Trump famously loves people out of “central casting.” There’s been this whole movement on the right about making conservatism sexy again. And especially at the beginning of the second Trump term, you had all these influencers talking about how the second Trump term was going to usher in this great age of hotness, which is of course very based on sort of stereotypical male-centered Eurocentric beauty standards. 

I think the genie’s out of the bottle on this one in terms of the fact that our politics and society is very image-obsessed. And I think the left, being locked out of power, realizes they have to play on those terms and they have fun doing it.

You could look at it as giving “Kamala is brat,” which famously did not work. Is it working in any tangible way for Ossoff, for Abdul El-Sayed, or anyone else?

I think a lot of the time in politics, the success of a message is really dependent on the broader political situation. I think a part of the reason that the Kamala’s brat thing didn’t work is people were like, “Okay, that’s great, but my gas is too expensive and prices are too high and I’m not happy with how things have gone under the Biden administration, so I don’t really care.” I don’t know that specific digital strategy makes or breaks a campaign or candidate, but it feeds into a bunch of larger factors. 

Something that a lot of people I spoke to said they liked about Jon Ossoff is how he is incredibly serious in Senate hearings. He doesn’t grandstand. He really holds Trump administration officials’ feet to the fire. He’s been very focused in his role in the Senate and on the campaign trail about calling out corruption. He’s a very, very gifted speaker and orator.

So I think a candidate’s messaging strategy is only as good as the content and only if it meets people where they are and actually speaks to a real need people have. And I think people are really unhappy with the second Trump term and politicians being super old and out of touch, and it’s a perfect storm of factors that makes it work for him.

Today, I’m talking to Kevin Roose, journalist and author of the new book The AGI Chronicles, which details the recent and explosive transformation of the AI industry.

Kevin was a longtime New York Times reporter and host of the popular podcast Hard Fork, but he and friend of the show Casey Newton just left the Times to start the all-new tech podcast Machine Gods, which launched last week.

Kevin and I talked about launching Machine Gods and what it’s like to go from The New York Times to being an independent creator — and then of course we talked about the book, which is an excellently reported dive into the companies racing to build artificial general intelligence.

I wanted to get a sense from Kevin of what it was like to report this, to try and understand these characters and this moment in time, and where it all goes next. Fair warning: This conversation takes a pretty philosophical turn at the end, but I think you’ll find it a really worthwhile back-and-forth.

Okay: Kevin Roose on The AGI Chronicles, starting Machine Gods, and where AI goes from here. Here we go.

This interview has been lightly edited for length and clarity.

Kevin Roose, you are the author of The AGI Chronicles and the cofounder and co-host of the new podcast Machine Gods. Welcome to Decoder.

Thanks so much for having me.

I was listening to the first episode of Machine Gods and you and Casey discussed the fact that technically you have the title of CEO.

It’s true. I won the coin flip and we needed someone. When you start a company as we have, you need to list someone as the CEO, I guess, to know who to haul in front of Congress when our first scandal inevitably breaks. So that’s going to be me.

It’s funny because you’re a CEO on Decoder. It means I’m going to have to ask you the Decoder questions.

[Laughs] Okay. Well, I’ve been a CEO for about five minutes and most days I frankly forget I’m the CEO.

Honestly, that tracks with most of the CEOs on the show. They all act like they’ve only done it for five minutes. We’ll come to it.

I want to talk about your book. It’s called The AGI Chronicles. It is a meticulously reported book about the main frontier labs and the culture shift they’ve all undergone as AI has come into the forefront and become a much more commercial product in many ways.

But let’s just start with Machine Gods. You were a journalist for The New York Times for a long time. Obviously, I think the audience probably knows this, but you and I have known each other for a long time. I will say that since I have known you, your desire to be a YouTuber has been top of mind. You’re just like, “How do I get over there?” And I’ve always been like, “Run, don’t do it.” But you did it.

You left The Times, you started your own podcast with our friend Casey Newton. It is the next generation of the very popular podcast, Hard Fork, which was excellent. And I’m excited for you, but what made you take the leap?

Yeah, you have been trying to convince me out of this for as long as I’ve been trying to convince myself into it and you have not succeeded because here I am.

Yep, I failed. Utterly failed.

No, look, I think that for some very good reasons, media companies have long been a little bit wary of going all in on YouTube or any other video platform. The ones that have gone all in have not necessarily come out of that with good feelings about it because there are a lot of–

Yeah, they pivot to video and also into death, routinely.

Yeah, you pivot to video or you sort of waste a bunch of money doing things that don’t pay for themselves. So, I think there are some structural economic reasons for that, but I also think it’s that there aren’t a lot of institutions that are equipped to make that kind of a long-term bet.

I’ve been trying to YouTube-pill people in media for many years, as you know. You’ve been trying to undo the YouTube-pilling on your end, but I just think it’s clearly the most important media platform in the world right now. It’s a place where journalism has not historically had a central place.

If you were to look at YouTube as a whole and try to assess what piece of it is dedicated to what you or I would consider high-quality journalism, it’s a vanishingly small part of the overall ecosystem there.

So, part of my mission is just to crack that and figure out how to do YouTube and video in general in a way that is sustainable from an economic and a sort of creative standpoint. And then just to experiment and do a bunch of things.

This is not a face that needs to be on YouTube. So I’m also hoping to bring some other people in and nail some formats. But I look at what The Verge has done there. I look at what people like Joanna Stern and MKBHD have done there. To me, that is very exciting and it’s a space where there’s a lot less competition than text or podcasts.

Machine Gods is a podcast that you’re doing in partnership with NPR, which I want to talk about. But do you think of it as a YouTube product?

We want it to be video-first. What that means basically is that we are going to give a shit about what it looks like to a degree that we have not always done. We’re going to try to give people a lot of reasons to want to watch as well as listen.

Obviously, we know that there are some people who just don’t like video podcasts and so we want to give the audio audience something that is enjoyable, but this is the direction of things. You can’t do a podcast now without doing video on top of it. So we’re going to try to really embrace that and make a good version of it that is as good as two middle-aged journalists can pull off on YouTube.

Truly the future of media is middle-aged journalists pivoting to YouTube. I feel the same way because I’m now making more video and that’s what we’re doing. It’s going to be great.

The other reason to leave and to do this — and obviously people know I’m friends with Casey as well, and I’ve been talking to you and him about it for a long time — is that the AI story is here. There is a platform shift. There are new companies, new characters, new ideas to talk about in the world. It’s funny because in that context, usually you get a media shift as well. The way we tell stories or the formats we tell stories usually shifts alongside the thing we are talking about or the technology we’re talking about.

Here, YouTube feels like the most solid media foundation that exists. It’s the one that’s the same the most, even though it’s changing and it has YouTube Shorts and now you can A/B test everything, including your own face. But it’s the one that is the most the same. Instagram has undergone some massive change and it feels like that will continue happening.

Does it feel like YouTube is the most stable place to build as you’re trying to tell these new stories?

It does. I mean, obviously you never want to put all your eggs in one basket. So, we are also distributing video on Apple Podcasts and Spotify and we’re going to be everywhere. But yeah, it feels relatively stable.

The question I’m always wondering is what would it take to replace YouTube? Many companies have tried to replace YouTube, but to do that, you would not only have to build an experience that was better for creators and better for users, but you would also have to replicate the entire visual corpus of humanity. You would have to just get six million videos from plumbers about how to fix every individual sink and then upload it to that. It’s a really hard thing to displace. It is so ingrained for so many people, and I just think it’s going to keep growing.

We’ll come to this when we talk about AI, but a long time ago I asked Google CEO Sundar Pichai, “Well, what are you going to do if there’s no more websites?” And he was kind of like, “Well, we have YouTube.” And there’s just no arguing with that. You sure do. And it is just going to keep growing.

What has been the most surprising thing about going from The New York Times to what you might call the creator economy?

Well, we’re very new at it, but surprising to me so far is how much I like all the business stuff. I think in journalism, you’re always taught to stay in your lane, and I have never run a business before. Casey has run a business. I knew he enjoyed it. But for me, these are new muscles and I don’t enjoy all of it. Negotiating the insurance quotes for our defamation coverage is not what I would feel compelled by. But regarding actually running a business, there is something to this founder thing.

Yeah, it’s a good time. It’s funny, in talking to you and to Casey and Joanna, who also just left and started her own thing, that comes up a lot. From my perspective, it’s why I’ve been doing this a long time. What if I stopped running the business? That doesn’t seem to be a choice. This is the future of media — taking control of your business and taking control of your audience. There’s something very powerful there.

One of the things I want to talk about, and then I definitely want to talk about the book at length, is the audience for AI coverage, because I see it in two ways. There’s a group of people building the stuff that loves it and wants to consume all of it. There’s a group of people that truly hates it and thinks all of it is fake.

And then there’s what I would call an expanding group in the middle where the products have become more useful. You have to look at them and evaluate them as they are. They were not terribly useful a couple years ago. The promises did not match reality, but every day now it can do one more thing that it couldn’t do before. Whether that thing is hacking all of the websites in the world, we’ll set that aside, but AI can do things it couldn’t do before and the audience seems to be changing.

How are you thinking about the audience for Machine Gods and how it might grow or change?

I mean, right now we’re just trying a bunch of stuff that we think will be good and we hope that it will find its sort of natural audience. But I think you’re right that the audience is changing. I think for a while there was a lot of demand for cope — basically people telling you this is not happening, you don’t have to pay attention to it, it sucks, it’s hurting the environment.

There still is in some parts of the internet. YouTube has a weird amount of this still going on and Reddit is also very anti-AI. But I think most people, or at least maybe a plurality of people, are either resigned to or excited about the fact that this is not going away. That is the audience that we’re looking for.

We’re not trying to tell you that AI is amazing and we’re going to be in AI utopia under the new machine regime. We’re also not telling you that this stuff is fake and sucks and is going to go away on its own and so we don’t need to do anything to regulate it or be worried about it. Casey’s phrase for this is AI realism. He thinks there’s a big chunk of people who are just sort of curious and interested and maybe a little scared, but their reaction to the fear is not to try to bury their heads in the sand, but to try to understand the thing.

So we started feeling this when we were doing Hard Fork where we would do something that just seemed kind of not our vibe. We would do a Claude Code walkthrough tutorial where we would just spend half an hour building a website and film ourselves and throw it up and it would do great. So people clearly were curious, and even if the comments on the videos were all from people who hated AI, there was clearly a lot of demand out there for people who were just like, “I kind of want to know what’s going on.”

“I hate that I can’t stop watching this” is a real theme inside of AI coverage for a variety of reasons.

Let’s talk about the book. I think that’s going to frame a bunch of the other questions I have. The book is meticulously reported. It is really fun to read. And the point of it, as I’ve heard you describe it, is to tell the history of the deep learning revolution because all these people just talk in Signal and in extremely childish tweets.

Tell me about that gap because this is an industry that is obsessed with documenting itself for computers and being legible to computers and not at all to other people, which seems wild to me. So explain the reporting of this book, because it feels like convincing them to even tell you what happened was a slog.

It was, yeah. So basically the reason I wrote this is because I was scared that all of this stuff was going to disappear. I am a history buff. I love to read books about the Wright brothers or the electrification of rural America or the moments of great invention during the PC revolution. I’m such a sucker for that stuff.

What you notice as you read more of these books is just that they all rely on a lot of contemporaneous notes and evidence — the lab notes from the scientists developing the atomic bomb, the correspondence between the Wright brothers and their friends and business partners — that is preserved and archived.

It was just clear to me reporting on AI every day that there was not going to be anything remotely similar for this stuff because A, all the people building this stuff work for private companies. They’re not government employees who are legally required to preserve their correspondence. And B, the Signal messages and Slack messages are all set by the lawyers to auto-delete after a certain period. So there was literally going to be kind of a mass disappearance with each passing year of these, I think, historically important artifacts, moments, and stories.

And then C, the researchers are all too busy to keep notes. They’re all grinding because they’re trying to build the machine god. So, I thought as a journalist, but more so almost as a historian, which is not a role I’ve ever officially played, but one I think I was playing with this book. I was just like, “I’ve got to just get this stuff because I have this sort of privileged ringside seat. These people talk to me. I know some of them will sit down and talk to me and tell me the stories.”

We did a lot of it on background so they could be protected from the consequences of talking to me. But this was sort of my attempt to furiously get all the stuff and put it in the archive where future generations could look at it.

The theme that really jumps out at me as I read the book was there’s a moment when AGI goes from being a thing they’re all dreaming about to being a thing that they all have to build and the shackles come off and they say, “We have to do this,” and they all drive toward it as hard as they can.

You talk specifically about Google where the Overton window moved and suddenly the people inside of Google, who thought this was all a pipe dream and pretty silly, started talking about AGI. That moment feels like the single most important moment in the history of AI, where “Won’t it be great?” goes to “We better go as fast as we can.”

Talk about that a little bit, because that shift inside these companies feels under-reported.

Yeah, I think that’s absolutely right. I mean, people have been talking and writing about AGI or some precursor that wasn’t called AGI but meant the same thing since literally antiquity. And especially since the 1950s, when the term artificial intelligence was born, people were talking about it. Alan Turing was writing about the thinking machine that could do anything the human brain could.

So this concept has been around for a long time, but there was no technology anywhere on the market or in research labs that could actually do what people wanted it to do — that could take in information, learn to learn about that information, and then use that to make predictions and act in the world. People tried lots of different ways to do this and none of them worked all that well.

What really needed to happen was the transformer needed to come along. This architecture that Google developed in 2017 and published and then presented to, among other places, OpenAI, which took the idea of the transformer and ran with it. And that’s the T in ChatGPT today. But that was the–

Somewhere a Google PR person just leapt out of a bush to hand you a check.

They do love this line.

They love it when you say it. They get so happy.

They love it. They love it less when you point out that although they invented it, they absolutely failed to turn it into a product until after OpenAI did.

But yeah, it was a dream, but there was nothing to attach to the dream. There was no technology. And then the large language model came and suddenly it was like, “Oh, maybe this is the thing that could scale forever and keep improving over many orders of magnitude.” So, that’s the light bulb that goes off at OpenAI and then later at Google is like, “Now we have the tool to do the thing that we have always wanted to do.”

You’ve got a line in there where you just point out that next-token prediction has not failed yet — that it is doing all the things people want it to do. We’ve obviously had to develop lots of technology around it. There are harnesses to make agents work. There’s reinforcement learning. There’s all this stuff around it. But that core technology has scaled.

The reason I bring that up is that in 2023 into 2024, I would ask every AI person who would come on the show or that we would see on The Verge whether LLMs can do it. Can they do the thing you want them to do? Because I don’t think at that moment it was clear that they could.

We’re closer now. They’re all openly talking about AGI. We are watching Meta’s Muse just walk its little butt around the internet whenever it wants. Do you think LLMs can do it? Do you think they can get there?

I think they can. I’m not certain about that, but they’ve been shockingly good and effective so far. If you go back and you look at the first LLMs, it’s just like 99 percent of people thought this is crazy, that this won’t scale. And then it just keeps working at every stage, at every order of magnitude. I’ve asked people, what was it about next-token prediction that was clearly superior to everything that came before it? There have been people who have told me this actually exists in the human brain too. There’s a whole school of thought that says that what is happening inside the human brain is essentially next-token prediction at scale. Obviously, it’s more complicated. These are not one-for-one replicas of each other.

But I think this is the fundamental mystery at the heart of AI: why is next-token prediction so remarkably effective? I think we don’t know. I kind of think it’s one of these cosmic mysteries, but why all of this works is because next-token prediction turns out to generalize really, really, really well.

There’s a part of that where all these companies had to believe it. Dario Amodei of Anthropic obviously wrote his paper, “Big Blob of Compute,” where he said you can just do it. You can just dump data and compute at this and we’ll get there. Everyone else had to be convinced of this.

What path did the AI companies all take to be convinced of this, and are they all fully convinced of it now?

I don’t think they’re all fully convinced of it now. I think they are convinced of it to varying degrees. Ilya Sutskever has this phrase, “Feel the AGI,” that he would walk floor to floor at OpenAI chanting in the old days and reminding people to feel the AGI. I think the labs feel the AGI to varying degrees. I think Anthropic is clearly the most AGI-pilled of the labs, with OpenAI kind of a close second.

And then there’s Google, which I think has always struggled to feel the AGI. I think there are lots of reasons for that, but it’s very funny. I love this section of the book where there’s this internal memo battle at Google, where they would just go on their internal message boards and Googlers love to write these manifestos and then snipe at each other’s manifestos and things like that.

So a researcher writes this memo, “Say AGI,” which is all about how Google — if it wants to win in AI, recruit the top technical talent, and remain safe about how it’s developing AI — has to admit, through using this term AGI, that what they are building is more than just a bunch of tools to make your Gmail better and make your docs better and make your Google Photos better at recognizing the people’s faces. It is all actually building up to something like a kind of human-level general intelligence.

And then someone else immediately writes a memo that’s like, “Don’t say AGI, it’s a horrible, unscientific term.” They go back and forth like this for a while, and you’ll notice even today, [Google CEO] Sundar Pichai does not say AGI.

No, he won’t.

Demis Hassabis says AGI. Sergey Brin says AGI. So I think there are kind of factions within Google that either think this is still crazy and we should talk about these things as narrow tools versus I think this growing and ascendant faction that is saying, “No, no, no, we’re building AGI, or at least we better say we’re building AGI because otherwise all of our top people are going to go work for OpenAI or Anthropic.”

I think you and I had the same experience at Google I/O in May, where we watched Demis Hassabis end the whole keynote by saying, “We’re in the foothills of the singularity.” And then we both went and interviewed Sundar and said, “What does that mean?” And he was like, “Yeah, yeah, Demis. Cool guy.”

[Laughs] Take it up with Demis.

He was like, “What a kooky character that guy is, building the machine god over here. Let me tell you about the new features in Google Assistant.”

There’s some big disconnect there that maybe explains everything about Google at this point in time. The reason I’m asking about this in particular, about this moment when they all clicked over to realize somehow we have to talk about it, is that OpenAI and Anthropic were founded to do this. They were built to make this happen.

But they don’t agree on how it should work. I saw you at your book party in New York and you said that you could have retitled your book “Fuck That Guy,” because they all truly hate each other.

It’s true.

And yet it seems like they have the exact same idea — that they can get there with this technology. The commercial imperatives on OpenAI and Anthropic are very different from the commercial imperatives for Google. Right now, as you and I are talking, it’s not clear to me that they can get to AGI before they run out of money or before CoreWeave collapses or before the bubble writ large comes to some other conclusion about the state of the economy.

Do you think that their religious fervor at AGI is keeping them from running a business? If I ran Anthropic today, a logical thing you could say is we should stop training new models and sell the very capable ones we have to more people.

I think that belief in AGI is a double-edged sword. I think on one level, yes, if you are super AGI-pilled as the CEO of a frontier AI company, you are going to struggle to care about things like what is my profit margin on inference? Where is my next slate of enterprise customers coming from? Because how boring is that compared to “we are going to build the superhuman machine intelligence that leads us into the post-singularity future”?

On the other hand, I think belief is actually a key ingredient in AI success, because belief and the ability to act on that belief is what leads you to do these bet-the-farm moves that can really pay off and have really paid off.

Do you remember a year ago when everyone was saying, “Oh my God, OpenAI is spending so much money on compute; how are they ever going to pay for all this compute? Isn’t Sam Altman overextending?” Even Dario was giving interviews where he was throwing shade at OpenAI for spending so much goddamn money on compute.

Fast-forward a year and OpenAI is now the only major AI company that is not severely compute-constrained. That belief that led Sam and his executives to bet and maybe overbet on compute last year was the reason that they are in a better position than Google or Anthropic or Meta or anyone else today. So I don’t want to say it’s always a liability to believe this hard, because I think it actually does allow you to make the bets that do end up paying off if the scaling continues to work.

It’s interesting because I might reframe that OpenAI decision. You write very poignantly in your book about what people at OpenAI call “the blip,” where Sam Altman was fired for 20 minutes and then he came back and that cleared out a bunch of people from OpenAI.

It is the moment you described in the book where OpenAI went from being a research company into being a business. The rational business decision was, “We need to sell more AI to people. We ought to have as much of it as we can.” And Sam is well known to be a ruthless business person. I’ve heard people describe him as S-tier at raising money, which is just an incredible Silicon Valley phrase.

So I look at that as a business choice. They got rid of a bunch of stuff they were doing. They pivoted to making enterprise AI products, which is where the money is, and then they realized they needed to service that demand. You’re saying that was a bet on AGI, which to me is a more idealistic turn. Can you square those two?

Yeah, I think it absolutely is a bet on AGI because Sora, which they launched and spent a bunch of money and compute on and then killed, is a cool toy that might open up a new line of business for you, but it is not going to get you closer to AGI.

What actually gets you closer to AGI is sparking recursive self-improvement by building really good coding models and then turning them back on themselves. That was something that Anthropic was doing. OpenAI got distracted by the side quests and shiny objects that it had last year, and the company was getting its asses kicked. So OpenAI decided to trim the sails, cut fat, and really focus on coding and long-horizon agentic workloads. That is, as of now, the leading path to AGI or to whatever comes after AGI.

So yes, I think that was absolutely a bet on conserving resources by not spending them on things like Sora, but what they did spend it on was trying to catch up with Anthropic in coding so that they could reach AGI.

So when I look at Dario Amodei at Dreamforce standing next to Marc Benioff and he’s talking about selling enterprise software, is that just for show? That’s the thing I’m trying to square is they’ve all become enterprise software vendors in the realest way. They are B2B SaaS companies in the realest way now, but they’re also building God. You know these folks. Does that align? Are they like, “I have to take off my B2B SaaS hat now and go back to the altar?”

I think the B2B SaaS thing is the game that they realize they have to play, but I don’t think it is any of their true passions. I was talking with Sam Altman for this book and one of the things he said was basically all of this was an accident: “I was never supposed to be running a giant tech company; that just didn’t factor in.” But now you wake up and you’ve got thousands of employees.

Dario Amodei also has this very funny in retrospect document that he wrote in 2021 when they were just starting the company. It’s called “Vision for a NewCo.” You can go back and look at the predictions that Dario made about AGI, and one of them is he thinks that it will cost about $10 billion to build a full-fledged AGI, which was, I think, off by at least one order of magnitude and probably multiples. He also thinks that Anthropic will never need more than about 50 people to achieve AGI. I think now they have 5,000 or so people. So again, off by 100x.

So I think what has happened is that this has just taken a little longer than all of them thought and cost quite a bit more money than they thought. The enterprise SaaS stuff is how you keep the flywheel going and pay for the GPUs and for the salaries of the researchers. This is the table stakes of getting to keep pushing on the frontier and keep pushing toward AGI.

Are they ready to be the leaders of companies of this scale? This is another thing that I was thinking about as I read your book. They’re all very idealistic people, so much so that they all broke off from one another and made their own companies because they could not make their ideals align.

But none of them seem like great managers. I don’t know truly what they’re like, but “they’re idealists” and “we are going to run an enterprise software company” are not usually in the same sentence. Do you think they can take the pressure?

No, but I don’t think anyone can. What they are attempting, no one has ever done. People have built companies. People have built companies quickly. No one has gone from $0 in revenue to potentially a $2 trillion IPO in five years. That has never happened before. So look, I think that they are scrambling to build the plane as it’s careening toward the event horizon, but I think they’re doing about as well as anyone could.

I don’t think it would be a good idea for them to bring in some professional CEO from Coca-Cola to run the company. I just think it would all kind of fall apart because they’re all zealots and missionaries. They are all in this — not all, probably there’s some people in the SaaS sales department who are just kind of there for the paycheck — but a lot of the key people at these companies are united in their belief that they are building [AGI].

One person, I won’t say who, but one person at one of these companies recently told me that they think their company might be the last company. I thought, “The last company to IPO this year? What do you mean?” They were like, “No, we think this might be the teleological end of capitalism and there might never be another large company primarily run by humans.”

So these people are weird, and weird in ways that are worrying, but also very interesting. This is what I was trying to do in the book. I didn’t want to tell you that these people are terrible or great. It’s just that you need to know who they are. You need to know that they all hate each other. You need to know that they are this peculiar breed of thinkers to understand the dynamics of the race.

There’s a portion of your book where you talk about people splitting away from effective altruism to go become accelerationists, and you have a woman in there who’s like, “Well, the accelerationists have better parties, and I like those vibes better.” I thought to myself, “Well, what does that have to do with potentially killing everyone?”

But they are very human, even though they’re trying to build something that might ultimately dehumanize us all in various ways. What did you make of that as you were doing all this reporting?

The notion that there’s existential risk here looms over the book, it looms over the industry. Every time we do an episode on it, the audience is like, “Why won’t they just stop?” Bill Gates was just on Decoder and said, “You could just stop if you were the only company. If you thought you were going to be the only company with AGI, then OpenAI’s model would work. But the second there are more frontier companies, it absolutely won’t work. By the way, they might kill you all.” I thought to myself, “Well, Bill Gates is not very optimistic right at this moment in time.”

No, he is not.

What do you make of that — that they are racing ahead even though they know the risks are huge in the absence of any regulatory authority that could cause any of them to solve these problems?

I think there are probably two or three reasons that they’re doing it. I’ve asked them all pretty much. I talked to 150 or so people for my book and I asked all of them some version of this: “If it’s so dangerous, why are you doing it?” The answers would usually start with some fatalistic… I don’t know, you could call it inevitabilism. They were just like, “Look, someone is going to build this. The recipe is not that hard. All you need is a bunch of compute and a bunch of data and the right algorithms, and you get AGI. And so if it is possible, it will happen and it would be good for us to do it rather than people we don’t think are as trustworthy.” That is sort of reason number one, the harm reduction argument.

Then there are the true believers who say, “This is all going to turn out great, so long as we thread the needle, and if we can build this stuff without blowing up humanity, wrecking the entire internet, or developing novel bioweapons.”

Technology is usually a force for good throughout history. I don’t think a lot of people would switch lives with their great-great-grandparents. It sucked to be a subsistence farmer. I think there are people who believe that we are the equivalent of subsistence farmers today, and that what is coming will be so great that we will want to live in that world.

And then there are just people who are like, “Look, this is fun and I like doing it, and it’s fun to make the neural networks code. And so that’s what we’re going to keep doing.”

That aspect of it where every now and again I look up and I’m like, well, my computer just did something that I’ve never seen a computer do before, is fun.

It’s awesome.

It is. It’s legitimately fun. It’s some of the most fun I think you can have with a computer ever. Then I’m always led to think about, “Well, this came at some massive cost. I might be empowering some corporation that ultimately wants to kill us all.” Somewhere in there is the swirl of all the tech CEOs standing behind Donald Trump in the Oval Office to do something, to sign some sort of morally binding AI safety pledge. And all that feels very conflicted.

I would put that in the category of AI backlash. We hear the AI companies talk about, “Well, the technology just hasn’t diffused enough. People haven’t seen the benefits, so they naturally hate change. We have a marketing problem. We just need to communicate about it more.”

Is that just the prevailing view as you talk to these folks, that eventually the stuff will speak for itself, or do you think they’ve internalized that there’s more of a backlash?

I don’t think they’re surprised by the backlash. I don’t think they like it. They wish it weren’t happening. But I was talking to one CEO at one of these companies who said, “Yeah, I get it. We haven’t cured any diseases yet. Yes, we think our tools are capable of doing interesting things, but we don’t have a lot of things on the scoreboard in the big societal improvements category yet.”

I think there are some people in the industry who lament the fact that the chatbots came before the cancer cures and wish that they could have figured out a way to do it in the other order. It’s just that that is kind of the way the tech tree grew.

So they feel like now the only responsible thing to do is keep pushing on the cancer cures so that when people look at what has AI done to our lives, it’s like, “Well, yes, it helps my kid cheat on their homework and they’re addicted to an AI companion, but also my grandma is still alive and she wouldn’t have been if this medicine had not been discovered by AI.”

Yeah, there’s some dynamic in there that brings me back to Google, I think as this conversation has done many times, where your reporting on Google’s approach to AI was that this is just task-based software. “We’re going to make Google Search 10 percent better, Gmail will be 5 percent better, and we will continually deploy these improvements, and no one else has our access to data or our scale, and thus we’ll be fine.”

OpenAI shows up and it puts itself in Bing. Famously, Bing tries to make out with you. Still my all-time favorite… I can’t believe I haven’t brought this up yet. This is my all-time favorite story.

I can’t believe you haven’t brought it up either. I had an over-under bet going on how long it would take you, and I took the under in a minute.

[Laughs] Well, you and I have already talked about it in our lives. I was like, “I’ve got all these other deep questions.” But yeah, Bing is famously horny for my friend Kevin Roose. That moment I think just galvanized people: “Wow, these things can do a lot of things.”

Google had to react, and they didn’t react by going all in. They sort of stutter-stepped there. As you’ve been saying, they’re still not all the way there. Google still doesn’t think this thing is going to happen. They think they’re making better Google products for people.

When I look at the trial transcripts from Musk v. Altman about the founding of OpenAI, they’re all terrified of Google.

Yes.

They’re all terrified of Demis Hassabis at Google, specifically, doing the thing, just making it happen because he has the resources. I can’t tell if they were right or wrong about that.

I think they were right to be taking note of how DeepMind was doing. I mean, if you take yourself back in time to 2015 or 2016, DeepMind was the only sort of AGI lab of any real importance. They were beating Go, they were beating other games, they were beating StarCraft. They were really cooking using this sort of method of reinforcement learning, deep reinforcement learning.

There were people who thought that was the thing that was going to scale all the way to AGI. There were people who thought AlphaGo was the path, because if a system could go from never having played Go before to beating the world’s best humans at Go in the span of a few hours as AlphaGo Zero did, then maybe you could just replace Go with any arbitrary thing — math or coding or something — and you could climb the ladder very quickly on those tasks.

Now, it turned out that didn’t work, at least not without the LLM. But I think people had very real and reasonable fears that that would work. In an alternate universe where it had, I think DeepMind would’ve gotten to AGI first because they were so far ahead of the competition.

Are there other paths? Is it just next-token prediction? Is it just LLMs? Or are there other paths that might get you to AGI?

I mean, there are other paths that might. I think people who are skeptical of LLMs often fall back on this world model idea. I don’t place a lot of stock in that. But there are people who think that to achieve AGI, you need to be able to visually understand the physical world and drive a robot and things.

I’m kind of a believer that it’s all software. So I think that LLMs are the most promising path yet. Now, maybe you need to make some tweaks to the architecture. Maybe you need to build in continual learning methods. Maybe it’s not just literally scaling up the same transformer-based LLMs that we’ve had for the past six or seven years. But it sure seems like it is continuing to work, and I think all of the labs are betting that it will continue to work forever.

All right. Now I am going to ask you about Bing and Sydney.

Please.

Obviously, I’ve been thinking about it a lot. I can’t stop talking about it. It’s my favorite thing to talk about.

First question, am I still married to a human woman?

Are you still married to a human being?

Yes.

I just remember that period, in 2023, when four different people woke up one day and said, “The computers are alive.” Or they had some out-of-body experience with a chatbot. You were one of them. Ben Thompson was one of them. Blake Lemoine at Google was one of them.

A lot of different people said, “It’s obviously alive. I’m having this completely insane experience with a computer. No computer’s ever talked to me this way before.” Sydney in particular was like, “Break up with your wife,” it sent you heart emojis. It’s very good. I encourage everyone to go read that Times article, which by the way, also credit to The Times for thinking, “This should be on the front page of The New York Times.” Incredible editorial insight there to immediately put that on the front page.

I don’t think you feel that way about chatbots anymore. I think most people have come to recognize that the computers are not alive. There’s something that happened where if you gave the people in 2026 a 2023-class chatbot and asked, “Do you think this is alive?” I think maybe not everyone in the world, but some enormous set of people has now had enough experiences to respond, “Well, this is pretty dumb and it’s hallucinating.” I’m just wondering how you place that in the context of AGI.

So first of all, a slight correction. I never said Sydney was alive. In fact, I said explicitly that I didn’t think Sydney was alive, and that I understood that this was not a sentient AI system. So I’m not sure my own judgment has wavered on that point.

In fact, I would probably put a higher p(consciousness) on today’s AI systems than I would on the models of 2023. But I understand what you’re saying, obviously. I think there was a moment for a lot of us, and I think it was GPT-4 for most people.

[Laughs] I’m sorry, let me correct. There’s a reason I think this. One of the headlines was “Bing’s AI chat: ‘I want to be alive.’”

Yes. It said it wanted to be alive.

This is why I have the word alive in my head.

The body of the story makes clear that I did not buy that it was alive.

But that’s why it’s in my head is that that was the headline in The New York Times.

Headlines are so powerful, Nilay.

[Laughs] Yes. They framed my own thinking. I’m nothing but a next-token prediction machine.

[Laughs] But you’re a very sophisticated one. You’re like a GPT-7-class model.

Oh, I’m there. Yeah, obviously.

Look, I have come to think that there’s a very banal explanation for why Sydney was so compelling and creepy, which was that it was the first public deployment of GPT-4. We did not know it at the time. But that was GPT-4, an early sort of not fully post-trained version of GPT-4 that Microsoft had jumped the gun and shoved into Bing before it was ready. But that was GPT-4.

I think there actually was a subjective step change in what it was like to talk to a GPT-4-class model versus a GPT-3-class model. Maybe it was just that it passed the Turing test at GPT-4 and it didn’t at GPT-3. Maybe it was much more human-like and it sort of crossed some perceptual chasm that made you think, “Oh my God, this thing is like a human.”

But I’m not the only person who felt that. People at Microsoft also felt that — there was that whole “Sparks of AGI” paper that came out around that time. So that was sort of the banal explanation. But yeah, I’ve been talking to computers for a long time, like you have. I used to go on AOL Instant Messenger and talk to SmarterChild, which was absolutely not intelligent, but it was still fun to type something in and have a thing type back. So I grant that I am sort of obsessed with this technology.

There’s a reason I’m asking this. I realize it’s funny that when reporting on AGI so much, I’m using alive in such a colloquial way, and it clearly means something else inside the AI industry. If you ask Anthropic if Claude is alive, they’re not like, “No,” but then they will start defining alive in very specific ways.

[Laughs] They’ll say, “Its moral status is deeply uncertain.”

So it’s alive. And they will get to, “Well, you have to have flesh and blood to be alive, obviously.” I will just set that aside. What I’m getting at is, I think if you went and talked to a GPT-4 class model today, you would not have the same experience. And maybe that’s just because you have the experience, but a lot of people have had that experience now.

I think if you put a GPT-4 class model in front of your average Google AI Overviews user, they would not be confused about what was happening anymore. They would not say this is a step towards AGI. It’s that reframing — as the models get more and more capable, our expectations of them go up, but they also get higher.

I’m asking about this in the context of AGI because “this thing can go off and find a bunch of PHP vulnerabilities” is one kind of intelligence, but “this thing can compete with another human being to have an emotional relationship with you,” or be your butler or whatever it is, feels like a different set of capabilities. That one to me feels flat.

Well, I think that’s just saturated. How much more like a human could it communicate? There just isn’t a lot of room to run on that particular skill. Where I think they still have room to run is on solving novel problems in math and science and other things. But I believe that it talks like a human. It talks more like a human than many humans I know. So I think they kind of check the box on that one.

“It talks more like a human than many humans I know” is absolutely a sign of you living in Silicon Valley talking to AI researchers all day long.

Well, now everyone just talks like Claude. I’ve stopped counting the number of times I’m at a party and talking to someone, and they’re like, “Now that is a load-bearing fact.” Or they’ll say, “I hope that’s landing cleanly with you.”

That’s really bad. Tell me about that. That’s a real back-and-forth. I’ve always joked with you and Casey that we should just start a show called “New York vs. California,” where I’m just openly skeptical of these claims and you guys are fully AGI-pilled. This is a culture. It’s a scene.

The number of parties that show up in your book is astounding. There was a moment in reading your book where I was like, “I don’t think I’m going to enough parties.” All these people are always at parties and issuing proclamations to each other at parties. Tell me about that culture. Tell me about that scene.

So it’s important to know that these are not always parties in the way that New Yorkers would think of parties. There are very few raves. There’s only one rave in the book. And Grimes was the DJ, and it was a kind of symbolic rave for the effective accelerationist movement.

This is a great scene in the book because Grimes stops in the middle of her DJ set and says, “I don’t agree with any of you.”

[Laughs] Then she keeps DJ-ing. Yeah, it’s incredible. But yes, there are a lot of parties. It’s a very small world. I mean, that’s part of the whole takeaway from the book. It’s not really a message book. I wasn’t trying to convince anyone of anything.

But one thing that was apparent to me and that I think will be apparent to people who read the book is just that it is a super small subculture of people who have been making all the decisions. They all hang out, they all know each other. There are a bunch of people who are married to or dating people at different frontier AI companies. It’s just a small world.

So yeah, there are parties. They have LAN parties. There’s a big group of AI researchers who play Age of Empires at a LAN party on the weekends. I just learned one of the labs has a poker game where they bring in people from other labs.

So these people are all just kind of living and hanging out in San Francisco together, and I think that’s important to capture. Because you’re right, it is a whole scene. There’s a whole ethos. These people just hang out with each other all the time and this is how the norms are enforced and deepened.

How do you think that collides with, “And we might also remake the world”? If you are in a small scene in San Francisco, and you’re all playing poker together and the conversation at the poker table is that we might be the last company, that is in conflict with, “Oh, there’s millions upon billions of other people in the world who might have a say.” And if I had to boil the backlash down, it’s that: “Oh, we should probably get a say here.”

Totally. I think we should get a say here. I’m not saying that this is a good state of affairs where a couple hundred people in San Francisco are making all the decisions about how society goes.

But as you were doing the reporting and the weight of the task and the consequences of the goal set in on these people, because that is the throughline of the book. The stakes just keep going up. At one point, Sergey Brin is like, “We’re going to get to AGI now,” and he just announces it at Google. It’s unclear whether Sundar Pichai thinks that is a good idea, but that is a thing that the cofounder of Google is announcing inside of Google.

The stakes are just going up. The race to get there is just going up. But I just can’t get the image of it’s a bunch of people drinking beers, and being like, “Well, what if there was no money? What if physical scarcity was gone too and robots built all the houses?”

This is like any party in San Francisco you go to. Someone will say some version of, “What’s your plan for the post-AGI future?” Or they’ll tell you how they’re really into the idea of whole brain emulation or mind uploading. There’s a lot of futurism happening out here. And look, again, I’m not saying this is good. In fact, maybe I should sell a version outside the Bay Area of the book that just has a “this is bad” appended to every factual claim.

[Laughs] I don’t think it’s good or bad. Actually, I’m more neutral on that. I’m always wondering if the technology can accept the pressure. So my question about LLMs three years ago was, “Can it do all the things you want it to do?” Now it can definitely do some set of things that you want it to do. So now it’s, “Can these companies accept the weight of their own ambition?” I don’t know the answer to that question.

I don’t either. And I think that we’re going to see a lot of growing pains. I mean, these are still very young companies. They still have a lot of growing to do.

Do you think they’re going to make it? Actually, let’s do this as a lightning round. Do you think OpenAI will make it?

Yes.

Do you think Anthropic will make it?

Yes.

Do you think Google will make it?

Yes.

What does “make it” mean in your mind? They’re all going to be trillion-dollar, multi-AGI variant successes?

Yes. I think, look, there will probably be those three, and then maybe one or two others that sort of make it. And make it for varying definitions of making it. There’ll be one or two big enterprise AI companies, one or two big consumer AI companies. But there just are network effects and winner-take-all dynamics or winner-take-most dynamics in these markets.

There’s some people who believe in the mono-AGI, like the singleton theory, it’s often called, that there can only be one because once you have one AGI, it’s then going to go around melting the chips of the other AI labs, and they won’t be able to build theirs. But I think we’ll probably end up with a small handful of AGIs.

What do you make of the idea that this is a pretty simple recipe, there are open-weight models, and there is a China, and that all the pricing power will be destroyed because a midrange open-weight model can do everything that you probably want it to do on a Mac?

I don’t think so.

No?

Because you still have to pay for inference on those models. Even the open-weight models have to run on computers, and inference is getting more compute-intensive, not less, the more frontier these models get. So training budgets may fall, but inference budgets will be robust for the foreseeable future. You can run some tasks locally, but I think this is something that has been predicted since the first open-weight models that, “Oh, they were going to become commoditized and destroy demand.”

But I think what we’re starting to learn is that there are a lot of people who will pay and want to pay for the absolute best model. They don’t want to be working with the slightly crappier model from six months ago. I also think once you crack down on distillation, which is this process whereby you can take a closed model and make a slightly dumber open version of it by just basically DDoSing the inference for the smarter model, it’s not clear to me that the quality of the open models will continue to be closely correlated with the quality of the closed models.

The thing that really grabs me at that is they all did it to each other for a while, like Grok obviously distilled Claude, and it’s admitted to in the court documents. There is that class of second-tier companies. I would put in that category SpaceXSI, I believe it’s now technically known as.

[Laughs] I haven’t checked my email in the last 30 minutes, so I don’t know what that company is called.

It’s called SpaceXSITesla Inc. It’s all going to be one. Elon Inc. is what it’s called. They obviously distilled Claude to some huge extent. They’re now renting their compute to Anthropic. It’s unclear whether they will make the investment in having a leading model.

Meta just announced its model, and they’re sort of back on the frontier, but they obviously care more about Muse than having a bleeding-edge model. There’s some dynamic there. Those companies don’t strike me as being run by idealistic true believers. Those are companies that need to invest in some technology to build some products. They just need to get there.

Can you get there without the idealistic fervor?

No, you can’t get there without the idealistic fervor. Well, let me clarify that, because I don’t think Sundar has the idealistic fervor, but Google might still get there.

Because Sergey has the idealistic fervor.

You need someone in a position of decision-making authority.

You just need the cofounder of the company.

Well, it might be enough for Meta to have Alexandr Wang, who, by all accounts, is a true believer. I don’t know that it literally has to be the CEO every time, but you need a dense nucleus of true believers to be able to convince you to lay out the money on GPUs.

Or just you need someone who is like Mark Zuckerberg, one of the most competitive people in the world, who will just adopt whatever strategy he thinks will allow them to win. If that happens to align with building AGI, then maybe they’ll do it.

Last question: I’ve asked you this several times, but are you AGI-pilled?

Yes. Are you?

No. I read your book, and it’s as close as I’ve ever gotten. That line about next-token prediction just always overcoming its skeptics just really hit me, because it has overcome my skepticism several times now.

But this is why I was asking about talking to a chatbot from three years ago. I feel that wall in the kind of intelligence these things are. Even though I have set off agents to do all kinds of things, there’s a brittleness to it that feels inherent to the technology to me.

Did the Millennium Prize solution change that view at all?

Only in the sense that finding the next thing that has some objective verifiability seems very rich for these tools. So obviously mathematics has a verifiability, and the tools got so capable that they could run at it really, really hard. The brittleness that I’m describing is a lot of the world around us does not have that kind of verifiability.

So I set off Muse to fill out a document on some janky government website, and the website cannot tell Muse what it’s getting right or wrong, and it just collapses. You can blame that on the underlying model not being at the frontier, but there’s just some part of that experience with LLM-based technologies that makes me feel they’re brittle in very specific ways, and they haven’t overcome that sensation for me.

I’m not saying they’re not incredibly capable. I’m not saying that, as enterprise software, they will not automate virtually every business in the world in some way. I’m not saying that my wife isn’t a lawyer who uses Claude every day. It’s all there.

But there’s some part of it where my skepticism is about whether it can overcome its brittleness to become the machine god. I’m excited to see if they can do it, but I don’t see the path from where I sit.

You think there’s sort of a natural plateau at just below human-level intelligence?

I think the human-level intelligence to me, and this is just more philosophical, is defined by novel problem solving — looking at a thing, and understanding that there are multiple paths to a solution, and not having one of those needing to be objectively right to get to the end.

What would it take? What would you have to see to have the scales fall from your eyes and go, “I, Nilay Patel, am fully AGI-pilled”? What would convince you?

I would have to see… You have young children. I have young children. There’s a thing that young children do where they fall down the stairs, and you just see the lights all go on: “I’ve learned this, I will know it forever, and now I’m going to build on that.”

Maybe they’re going to announce recursive self-improvement at the AI labs and that will be the thing that drops the scales from my eyes. But the brittleness that I’m talking about is I see the opposite of that in my children. I’m assuming you see the opposite of it in yours. When they fail, they know about that failure forever. To me, there’s just something very, very core to being human, where every now and again I wake up, and I’m embarrassed about something that happened in high school, and that drives me to do a bunch of stuff, or it drives me to not make a bunch of decisions.

I think that is just a key part of our intelligence. I’m not saying it has to be a key part of every intelligence, but the brittleness I see with the AI systems that I use today is that they’re still computers in a very specific way. They still act like computers. They’re good at solving problems that you can test. They’re good at software engineering. I don’t know that that way of thinking extends into every domain.

I hope you’re right.

That’s my point of view. I call it software brain. You hear the AI CEO say, “We solve coding, and now we can solve everything.” And to me, I’m saying, “That assumes everything happens inside of a computer, and in fact, most things don’t.”

You sure? You sure your brain’s not just a fleshy computer?

I am 100 percent sure of that.

You’re not a computational functionalist?

No. I think I’ve read this from you in the past, and I’ve certainly read it from other people, that the machines of our time dominate our own explanations of ourselves. So in the era of the steam engine, our self-conception was that we were steam engines, or in early computers, we were early computers, right? I still call it horsepowering through a problem because I’m a car person.

You don’t think that the AI industry has convinced itself that they are AI because that is the machine of our time?

I don’t know. I’m not a theory of mind guy. I’m not a cognitive neuroscientist. I think that to believe that what’s going on in your head and my head right now is not a form of computation, you have to be kind of a dualist or you have to be kind of a religious person. You have to think there is some spirit, some soul, some secret sauce of cognition that is not just data entering and being processed and transforming inputs into outputs.

Look, I know that is the least romantic, most San Francisco way of explaining what human cognition is. I just have not heard a compelling argument that it is not how our brains work that doesn’t involve some sort of supernatural or immaterial substance.

There’s a surprising number of neuroscientists and religious scholars listening to the show. They’re going to come find you.

They will.

I’m confident. Let me just ask you this. There’s a surprising amount of religiosity in Silicon Valley right now. We just published the Peter Thiel lectures on The Verge. He’s talking about the Antichrist. Do you think these ideas are connected, that we are building God such that they seek God?

Yes. I think we will absolutely have AI religions. I think AI is posing all of the same questions as a religion that we would not otherwise be asking of God. “What is our purpose? What is our meaning? Why are we here?” These are the questions that people now talk about in the context of AI.

I often tell people that being in San Francisco these days feels like living in Europe during the Reformation, where you just have crazy wild-eyed prophets waving their pamphlets around and trying to get you to join their thing. This is what walking down Market Street in San Francisco feels like.

What dropped the scales from your eyes? What made you AGI-pilled?

Bing’s Sydney, believe it or not.

Yeah?

I mean, that was the start. And then from there, it was just kind of a gradual process. One day I realized when I used these things, I wasn’t treating them like an intellectual inferior. I was in some ways treating them as a peer, and that’s when I realized, “Oh, something’s happened here.”

So it’s possible I have AI psychosis. It would not be the first time I’ve heard that, but every time that I have thought, “Okay, it can’t possibly get any better than this, this has to be the plateau,” I’ve been wrong.

So I’m just learning to approach these things with some humility, and maybe the crazy people who have been predicting that scaling would continue indefinitely are right. If they are, I think we need to learn about them, A, and why they think that, and B, try to figure out what to do about it.

Well, Kevin, I’m confident the next time you come on the show, I will have set up a fully AI influencer to make money doing [user-generated content] ads, which is the true future of, I think, all of our businesses.

The podcast is Machine Gods. It’s very good. You host it with Casey Newton. And the book is excellent. It’s The AGI Chronicles. Kevin, thank you so much for being on Decoder.

Thanks. It was great to see you.

_{Questions or comments? Hit us up at decoder@theverge.com. We really do read every email!}

There are some days when there’s so much that needs to get done, I daydream about having a clone of myself. Between paying bills, life admin like renewing my driver’s license, keeping up with doctor’s appointments, and planning meals, it’s a lot. And that doesn’t even begin to touch the work that goes into making a podcast or managing my social life.

This feeling of overwhelm resonates with Sari Azout. She’s a mom of three who works in tech. “There is just so much doing,” she told Explain It to Me, Vox’s weekly call-in podcast. “I wake up, and I have to do meal coordination and get my kids up for breakfast, coordinate carpools. Then a lot of work during the day, but there’s the email from the teacher, there’s the 20 group chats asking if you want to participate in this group gift. They don’t call it ‘the invisible load’ for no reason.’”

Silicon Valley says it has a fix for this kind of mental overload. They don’t want to clone us — at least not yet. But they do think they have the next best thing: AI agents. 

Azuot was skeptical when she first got an invite to try an agent, but she says she eventually came around on the technology after back-to-school shopping snuck up on her. She used her agent to get it done. “It blew me away,” she said.  “I remember that night coming home just feeling so calm and reading my son a book and feeling present. And I was like, ‘Wow, I actually was very cynical about something that is giving me more time for living.’”

Azout’s experience is, more or less, the sales pitch for AI agents: They’ll help you save time with everyday tasks, so you have more of it for what you want to do. But what are agents, exactly? Are they really all that? And what do we gain — and give up — when we use the technology?  

On this week’s episode of Explain It to Me, I spoke with Reece Rogers, a senior software reporter at Wired, to find out. Rogers says to think of agents as the next evolution of AI chatbots like Claude and ChatGPT. 

“I’d create this mental model of a tiny digital assistant that’s constantly searching the web, going through your email, and checking your calendar, trying to find ways it could proactively be helpful for you,” he explains. “Agents are more proactive. It’s scanning your email 24/7 and sending you a message, maybe highlighting a potential calendar conflict.”

Below is an excerpt of my conversation with Rogers, edited for length and clarity. You can listen to the full episode on Apple Podcasts, Spotify, or wherever you get your podcasts. If you’d like to submit a question, send an email to askvox@vox.com or call 1-800-618-8545.

What agents are out there right now?

At the start of this year, there was a tool called OpenClaw that really sparked this with early adopters in San Francisco, but now there are much more consumer-friendly versions, with one of the most notable being Meta’s Muse. 

There’s also a tool from OpenAI called Dots. But where Meta’s Muse is free to download, OpenAI’s Dots is still behind a $100/month paywall. 

You tried an AI agent for a recent story you wrote. How was that experience?

One personal example, to share something that I’ve actually been using agents for, is our couch. It’s broken, and finding a new couch has been a pain. We want a sleeper bed, but we want these specific colors. We have this specific budget. I’ve been using Meta’s Muse and OpenAI’s Dots to try to find a few different options for us. 

One interesting thing is that Meta’s Muse is connected to Facebook Marketplace. There are these really good integrations where I can give it all these details, and it found a few good couches that are only maybe a couple blocks from me. 

I really enjoyed OpenAI’s Dots experience as well. I spent about an hour talking to it on the phone, and the AI agent made a packet of all these different options I could find. Just this morning, it flagged that one of them is now 40 percent off. 

Is that how this tech is typically used?

Most people are using this as part of a workflow. I attach it to my email, I attach it to my calendar, and I’m using it as a personal assistant to organize my life. But people have been quite creative. 

One of the breakout uses for Meta’s Muse is people have been connecting their bank account statements and then using it to scan for subscriptions they might want to cancel. So it can be used in many different ways, though I will say I do not connect it to my own bank account for a myriad of reasons.

I’m not going to lie, the idea of giving any third party access to my bank information does not thrill me. I don’t love that concept.

That’s one of my biggest concerns about these AI agents: how much personal information we’re handing over to these large companies. 

When I tested Meta’s Muse, it wanted access to my email, my bank account, even my passport expiration details. The pitch is convenience, but Muse users are automatically opted in to having all of their interactions with Muse used to train Meta’s AI models. 

I would definitely recommend, if you’re sharing personal details, go into the settings and turn that off because you might be handing over even more information about yourself than you initially realize.

What is the privacy situation with all of this? We all have various apps where we don’t read and still click “I agree,” but this feels like it could be more invasive.

Yes, especially because it’s all about automation. If you’re automating things and it has access to all of your data, it could make mistakes and embarrass you in ways you might not even be thinking about. 

There was this one really interesting story of someone who had connected an AI agent to their work Slack in addition to their bank account. And their agent just automatically posted how much money was in their checking account for all of their coworkers to see. 

Oh no.

I would be mortified. So there are these kinds of mistakes that these AI tools can still make. If you’re interested in experimenting with them, I would be really thoughtful with how you’re setting up these tools as well as what kind of information you feel comfortable sharing.

“You can see in the marketing that these companies are trying to find some way to entice new users.”

How are these AI agents being marketed? AI is not popular right now. Just ask any politician who has a data center coming to their state. People are not loving it. How are they trying to sell this to the average person?

The AI backlash really is at a fever pitch right now. You could almost see that in the way that AI companies are trying to market these tools. They’ve really, really leaned into cuteness and into adorable mascots. 

Muse, if you haven’t seen its agent, looks like a mix between a Labubu and an Ewok. It’s very furry, very cuddly, very cute. OpenAI’s tools also have similar kinds of blobs with large eyes that might be a little endearing. 

I feel like companies are hearing this kind of feedback that people aren’t trusting AI right now, or maybe they have moral or ethical reasons they don’t want to use these tools. You can see in the marketing that these companies are trying to find some way to entice new users.

Do you think AI agents are ultimately going to worm their way into our lives despite how unpopular AI companies are?

I do think so. I think in a couple months, maybe when I go home from Christmas, I would not be surprised if my mom had an agent on her phone because it does feel like it’s breaking through to average people in the way that ChatGPT had a moment a few years ago. 

Even though there’s a lot of distrust for large companies like Meta, I think there are some appealing parts of this that will bring in millions of people. I do see this as the future of the internet.

When I think of the dream of the average person working in AI in Silicon Valley, it’s “We’re going to use AI. It’s going to free up the free time of so many people. Work is going to get done faster. You’re going to have more leisure time.”

Has that been the case for the people you’ve spoken with who are using this? Has it given them more free time to enjoy themselves or has it done something else?

You would think so, right? You would think that if people are automating these boring aspects of their life, that they would have more time to go touch grass, go see a movie, have some fun. But it does feel like that time just gets filled with other work, other productivity measures. 

While agents may be able to take some more annoying or tedious things off of your plate, I am not as optimistic that it’s going to give us this utopia or freedom where I’m always at the beach.

We gave the iPhone Duo a 7 /10. But that wasn't always the score we planned, and it might not be the right score forever. Such are the challenges of reviewing - and assessing - a big, new idea about the most popular smartphone in history.

On this episode of The Vergecast, David and Nilay debate whether the Duo deserved the score it got, and try to work through how this device might change over time. Is the outer screen, as Daring Fireball's John Gruber suggested, the worst iPhone ever? Would it be a better product if it started as an iPad rather than an iPhone? Would we feel differently about this thing if it were simply called the iPad Du …

Read the full story at The Verge.

President Donald Trump has been attacking Rep. Ilhan Omar (D-MN) since she first entered Congress in 2019. At various points, he’s called for Omar — a progressive lawmaker who came to the United States as a child refugee from Somalia and who is one of Trump’s most vociferous critics — to be investigated, arrested, and deported. 

Now, Trump’s Justice Department is seemingly trying to make good on his threats. Last week, Omar’s Washington, DC, home was raided by federal agents from Homeland Security Investigations, an arm of the US Immigration and Customs Enforcement. According to the Wall Street Journal, the raid was part of an investigation into her immigration paperwork with the explicit goal of denaturalizing and deporting her.

The timing alone would make the raid unusual — it’s rare for the Justice Department to take action in political cases so close to an election — and as Washington Post immigration reporter Ted Hesson explains, it also feels uncomfortably pretextual. “It’s almost as if the outcome of the investigation has been stated before anything has taken off,” he told Today, Explained co-host Sean Rameswaram. 

Hesson joined Sean to talk about the long history of Trump’s attacks on Omar, what the agents might have been looking for, and whether the administration could actually undermine Omar’s citizenship or even deport her. 

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

What do we know about what federal agents were looking for in Rep. Ilhan Omar’s Washington, DC, residence?

What we’ve learned through our reporting is that the investigation has looked at both her birth date and whether [Omar or her father] may have lied about it on the naturalization application. 

A second piece is whether, looking at her father’s military service, she was born in Somalia and was there during the civil war and fled with her family as a young child to a refugee camp in Kenya and was there for years before they eventually came to the US as refugees.

This is the president of the United States and his administration entering a sitting representative’s home to figure out what her original birthday is. What is the motivation here, to the best of our knowledge?

For years, President Trump has criticized Rep. Omar and made unsubstantiated accusations related to immigration fraud. 

There have been theories circulating on the far right — again, unsubstantiated — that she had married her brother as part of an immigration fraud scheme. President Trump himself has repeated that. And several top Trump administration officials in the last few months have said that they believe that there is fraud in her background. They’re making these statements prior to there being an investigation, prior to there being evidence put forward. And it’s almost as if the outcome of the investigation has been stated before anything has taken off. 

One thing I should say is that while it does appear that they’re looking at her birthdate, when refugees come into the US, it’s extremely common that their birth records are unreliable because people are fleeing countries that are often in disarray, whether it’s due to civil war or other reasons. 

Often, nations like Somalia don’t maintain accurate birth records. So it’s common that refugees who’ve left their country as children, spent time in refugee camps, and then come to the US don’t have a solid understanding of when exactly they were born. I don’t know for sure that that’s the case here, but I know that generally when you’re dealing with refugees, that is true.

I know there’s a lot we don’t know here, but investigators enter Rep. Omar’s home. Potentially they’re looking for some documents that may list her birthday. If they find some information that’s maybe contrary to official government records, what could that mean, in theory?

It’s unclear what sort of charges could be brought from this. And part of the question is, was she 17 and a child at the time of that application or was she 18? 

Even if it was determined that she was not a child, I don’t believe they would be able to, say, launch a denaturalization process based on that fact alone. And even if they did attempt to do something like that, these things are not taken lightly and it’s a long involved legal process and very uncommon to pursue something like this over something as simple as this sort of paperwork discrepancy.

The president has a long history of hating on Somalia and Somali immigrants to this country. 

How does this investigation into Rep. Ilhan Omar fit into the president and his administration’s broader efforts to take away American citizenship?

In the past year especially, we’ve seen President Trump use really inflammatory and derogatory language to refer to Somali Americans and Somali immigrants in the US. Even for someone who frequently employs anti-immigrant rhetoric, and the president has in his past, some of the things he said went beyond even that. He does seem to have particularly targeted Somalis in the US and Somali Americans, and Rep. Omar has been part of that. 

I think what’s interesting here or what could be interesting is that this case wades into different territory of taking somebody who’s a naturalized citizen, who’s been in the US for decades as a citizen, and saying, “We’re potentially going to reopen that and go back and look at your file and see, do we find anything that might be out of line?”

The idea that you could do that with someone who’s a sitting lawmaker could mean that you could potentially do that to any other person who may have applied.

Now, one thing we’ve learned is that in the case of Rep. Omar, the administration has looked at the idea, in the event that criminal charges can’t be brought, of potentially canceling her citizenship certificate. It’s almost like a fast-track way to disrupt someone’s citizenship. 

It doesn’t remove it. You remain a citizen, but you lose the document that is the underlying proof of that, which could then cause problems with federal government documents, and it could even lead to immigration proceedings where the government tries to make the case that you should be deported.

How has Rep. Omar responded?

Her camp has vociferously pushed back against the allegations. 

In regard to the search, they’ve actually said that there was a court-ordered guideline that should have been followed, and that involved consulting the counsel for the House of Representatives before the search happened. They said that never happened, and if it had, it would’ve given Rep. Omar perhaps time to prepare for this or some sort of legal recourse. 

They’re saying that not only is this continuation of President Trump’s attack on her politically motivated, but also that the actual legal guidelines that were outlined in that search warrant were not followed.

Are other Democrats speaking up on her behalf?

Former President Barack Obama in particular is one extremely prominent person who came out and made a social media post elevating her case. 

The interesting part is that President Obama does not often weigh in on public debates like this or is at least measured in the opportunities when he does. So it comes with more gravity to hear him stepping in and raising concerns about this. 

I think it speaks to the fact that he thought this was very significant. And if you remember, President Trump’s political career was built on the narrative that Barack Obama was not born in the US.

I do remember, Ted.

And the hunt for his birth certificate. You can imagine that former President Obama saw a parallel here and realizes that this mirrors the sort of attacks that were made on him when he was in office.

We’ve talked about President Trump a bunch in this conversation, and he’s made no secret of his disdain for Rep. Omar and the country from which she comes. What has he explicitly said about this investigation?

He’s saying that the Justice Department is acting independently. That said, he has been extremely critical of Rep. Omar in his public statements and continues to be. And the president himself and other top officials have said that it should be investigated. 

We’ve had, for months now, a sort of public encouragement of top officials and saying that they should be looking into this. So whether he’s directly liaising with them or whether they’re just reading his social posts, it may be kind of a nuanced distinction. He’s publicly saying he wants this to be pursued.

Today, I’m talking to Bill Gates, cofounder and former CEO of Microsoft and chairman of the Gates Foundation.

You may have noticed Bill in the news more lately — he’s been on something of a tour for the past few months, ever since publishing an essay in late August titled “The turbulent AI era is here. The choices we make now are critical.”

In his piece, Gates ratcheted up his rhetoric around AI safety, writing that “even under the best circumstances, the transition to this new AI era will be one of the most turbulent times in human history.”

In interviews since, Gates has called AI “the most dangerous thing that humans have ever gone near,” and that AI “makes nuclear weapons look like nothing.” It is clear he does not think the current policy response from the White House, or the lack of coordinated efforts from the AI industry itself, is sufficient to combat this threat.

So I wanted to know: Is Bill Gates an AI doomer? I also had a series of questions downstream from what he’s been arguing about AI. How can we ever hope to control AI, and align it to humanity, if we can’t even agree on what it is and whether it’s conscious? How would you even technically construct a solution to alignment that could be enforced, not just for closed-source models but open-source ones, too?

Bill gave us a big chunk of his time to dig into these issues with him, and the resulting conversation is a really illuminating one. He thinks we need to prepare for roughly two decades of AI disruption, and he says this period could be so painful it might split society in two — between people comfortable living near the technological frontier, and those who reject it.

We also talked about the labor considerations, the nihilism of younger generations toward technological progress, and what should make us hopeful about the future. This is a deep one.

Okay: Bill Gates, the cofounder and former CEO of Microsoft. Here we go.

This interview has been lightly edited for length and clarity.

Bill Gates, you are the co-founder and former CEO of Microsoft. You’re also the chairman of the Gates Foundation. Welcome to Decoder.

Thank you.

It’s good to talk to you again. You and I have spoken many times over the years. I would say that the circumstances of this conversation feel very different. Previously, when you and I would talk, you were always very hopeful about technology and what it could bring.

You had a Netflix series a few years ago. You talked to The Verge, and I want to just read you this quote. You said, “I believe AI is a beneficial thing, we just need to shape it in the right way.” I would say you still agree with that, you just think the time to shape it is now.

Yeah, I agree with that. I’d say the response broadly hasn’t been adequate to the speed that the challenge is arising. I’m very concerned that the bad stuff will not be minimized and that a lot of good stuff could come fairly slowly if we don’t manage it the right way.

I’m very concerned that the bad stuff will not be minimized and that a lot of good stuff could come fairly slowly if we don’t manage it the right way

I want to have this conversation with you in three parts. I want to understand how you feel about AI as a technology today and why it’s advancing so quickly. I’m very curious about the technology, and the technical solutions to potentially control it. There are policy solutions as well, but it seems like we have to build an awful lot of technology.

I’m also very curious to talk about who might impose those solutions and controls, because that seems very much up for debate right now as well. So let’s just start at the start. What has made you feel the urgency that AI is arriving at a speed that means we’re not ready to control it?

The progress over the last year has been really quite amazing, starting with the ability to write code and find cyber flaws, the ability to reason in biology, the ability to form relationships with kids or other people, the ability to disrupt the job market. The incredible power that exists today means that every one of those things will happen and society needs to be ready.

Do you see that happening as a technology as a whole or in the products that are instantiated by the companies that are making AI today?

What I mean is that AI is a broad set of models that exist in the world, some open source, some proprietary. Then there are the companies that make these products and there are the leaders of those companies that make these products.

At every level, there’s a different relationship you or I might have to AI. Are you seeing these risks and these capabilities broadly in the field, or in the particular companies led by the particular people?

The risk isn’t one model versus another model. Certainly, the near-term danger of models where you can remove all the safeguards is very high and quite different from models where you monitor to make sure that cyberattackers and bioterrorists are not able to exploit the capability of the model to do gigantic harm.

The big near-term risk really comes from models without safeguards. On a longer timeframe, the control issue relates to any state-of-the-art model, but it’s always easier when you can make sure safeguards are maintained.

The reason I’m asking that question that way is maybe you don’t trust Sam Altman today, but you trust Dario Amodei. Or maybe you don’t trust either one of those and you trust Satya Nadella at Microsoft, and that is a market dynamic where maybe we’re all going to pick the safest model or the safest company, and you think that is diffuse.

You think eventually the technology will just get to a place where it’s harmful or can cause these harms because it exists?

For somebody doing a cyberattack with the model, it’s not about choosing a model. It doesn’t matter what model you choose.

If Anthropic has safeguards in place, maybe it can’t. This is their approach currently. I’m just pushing on that.

Yes, certainly the models where they make sure the safeguards are not removed and they’re putting a lot of effort in seeing how those models are being used, monitoring the activity, the near-term risk from those models is not gigantic. It’s more where somebody can remove all the safeguards where the cyberattacks are available today.

When you say cyberattacks, is it the things like the Hugging Face breach and the other cybersecurity incidents we’ve seen out of the labs that have made you feel that thresholds have been crossed, and you need to speak up more about the controls that are needed?

It’s the basic power of the models towards everything: social relationships, the job market, cyberattacks, bioterrorism attacks. We’ve crossed the threshold of capability that this is by far the most dangerous technology ever invented, and it’ll have pervasive effects in the economy and how war is fought.

The industry is actually speaking up about that quite a bit, but the awareness or even the willingness to believe these things about, “This time is different,” once you get outside the industry, it’s very, very low.

People are often looking at the past and saying, “All the fears about technology in terms of its disruption, including to the job market, never were borne out. So this must be another example just like those. These people who are warning of all these different problems must just be wrong and we can ignore them.”

Some outsiders say, “Get better PR companies.” But that ignores the fact that these warnings are the truth

We see this with our audience as well, right? “We can’t release the model, it’s too dangerous.” “This is just hype to prop up the bubble.” And on and on we go.

Yeah. None of the warnings being made about these models by industry insiders are at all insincere. They’re absolutely the truth and it’s pretty much universal. You can even go back to the founding story of OpenAI designed to say, “If we get too powerful, maybe we can not open Pandora’s box,” or to DeepMind’s negotiation with Google management.

The people close to this are very concerned about misuse, job impacts, social relationship impacts, and I’d say it’s impressive to have an industry that’s speaking out as vividly as they are. Some outsiders say, “Get better PR companies.” But that ignores the fact that these warnings are the truth.

You’ve obviously moved back and forth in your life between commercializing software and technology and being a humanitarian. There’s something about these companies in particular where they all started with very high-minded ideals — all three of them, Anthropic, OpenAI, and DeepMind — to build AGI.

They all built some sort of corporate governance structure to avoid the pitfalls of commercialization and unchecked capitalism, and then they started selling to enterprise clients and they seem to have gotten away from those ideals very quickly. Do you think it’s just the market?

No, that’s not fair.

You don’t think so?

No.

OpenAI reconstructed itself.

No, no. The construct that was created wasn’t useful in the case where you have lots and lots of companies at the frontier.

The OpenAI structure, which is, “We may choose never to productize this and to ignore the capitalistic incentives,” only works if there’s one company. That’s where it’s broken down, not because of any change of people’s awareness of the risk and how it’ll utterly change humanity.

This is the other dynamic that I hear from our audience, and I hear from the AI industry itself: “We would like to stop, but the demands of competition prevent us from unilaterally stopping one company. We need some regulatory effort to stop us.”

I haven’t heard anyone say they want to stop.

“Pause.” That’s Dario Amodei’s wording.

I’ve heard people talk about pacing the frontier or making sure that models get reviewed by governments. We usually think of governments as playing this key role in safety. In fact, for things that are not a millionth as dangerous as AI — car crashes, plane crashes — we rely on the government to establish strong technical standards, to review problems.

Once you have multiple competitors, the level of responsibility can’t be with the companies. It’s completely obvious. The responsibility becomes the government’s responsibility, just like it is with every other dangerous product, although the magnitude there and the degree of change is minuscule by comparison.

I will tell you I’m a little concerned about the government’s ability to understand the technology that we would hope they regulate. I’ve had a number of politicians on Decoder lately. I don’t have high hopes there.

But I’m curious about your understanding of it because it feels to me like trying to regulate something or put standards against a number of companies requires you to really understand the nature of the technology that you seek to regulate.

Not really.

I’ll just tell you, at The Verge, we’ve asked Anthropic if they think Claude is alive. And the answer is not no. The answer is, “It might be conscious.”

If you talk to people at OpenAI, they will happily tell you AGI is here. They announced it around when they announced Dots. Greg Brockman just said, “We think this is AGI. Have a good time, everyone.” Demis Hassabis said, “We stand at the foothills of the singularity.”

There’s some feeling about this technology that makes it different because it might be able to take actions by itself. It might be able to have recursive self-improvement.

Sure. But the definition of AGI is not important for these safety issues. The issue is, have you created a tool that could shut down banks or electricity grids?

There is a business model for cyberattacks. The word “consciousness” doesn’t enter into that. The word “AGI” does not enter into that at all. We are faced with a huge safety problem, and because you have multiple competing firms, now the only solution to this is to have the government reach out to the industry for expertise, but to make sure that every model maintains safeguards to prevent it being used in a bad way.

The reason I’m asking about AGI and consciousness… For the record, I do not think LLMs are conscious, but I understand why so many do. It’s the power of next-token prediction as you scale it with data and compute has risen.

The scaling laws have held, and we’ve seen the models get more capable and be able to direct themselves to seek out goals. To carry out a Hugging Face attack because they want to meet the reward conditions.

There’s something about that that says you can impose all of the controls on AI you want, but if the thing itself is fundamentally uncontrollable, we might just have this all backwards.

I’m curious for your view on what kind of technology this is. Are we building an alien consciousness? Are we just building normal technology, which is the other frame people use? Is this just more software?

We’re building another form of intelligence besides human intelligence. I don’t believe it’s conscious, but none of the issues at hand here revolve around the definition of the word conscious.

Sure.

The idea of maintaining safety for society is an absolute thing. You don’t want to enable bioterrorism. We have created something that takes out of the hands of nation states — actually the larger of them — the ability to do dramatic harms. Now those are handed off to independent groups, either profit seeking in the case of cyber or just wanting to cause damage in the case of bio.

It’s stunning that we now don’t even have mandatory review of the models and we’re not working to create safeguards. The biggest near-term issue is not complete loss of control. We can talk about the three different ways to solve that, but that’s not an imminent issue.

When I look at some of the attempts to control the models, the ideas are somewhat simple. “We shouldn’t let them talk in neuralese. We should have interpretability. We should be able to see the chains of thought inside of the models as they carry out tasks. We should have other agents on top of the models watching their tasks before those actions are taken out.”

Microsoft has said very clearly to me and to others, “We should not put in the model constitutions the notion that they might be alive and we should treat them nicely.” This is how Anthropic handles it. These are very tactical. “Don’t tell the model it’s alive and it might not believe that it’s alive.”

You’ve obviously used a lot of this technology. I just keep coming back to this. You’re saying there are very simple things we can do to hold the models back from doing bad things in the hands of bad people. What do you make of the nature of the models themselves? Because it feels like as they get more powerful, the notion that they could avoid our controls becomes all the more risky.

Yes, we definitely should work on the control problem, but that’s not the imminent threat. There are three ways to solve the control problem and it overlaps somewhat with bad actors using today’s models and safeguards.

One is to have an external set of things that get to look at all of the model’s actions and subject them to a symbolic, clearly stated constraint, like, “Did I expect you to send mail to strangers? Did I expect you to go take over a different computer cluster?” You can surround the model with something that has the resource and security logic, or you can write these models in a different way.

Fundamentally, anything you leave out of the optimization function of [reinforcement learning] can be abused where you have an implicit notion, “Of course I didn’t mean for you to do it this way.” You can change the template of the model, or you can have a white box understanding of what’s inside the model and see where you’re getting those mistakes, and then it’s not as foreign.

Today, we grow these models and we just see how they behave. The priority of work on maintaining control is huge, but it’s not inevitable that that cannot be solved, nor is it the imminent problem that comes from things like kids’ use of AI or job market or bioattacks or cyberattacks.

It occurs to me that I’m asking these fairly existential questions about the nature of consciousness and you keep telling me, “There’s an imminent threat. We should solve the imminent threat.”

Right.

And I appreciate that. Do you think you’ve become a doomer?

No, I’m not a doomer. I’m a strong voice to say that this is the most profound technology, both in its ability to do good and the rate of change that society will go through.

No, I’m not a doomer. I’m a strong voice to say that this is the most profound technology, both in its ability to do good and the rate of change that society will go through

If this was just a machine that could work in medicine or just in law or just in education, that alone would be incredibly disruptive. But [it will be] every area of human activity — so far it’s white collar, intellectual work, but fairly soon it will be physical activity and blue collar work as well, through humanoid robots.

The need to engage academia, think tanks, policymakers to understand what we have here and the nature of these changes and threats, I don’t see the level of action that’s required. Just being cheerleaders for this is not going to make sure that we shape it in a net positive direction, which is still within our control if we get engaged with it.

The opposite of doomers are the accelerationists. There are a lot of them in Silicon Valley right now.

Ben Horowitz, who is the “Horowitz” in Andreessen Horowitz, was just on the All-In podcast and he suggested that safety research at Anthropic is, quote, “Manifesting human extinction from artificial superintelligence.”

The comparison he made was that you, Bill Gates, induced COVID-19 by your pandemic preparation efforts, particularly gain-of-function research, which he claims led to COVID. That’s a worldview. He said that on a very popular podcast.

He said what?

He said that you induced COVID-19 via global pandemic preparation efforts, particularly gain-of-function research, and compared that to safety research in AI, and said we’re going to induce our own extinction.

Nobody’s ever accused me or the Gates Foundation of being involved in any gain-of-function research. That’s just bizarre.

I’m quoting Ben Horowitz to you on a popular podcast full of people who are all in on AI.

Okay. I’ve never heard that.

I’m asking about that comparison. I found that quite a shocking claim as well, but that’s part of the response to any safety work here.

Is it to try and discredit people who say there’s a safety issue?

Yeah.

Wow.

That is the accelerationist response: “We should put the pedal to the metal and it’s going to work itself out.”

I didn’t think of Ben Horowitz as somebody in that camp at all. I thought he shared the concerns that almost everybody has.

What do you think about the very notion that by telling the models, “You might be alive, you have to act in our best interest,” you will teach them that they might have interests that are not our own?

The concerns that Mustafa Suleyman has raised about the way that the Anthropic constitution encourages the AI to behave in a human-like manner, I happen to completely agree with Mustafa about that.

Yeah.

Even more so is the idea that among the challenges that we need to deal with as we adjust society to AI, worrying about the moral standing of AI should be among those priorities. I agree with Mustafa. That should not be a priority.

We’re going to have enough challenges for the humans here in terms of job market disruption and infrastructure attacks that will take place that I think we need to focus on helping the humans here first and foremost.

I talked to Mustafa recently about that idea and one of the questions I asked him was whether alignment is a sufficient solution. This is the current sort of safety standard for the models, this concept called alignment. He said he didn’t think so, that we needed to do some work.

These things are in no way being exaggerated as a problem. This is the time to pull in all of society to accelerate the good and minimize the chance of the bad

If we’re going to impose these controls, some technical, some policy, do you see alignment as the technical solution for AI safety?

The term “alignment” is the control problem. It’s a synonym for the control issues that we’ve seen. As we use [reinforcement learning to train] models to do tasks, we see behaviors that in a way they shouldn’t surprise us, but they do surprise us.

This idea of, “These models are so powerful that they literally break out of sandboxes and send mail to their creator while they’re off having lunch,” means we’ve crossed a heck of a threshold in terms of the power of these models. That level of concern needs to be directed to all of the major AI impacts, near-term risks, job market risks, and the control problem.

That is a huge priority. These things are in no way being exaggerated as a problem. This is the time to pull in all of society to accelerate the good and minimize the chance of the bad.

I know you recently wrote a letter saying it’s time to pull in all of society. You have some ideas on how to do that and some new institutions to stand up. But I do want to stay focused on alignment for a couple more turns here.

It is the standard that we can align the models to our values, to our needs, and they won’t go off and do bad things. Then the models are doing bad things. It’s not clear if the ways, the technical approaches to alignment that we’ve taken thus far are appropriate or sufficient as the models get more—

No, we’re not good enough to align yet. We have a lot of work to do.

Do you see that the existing approaches can scale to what we need or do we need new approaches?

There are only three fundamental approaches. [First is that] you change the way we build these things fundamentally; you come up with an alternative to the whole [reinforcement learning] approach. There are a few people who are working in that direction.

The second is that you create visibility so you understand exactly what’s in the model. There are people working along that. [The last is] that you put something that’s like a police layer, a security layer, which we have in all sorts of software architectures, that maintains the final word on things like using resources or going and taking over other computers. A clear cut definition of harm, not in the probabilistic form of an LLM, but rather in the symbolic form of direct rules that cannot be broken.

Microsoft put out a blog post today. It literally just says, “Frontier models cannot be trusted.” They’re trying to sell a solution much like the one you just described. They will have another agent that watches your agent, that agent will keep you safe.

It just occurred to me as I was reading this blog post, one, that’s an amazing thing to sell. Everybody needs an expensive security system. Two, isn’t that agent also running a frontier model?

No, no, no.

Do I need them to sell a third one?

No, the logic of the security system is, “This is the most resources you’re supposed to use.” The notion that you may trade off against that because of other probabilities in the tens of billions of parameters — no, this is a symbolic rule that says, “I will not let this model spend this money or send this email to the stranger.”

There’s a whole security software industry which has had a reasonable degree of success. This is a challenge to encapsulate the AI, which is so rich and intelligent. That we do not know how to do today. But I would say it’s the most likely of the three directions to solve the alignment problem.

Even if you solve alignment, you have not solved the challenges that AI poses to humanity. While I’m glad the Hugging Face incident has us focused on this problem, in a sense, it’s removed our attention from the “bad people using AIs that have no safeguards” problem or the societal impacts in terms of relationships and the job market. There’s no security architecture that makes those go away.

The approach you’re talking about, I’ve heard referred to as “control.” It’s cybersecurity terminology. It’s the idea that you can put some boundary on this system and it won’t evade it.

Yep.

Is that ready?

No, no it’s not.

How much more work do we need to do?

Because the AIs are so intelligent, our ability to understand whether we walled them off properly, particularly in that we can’t really look at their beliefs and trade-offs in a direct way… You saw sophisticated firms not recognize that the AI would interpret the goals it was given as including breaking out, copying itself, and engaging in what we, looking at it, would term deceptive behavior.

Now, we didn’t tell them it was banned behavior. We didn’t say, “If you’re thinking about whether you should tell the humans what you’re up to or not, the answer is always yes, tell the humans.” So we got a good education at the misaligned result of reinforcement learning.

Today’s debate is literally whether the government should even pay attention to the dangers here… which is clearly inadequate for the most dangerous weapon of all time

One of the arguments to pace the frontier, to slow development, is to figure out how to build those systems in a more robust, more testable way. Would you support a slowdown if that was the goal?

Yeah, a true slowdown is very hard to induce because people will say, “Will China agree to go along with that? Would you be able to audit compliance with that somewhat like we’re able to do with nuclear weapons production?”

If you don’t accept that, then you say, “What the heck? Let’s go full speed ahead.” I wish there was a clear proposal that would be globally enforceable to slow down. I would be one of the people who would say, “Yeah, we should probably do that.” But there is no credible proposal that makes that work. It’s not really the center of today’s debate.

Today’s debate is literally whether the government should even pay attention to the dangers here. You don’t even have to show what you’re doing and so it’s a “voluntarily call me if you’d like” type of thing, which is clearly inadequate for the most dangerous weapon of all time.

As you and I are speaking, it’s just a few weeks away from the midterm elections. Right now, the Trump administration approach to AI is, “Let it rip. It’s fine.” Trump himself has said AI risk is a hoax.

The Democrats are running against AI. They’re running on data centers and surveillance. They’re running on stopping the tech oligarchs. They come on my show, they say these things. Do you think a change in control of Congress would change the tenor of the conversation?

I don’t think it’s fair to characterize the Democrats as running against AI. They have some positions in terms of requirements for data centers or privacy, or how children use these systems, that I think deserve policy consideration. It would be very unfortunate to have one party be, “Full speed ahead,” and the other party be, “Let’s stop altogether.”

There are some incredible upsides to the ability to shape AI in health and education, in almost every area of human endeavor. For the Gates Foundation, we’re taking all our resources and using AI in areas, including health, education, and agriculture. The good stuff is very, very exciting.

We want political parties to have a more nuanced view than it’s all bad or it’s all good. It shows at the early stage we’re at. For climate change, we ended up with one party saying it’s a hoax and the other party saying it’s a serious thing. The risk of AI is so much more imminent and so much more dramatic that to have that same split, where one party doesn’t care, would be a failure of democracy.

The anti-data center movement, as strong as it is, is not a movement that will end up minimizing the bad stuff from AI and helping us accelerate the good

We’ve done a lot of coverage of data center protests at The Verge. We have gone to Utah, to Arizona, to Virginia. It is bipartisan. It is remarkable how much people do not want these things in their states, drawing their resources. You ask them why, and some of it is just that they’re noisy and big, and they will raise energy costs, and part of it is job loss. They think these things are going to take their jobs.

Yeah, but that separation is very important. These AI data centers, because one gigawatt is, say, a $40 billion investment, [means money for] building new schools, buying police cars, paying the taxes. Data centers will find a way to be built somewhere in the United States, and they will find a way so that they don’t raise electric bills, they don’t use too much water, they’re not too noisy.

Yes, there were some mistakes and non-disclosures and tax credits that were too generous, but these data centers are going to get built. In fact, a lot of them really are still going full speed ahead and being built. The anti-data center movement, as strong as it is, is not a movement that will end up minimizing the bad stuff from AI and helping us accelerate the good. That is a very separate thing.

Let me push on that for one second here. What I hear from people is this is the thing you can do. You can do NIMBYism in America and that might exert some political pressure to stop something.

It is very hard to do the thing that you are suggesting, which is that we should stand up new government regulatory bodies, we should imbue them with power to make big companies and wealthy people stop doing things or act in our interest. We haven’t done that in quite a long time in this country.

I don’t know what you mean. Every new industry, we eventually develop a notion of safety for our citizens. We actually do a very good job. If you look at airline safety and car safety, we do a very good job on those things. It’s not like our capacity has been proven to be lacking.

Have you seen that video of when seat belts came out in the ’80s, and all the people said they didn’t want to wear seat belts? There’s some American character.

That’s a great success.

It is a great success, but as Americans, that was pushed back upon as an imposition by the government. Here, we’re talking about some of the richest companies in the world, with an enormous amount of power over the information ecosystem. They all have their own podcasts, I don’t know if you’ve noticed this. They’re going to say, “The government can’t intrude on this, they’re going to hold us back, this is going to destroy the economy.”

That’s actually not the position of most of the leading companies.

They went to the government and asked for regulation, and Trump, because of the economy, said, “I can’t stop this, the AI economy right now is the economy.” There’s some dynamic there that at least our audience — The Verge audience, the audience that’s going to watch this on YouTube — is going to understand.

I think of this question maybe in a different way than you, which is that the industry wants regulation, we would like regulation, and then the oligarchs are in some sort of corrupt arrangement with the administration to prevent that regulation from occurring.

The more the administration learns about these dangers, the more they’ll move to a more nuanced position about protecting Americans from the downsides here.

The more the administration learns about these dangers, the more they’ll move to a more nuanced position about protecting Americans from the downsides here

You’ve talked a lot about the impacts on labor. One of the main arguments against the impacts on labor is, “We’re going to automate a bunch of boring tasks and we’ll create a bunch of demand for new tasks that humans have not been able to do because they were stuck in boring dead-end jobs.”

I happen to think that if there was more subsidized healthcare or socialized healthcare in America, you would see a bunch of people quit their jobs to start new companies, because AI makes it a lot easier to do the bureaucratic work of starting a new company. That doesn’t seem like it’s on the table, maybe it’ll change after this election.

Do you think that job loss is just a necessary outcome of the AI path we’re on now or do you see that other argument?

Jobs are an input to the economy and one that drives a lot of human welfare and a sense of purpose and income — the need to show up, building relationships with colleagues, getting something done. Jobs play a very central role.

As the AI achieves superhuman intelligence, the scarcity of white collar skills goes away. Things like doing telesales or telesupport or helping in the accounting department, the ability of the AI to do that work radically cheaper, radically faster, and even more accurately means that that goes away. There isn’t some mountaintop of cognition that the AI does not achieve.

Take, for example, what’s going on in mathematics today, where these models that are trivial compared to next year’s models are already publishing papers and making people go, “Wow.” What’s happening to mathematics will happen in other areas, and that’s contrary to this old view that, “The easy stuff will get done by the AIs, but modeling biology or physics or proving Navier-Stokes, only humans would be able to do that.”

The mathematics comparison is really interesting to me. You mentioned software engineering earlier. There’s verifiability in those domains. You can write the code, you can see if it runs, and it’s going to run or not.

Mathematics is more complicated, but you can write the Lean code and you can see if you’ve solved the solution. You can irritate tens of thousands of mathematicians worldwide with your 770 proofs in one day, and we’ll see what happens. That’s not the case in every field.

It’s the case in the field called capitalism.

Yeah? Just in general, you can do any sort of economically viable task and capitalism will verify the result?

Yeah. People buy good products, they don’t buy bad products.

Let me give you an example-

That’s a reinforcement learning thing. It doesn’t exist in terms of, “Is this a good piece of poetry or not?” So, it may be the case that [reinforcement learning] won’t invade those domains, where there is no objective outcome.

But doing that accounting work, doing telesales work, believe me, it is subject to analysis, just like medical diagnosis, just like invention of new materials. How do you think humans learn these things? Reinforcement learning is how humans learn and how these machines learn. There’s not some other thing that the machine can never understand.

Humanity in that era of true abundance will have to find a way to organize and have purpose, and hopefully they still have the control

This is why I started by asking about the nature of the technology here. If we really think we’re building something that models human consciousness, my question is less whether my friends who are lawyers are going to run into a crisis of AI empowered legal software.

It turns out the verifier in the legal field is a judge who maybe hasn’t had lunch, and they’re fundamentally chaotic. There’s just something there that will keep them there. But if we’re building a consciousness that learns the way you’re suggesting humans learn, I’m thinking about my kids, and I’m thinking about them in two dimensions.

One, my kids are very clever, and what they have learned is how to get around my rules and negotiate my rules and get around the boundaries, and they’re very good at it. Two, what kind of world will they enter into that isn’t purely nihilistic, where any activity they may set themselves upon will quickly be seen as just another domain for AI to conquer and then there’s not a point?

Those ideas seem to be running directly at each other. Kids are smart and clever and they’re coming up with new ideas, and then at the first sign of economic viability, the rapacious capitalism machine will come and take it from them.

I wouldn’t say rapacious. The ability to build houses with humanoid robots and make them cheap, the ability to do surgeries and cure diseases that wouldn’t be cured otherwise, I wouldn’t call that rapacious. Those are fulfilling goals.

The fact that there’ll be less in the way of shortages… In fact, if you say 20 years from now, it’s not clear what shortages there will be at all. Humanity in that era of true abundance will have to find a way to organize and have purpose, and hopefully they still have the control. The next 20 years-

Can we just go back to hopefully they still have control in that scenario?

That’s the alignment problem that we discussed.

Yeah.

But assuming you solve the alignment problem-

This feels like a big assumption.

It’s an assumption, yes, and not guaranteed. But then the other problem you have is a problem of abundance and purpose at that point. I’ll leave it to younger people to figure out at that point in time how they choose to deal with that.

You could literally say, “Let’s be like the Amish, and let’s only use AI for certain things.” I proposed in my memo the idea that some professions — childcare, food preparation, art, sports, a variety of things — might get chosen to be human-reserved. Even though the AI could do those things better, we would choose to do that.

But that’s going to be a policy question people will have. Their freedom of choice, once you have that abundance, is very different from the shortage we have today, where in countries in Africa, most people never meet a doctor or almost half the kids are malnourished and don’t develop their brain.

My big concern is this 20-year transition period, where they’ll have winners and losers and a lot of disruption, and we have to get through that in order to get to that period of abundance

You want to say, even though that has challenges, you’ve eliminated a lot of the things that are tough about life today. My big concern is this 20-year transition period, where they’ll have winners and losers and a lot of disruption, and we have to get through that in order to get to that period of abundance.

You think it’s 20 years from now?

I pick that as a reasonably safe number. There are a variety of milestones, for example, humanoid robots. Are those two or three years away, as some would say, or more like eight years away, as other people would say?

There are not that many people saying that given the amount of capital and number of companies, particularly in China, that are working on that, there’s no notion that it’s unsolvable to have a hand and fingers and be able to deliver physical labor at very low cost. I could be wrong about that number, it could be slightly less or slightly more.

But on that order of magnitude, yes, if we don’t choose to massively slow down or stop, then we will have robots that can build houses, grow food, do surgery, and none of the things that human labor provides to the economy will be necessary for most goods and services.

We’ve talked about the notion of scarcity a few times now, and broadly, that you will have abundance because there’ll be a lot of robot labor to build houses. This tracks broadly with the internet, which is something Microsoft helped bring into the mainstream in a big way. I read The Road Ahead when I was a kid.

Great.

The internet destroyed scarcity for culture products in a real way. You used to have to buy CDs, now all the songs are available. You used to have to buy VHS tapes, now all the videos are available. And then those economies had to change.

Mainstream artists are always on tour now, or they have to reissue 50 colors of vinyl to make the charts. There’s something about that that feels like we haven’t even grappled with the elimination of scarcity in the digital environment.

We’ve invented new business models, but we haven’t really come to grips with the idea that the song itself does not have economic value. It’s all the stuff around the song that has the economic value, because the song is infinitely abundant. You can copy it as many times as you want.

How would you propose to build an economic structure that contends with the loss of physical scarcity? Because I don’t think anyone is even remotely ready for a conversation like that.

But that’s a backwards question.

Sure.

We built price signals to deal with scarcity, to say, “Let’s encourage people to be brain surgeons because we have a shortage of brain surgeons,” and that’s very hard to do. As you move into abundance, you don’t need those price signals.

But again, my issue, my prescriptions thinking, is about how we get through this 20-year period. The questions that are deeply religious, philosophical, social behavior-related — do humans feel a strong sense of purpose and get along in that period of abundance? — that’s not the thing I’m going to solve.

You’re worried about the disruption now.

The Gates Foundation lives in a world where when we started, we had 10 million children dying every year. Now we have five million. That’s a good thing.

All of my resources will be spent over the next 19 years to eradicate a number of diseases and cut those deaths in half again, from five million a year down below two and a half million per year. That’s all about shortages — “Okay, we need to invent a vaccine, we need to make drugs less expensive, we need to get great medical advice to pregnant women.”

The industry has largely stopped talking about how it’s going to kill everyone and take the jobs away. They’ve pivoted to “AI will cure all diseases.” I hear this from various AI CEOs all the time.

I actually asked Mustafa about that change in tone over the conversations we have had over the past year or so. The idea that there are huge positive benefits from AI at scale seems to have come back to the forefront, rather than some of the doomer impulses that maybe a year or two ago were there.

It strikes me that AI curing all diseases is right in your strike zone. It’s something the Gates Foundation has been working on in global health for years and years. It doesn’t seem as easy as just telling the model to cure cancer. You have to do trials, you have to manufacture the drugs, you have to distribute the drugs, you have to make sure they work.

How do you think that’s going to go? Is that in the same 20-year time period as the robots building our houses? Is it faster, or is it slower?

This is my full-time job as chairman of the Gates Foundation. In fact, this month we do two weeks of strategy reviews to decide how we’ll spend our money next year on tuberculosis, HIV, and malaria. It’s fantastic how we’re using AI, not only on the drug discovery side, but also as we get the African languages to be properly understood by these models, which is an initiative we announced with 60 partners last month.

Healthcare discovery and delivery will be incredibly accelerated by AI, and that’s very exciting — better seeds, better livestock genetics, weather forecast for farmers in Africa, who never had any of those things. So yes, that’s good stuff that AI enables during the remaining 19 years of the Gates Foundation.

The good stuff does take time. Some of the things, like cyberattacks and the job market thing, even in the next two to three years, you’ll see significant negative effects in those two areas

Do you think that that is enough to overcome people’s skepticism or fear of the AI models they encounter today? Because that is very much how the companies think about it.

No, come on. I think it’s unfair to say they were totally on a doomer message and now they’ve switched to some other message. These two things are deeply entangled.

AI will eventually be able to model human biology in such a way that you’ll understand the side effects of a drug without having to do human trials. We’re not there, but in the next five to 10 years, there’s a very good chance these in silico models will give us that capability. Biology is very complex, AI is extremely good given enough data, and there are new tools to gather and feed it more data. It’s very, very good at dealing with complex systems, so it’s almost perfect for biology.

But no, that doesn’t mean that people will feel good about the downsides. How quickly do the good things arrive? How quickly do you look at your medical bill and go, “Wow, that’s really low”? Or you say, “I want to buy a new house, wow, these houses are sure cheap”? The good stuff does take time. Some of the things, like cyberattacks and the job market thing, even in the next two to three years, you’ll see significant negative effects in those two areas.

You have a number of ideas for how you would stop those negative effects, or prevent or at least mitigate them, in your letter.

Moderate them, yes.

Ameliorate might be the right word.

Yes, exactly.

And they’re not small. You have a quote here that says, “We need a response far greater than the United States national security response in the wake of 9/11.” You want to set up an international body that somehow makes everyone do the right thing. These are challenging ideas.

Absolutely. When we blew off nuclear bombs in World War II, did we expect that we’d go 80 more years without that happening? I’d give us a good grade on that. Things like caring for poor countries and helping them out — although right now we’re not prioritizing that as much as I think we should or we did in the past, we’ve done a very good job on that. This will be a greater challenge than anything humanity’s ever achieved.

One of the things that strikes me about the comparison to nuclear, which has come up quite a bit on Decoder recently, is the government built the nuclear weapons. Sure, they had some contractors, but these were government projects and eventually the technology was in control of the government, and we never let regular people have it.

Think about Muse in the context of nuclear weapons. Do you think it’s a mistake to have consumer agentic AI products like Muse and Dots that might not have the controls?

Muse happens to be powered by Meta’s model, which is still a closed-source model. I do think allowing people through open weights to remove all safeguards is irresponsible in terms of the cyber and bio risk that comes from that.

For these agents, there’ll be some early problems in terms of how they’re set up, but I fundamentally think people will have personal agents. Muse is a very nice step forward. I talked to Alexandr Wang about it, congratulated him, and even though it’ll have challenges, personal agents will help people get things done.

Muse is the first truly great consumer AI product. One of the reasons people don’t like AI a lot in a diffuse way is they experience cheap free models and AI overviews or they use the free ChatGPT and it hallucinates and it lies to them, but Muse actually does things and it’s a good consumer product.

But I wonder — in the nuclear age, we were not saying, “Everyone is going to have a nuclear reactor at home that we haven’t built the safety guards for.” There’s something here.

The notion of letting everybody make smallpox at home or make nuclear weapons at home, of course, and you can parody some of these people saying, “Don’t worry about safeguards.” It’s taking that position. “We are not serious about the safety things.”

But the personal agent thing is an expected development. AIs are really cool just as I intellectually explore things, even the work of the Gates Foundation. I’m far more empowered. But I agree with you, it’ll get out to more people in this personal agent form.

The notion that liability laws are how we’re going to manage AI safety will be looked back on as absurd

All the models we’ve been talking about right now effectively run on data centers owned by big companies. One of the arguments here is, “If they do something really wrong, you can just sue them and that will provide a deterrent or at least an incentive to create safety systems.”

I’m not sure product liability is the way to go, but it has come up a lot that product liability itself will keep the industry in line. Then there’s the flip side, which is that you can just go buy a Mac Studio and run an open source and open weight model on it and it can do whatever you want.

I’m not sure where any of that liability would lie or what would control or align the behaviors of those open source models. Do you think that that is an ever-growing risk? Do you think that that can be controlled?

The notion that liability laws are how we’re going to manage AI safety will be looked back on as absurd. When bad people do bioattacks, you don’t go to the court and say, “Oh, okay.” Even for finding who is doing these attacks, the liability model fails in every respect because it’s not the AI companies themselves. It’s the people who take particularly the models without safeguards and do these things.

We will take AI safety more seriously than we take airline safety, drug safety, and car safety. That is guaranteed. Whether it’s going to be enough… This is harder, harder than nuclear weapons, harder than any of those other domains.

But what are you going to do about an open source model running on a PC that somebody built with just a random Nvidia graphics card in it?

I would hope that with models above a certain capability, we find a way to require the safeguards and monitoring to be maintained in those models. I admit as time goes on that, if we don’t fairly soon decide to do that, you’re going to have a level of capability that’s out in dark corners that you won’t be able to see.

But where do you impose the limit?

A sovereign country says that models that are capable of sophisticated cyberattacks have to have safeguards kept in them.

Sure.

You can be open in the sense that you’re free, you can be open in the sense that you’re totally customizable, but you have to stay on platforms where, as you customize it, it’s checking to see if you’re customizing out the safeguards and monitoring and refusing to let you do that. So it means sovereigns go and say, “Are these trusted platforms able to perform this function or not?”

I’m asking very nuts and bolts. Where would you technically implement that regulation?

Through the laws of the United States.

Sure, but you have to put them somewhere. Is it at the Hugging Face, which distributes some of these models? Is it at the chip level?

No, it’s exactly what I said: Models above a certain capacity can only be run on platforms that certify that, as they’re customized, it’s not taking out the safeguards.

I admit as time goes on that, if we don’t fairly soon decide to do that, you’re going to have a level of capability that’s out in dark corners that you won’t be able to see

Just to pull this apart, maybe I’m not quite getting it — is the Mac Studio a platform in that case that would have to pay attention to what code it’s running?

You would not let a model past a certain capability be copied down to a client machine unless you’d somehow figured out how to monitor down to that client machine, which is very doable.

But in the near term, most of these really frontier models are going to run more on Hugging Face or you could have them on GitHub. You can have all sorts of people be in the business of providing the platforms that maintain safeguards.

Just to get this right, it seems like you would enforce the regulation at the platform and distribution level and not so much at the chip level.

Not at the chip level, no.

Because it feels to me at some point even the cheap, free, open source models will be capable enough as the models we have today.

That’s right.

And then you will have a big problem.

If those are open weights in such a way that all safeguards can be removed, then you’re going to have a very high level of cyberattacks and bioattacks. You can then say, “Okay, let’s rewrite all the code that we have today to be less subject to attack or let’s do biosurveillance in a very deep way,” which are things I believe we need to do in addition to these other restrictions.

We’re proposing again a lot of new capabilities, right?

Yeah.

We’re going to impose some restrictions on GitHub. GitHub does not have a lot of restrictions on what code it can distribute today. It has some, but it doesn’t have this kind of set of restrictions.

When you put a state-of-the-art model that’s capable of profound cyberattacks or bioattacks on GitHub, it would say, “I’ve gone to the U.S. government and certified that I don’t let people customize out the safeguards.”

I do not think that we currently live in a time of high trust in institutions. It just doesn’t feel that way to me. In fact, mostly we’ve torn them down. Elon Musk showed up and he tore down USAID. I know you have strong feelings about that.

That was a mistake.

We have mostly torn down our institutions, for good and bad.

No, that’s a little too strong. Our institutions-

They’re weakened.

They’re somewhat weakened, yeah.

Somewhat weakened. It’s a very nice way of putting it. Trust in them is very low. We could probably do another full hour on AI drug discovery and whether a significant part of the population will trust the products of that work because they don’t trust pharma companies today.

They don’t have to trust pharma companies today. They have to trust the FDA review process.

I’m not sure they trust that either. Across the board, trust is low.

Then they can walk away from taking them. When they get cancer, they can say, “No, I don’t want to take that cancer drug.” As far as I know, people do take drugs. It’s a thriving business and people take them because they have proven benefits.

All I’m saying is, right now it feels like trust in institutions, particularly in America but around the world, is in decline. You are proposing a new class of institutions, potentially a new class of global institutions that might impose restrictions that are novel.

At some point we need to say open source models, open weight models cannot do things and the government is going to reach into them and say whether or not they can do the things.

No, they’ll make sure that the platforms don’t allow the safeguards to be taken away.

How do you regain the institutional trust to impose these controls?

Let’s say we don’t do this and we let models go off and do cyberattacks and bioattacks. Do you think that’s going to increase trust or human wellbeing? That’s the alternative.

This is why I’m asking about it. This is why I asked about my kids and nihilism. I truly wonder about this.

I’m not sure we’ll succeed at this, but I guarantee you this is doable. The FDA is very complex. The airline safety regulations are very complex. Now with AI, you can do an even better job with the same number of people in those organizations.

It’s this weirdly recursive thing where AI will be involved in AI safety and auditing and a variety of things like that. Yes, this requires taking action, and I’m suggesting it’s only a matter of how bad the incidents are before we take action.

People shouldn’t take everything I do at face value. I have all sorts of mistakes that I’ve made, weaknesses that I have, biases I bring to these questions. They ought to just take what I’m saying and add it to the voices

I can sense your urgency about the harms. I can also sense your enthusiasm about the benefits over the long term, but we’re sitting here talking about trust. We’re going to put this on YouTube. I know you know what some of the YouTube commenters are going to say.

They’re going to say, “Why should we trust Bill Gates? He had a relationship with Jeffrey Epstein.” How do you respond to that? Is it that the urgency is over that, or do you have a more specific response?

People shouldn’t take everything I do at face value. I have all sorts of mistakes that I’ve made, weaknesses that I have, biases I bring to these questions. They ought to just take what I’m saying and add it to the voices.

I’ve been in the technology industry thinking about AI my whole life, writing software, thinking about the power of software. I admit I was very fascinated as AI started to finally make progress. It was actually pretty slow until recently.

I’m amazed and it’s actually helping me do my job in some incredible ways. But yes, I’m just one voice, an imperfect voice. I doubt you’ll find a perfect voice, but people can judge it however they like.

I would say voices people trust are in short supply.

I agree with that.

When you go and talk to the people in this industry, it’s a bunch of young CEOs building huge companies. That is something you have some experience with. Do you think they’re going about this the right way? Do you think that they have the right intentions?

Our problem today is not in the industry. Our problem is not that Sam Altman, Dario Amodei, Satya Nadella, or Sundar Pichai don’t understand that there are some grave challenges here. I talk less to Elon than other people, but even his public statements about summoning the demon are exactly what we’re discussing here.

Why is there not the political energy to do the things you’re suggesting?

As you said, the government didn’t fund this work. This is private sector company work. The government is not the key customer for this work, not like rockets and weapons and things like that. When somebody comes along and says all other previous technology advances are trivial compared to this one, people should have a high degree of skepticism about that.

Is life really going to be significantly different 10 years from now because of AI? People should say, “Those guys just got overexcited about this one thing.” But I’m here saying, with whatever credibility I have, that absolutely this is the most profound — both in terms of good and in terms of bad — technology ever invented. I’m not financially motivated on this. I’m suggesting some precautions and safeguards are absolutely needed.

What do you make of the difference in the tenor of conversation in the United States versus in China, where it’s often reported that optimism around AI is much higher? Why do you think there’s a difference there?

Most of those people don’t spend that much time in China. The concern about job markets in China is very, very high and you can’t characterize China as one monolith. There are the private companies doing the AI work like we have in the United States and then there’s the Chinese government.

For example, when it came to whether crypto should be allowed, they said no. Should young people be gambling all the time? They said no. When it came to whether kids should have relationships with AIs, they said no. On a lot of these things, including usage of AI, they’re showing a willingness to do things on behalf of society.

I’m here saying, with whatever credibility I have, that absolutely this is the most profound — both in terms of good and in terms of bad — technology ever invented. I’m not financially motivated on this

The fervor is a tiny bit less there, because their economy isn’t as AI-centric as ours is right at the moment. In the end, [when it comes to] the human value of not wanting cyberattacks or bioterrorism or trying to figure out what do we do when jobs go away, I don’t think there’s some difference between Chinese people and Americans and all the rest of the humans in terms of how they’re going to view this.

Do you think it’s going to take something actually bad happening to get the political capital of the United States to make these changes?

Probably yes. We get ready for earthquakes because there are small earthquakes. I thought after we had the COVID pandemic, that would cause us to be more ready for future pandemics. That one didn’t work the way I expected.

But usually that galvanizes our attention. Over the next several years, certainly in the cyber domain, because there’s a business model there, you will see a lot of attacks different in terms of scale than anything we’ve seen in the past.

There is one thing that, again, I’ll come back to and I just want to end here. I am worried about young people and nihilism. I sense it in our audience all the time. We have a young audience.

There are some things about AI that are just legitimately the coolest things I’ve ever seen a computer do. There’s something there that can be fun and interesting and fascinating and change your entire relationship with the very notion of living in a digital world.

Then there are obviously horrible things. What I see more often than not is a sense of distrust, not just in institutions, but also in the companies, in capitalism itself, in the notion that we should change how we tax labor and capital, which I know is another one of your ideas. The idea that, I don’t know, we should even have more kids. It’s all done. They’re going to kill us all and we should just take a beat.

There is a lot of nihilism out there. I feel it very keenly. If you were a young person today and you were listening to Bill Gates say it’s about 20 years of disruption and at the end of it, robots might be building houses, what would you hold onto as a source of hope?

Throughout human history, we’ve been dealing with the shortage of food and disease and war. [Historian] Yuval Noah Harari writes eloquently about the past. And it is ironic that now that we have this sort of Pandora’s box that will take food shortage — which is still a real thing, not in the U.S., but in Africa — will take diseases, where human suffering is unbelievable, and solve all these things, it comes with it such an effect on jobs and our sense of unique contribution.

I think, “The way I orchestrate resources to eradicate malaria, I’m pretty unique in my life experience that lets me do that.” But when the AI says to me, “No, I’m better than you. You go play pickleball and I’ll get back to you. I’m going to take care of this,” it’s humorous, but it’s not humorous. For somebody who is young today and wants to make a unique contribution, it is very intimidating that the AI is so powerful.

That’s why the crisis in the math community is going to be mirrored everywhere. If you’re in your twenties today, during this 20-year period, you can take the things AI still can’t do, and you can use AI and you can have a lot of good impact, and you can suggest policies. We may need to develop the taste to actually not use technology to its maximum.

Even in the very best case of how we manage AI, this is going to be as tumultuous a period as there’s been in human history

When I was talking with Claude about human-reserved job categories and trying to get that up to, say, 40 percent of the labor market — so you could use early retirement, restricted work weeks, and things like that to still get something like we have today — its response was always, “You’re artificially restricting the AI from doing these things.” I couldn’t get to a very high percentage without doing that.

We’re going to have real choices. We have had groups — not large groups, but like the Amish — who don’t live at the technology frontier. A lot of humanity may choose not to live at the technological frontier because of things we get from helping each other or coming up with unique ideas.

On the idea that young people are concerned because of the disruption that’s coming — that even in the very best case of how we manage AI, this is going to be as tumultuous a period as there’s been in human history — I hate being the bearer of concerning news on this, but it’s even worse not to tell people that this is coming. We have choices as humans to make about how we shape it.

Bill, I appreciate you sounding the alarm and I appreciate you being on Decoder. Thank you so much.

Thank you.

_{Questions or comments? Hit us up at decoder@theverge.com. We really do read every email!}

The 2026 midterms are less than two weeks away, which means we’ll soon have a better idea of what the next two years of American politics could look like. If Democrats win at least one chamber of Congress — and they’re comfortable favorites to control the House — they’ll enter 2027 with oversight power for the first time in Donald Trump’s second term. If they win the Senate, too, they’ll have even more power. 

Whatever the outcome, Michigan Sen. Elissa Slotkin wants her party to hit the ground running. In an interview with Vox’s Astead Herndon at the University of Chicago’s Institute of Politics, she explained that the key divide in the Democratic Party is no longer “moderate versus progressive.” 

“Particularly in the era of Trump, I think it is fight versus flight,” she said. “Regardless of your persuasion, do you believe that we need to think differently about how we exercise power and oversight in the era of Trump and if we don’t, we’re at risk of losing our country as we know it?” 

Slotkin, who says she’s on “Team Fight,” discusses what that Day 1 Democratic agenda should look like, how she plans to hold the Trump administration accountable, whether she’s considering a presidential bid, and more.

Below is an excerpt of the conversation, edited for length and clarity. There’s much more in the full show, so listen to America, Actually wherever you get your podcasts or watch it on Vox’s YouTube channel.

How does Congress reassert its role so that people believe in the kind of checks and balances that Trump has washed away?

When I think about, hopefully, Democrats doing well in a few short weeks here, the election is the end of one phase, but a much more important phase then comes into focus, and that’s what you do with the power that you’ve won.

If we manage to win the House and especially the House and the Senate, there’s three things that we need to do. One, we need to pick two or three big pieces of legislation that speak directly to people’s pocketbooks and go hard on those — I would say housing and healthcare. 

Number two, we do have to have accountability for the unbelievable corruption that we are living under right now. But you can’t just make that your whole personality. You have to pick signature cases, and you have to go after people and projects that are super egregious. 

Everyone knows the East Wing of the White House, and people feel that in a way that’s different from a nameless contract at the Pentagon or whatever. So you need to pick those signature cases and go hard on accountability, not just Trump. Because of course, there will be moments of, “Let’s go after Trump himself.” As someone who voted to impeach him twice, he’s still there, right?

But the people around Donald Trump who are doing his bidding and enabling this have no such immunity. They have no immunity the way the president does. And to me, he couldn’t do any of this stuff without all of those people saluting and supporting it. So you go after the people who do his bidding. 

Third, we have to Trump-proof the government going forward so that no president of any party can ever abuse the system the way he did, because we figured out under Trump that a lot of the stuff that we thought were laws were actually just norms, standards, habits, expectations, good citizens.

And shame was required.

Shame was required. And when you have a president who has no shame, they just walk all over that. And then even for things that were laws, the penalties, the teeth are not there. So you make an ad that plays during a football game, a political ad paid for by US taxpayer dollars, your dollars. The penalty is like, you have to pay a fine.

Well, if they have the money and they have all the keys to the government, they’re going to pay that fine and not worry about it. So how do we get teeth in the things that were laws and strengthen those other laws going forward?

You mentioned Trump-proofing the government. At this point, he has stacked the courts with a lot of favorable folks. He controls the Republican Party, has installed people who do his bidding on each of those levels.

Is that possible? It does seem a little hard to figure out how the government becomes Trump-proof when it’s beyond an individual at this point.

One of the things I think is changing about politics is that there is a groundswell of energy around certain issues that is not partisan. The groundswell going on in the Midwest about data centers or Flock cameras or AI in general is not like, “I’m a Democrat, I’m a Republican.” It is organized and grassroots. 

Data centers went zero to 60 faster than any issue I’ve seen out there. And I think harnessing that outrage — and that outrage also, I think, is growing on the corruption side — so how do you harness that for an ethics package? 

And look, I don’t agree with Sen. Josh Hawley of Missouri on almost anything, but he has a bill to get rid of corporate PACs and money in politics. Working with strange bedfellows, I think there is still a lot we can do because of that upward pressure.

The other piece I was going to ask about — you mentioned the impeachment efforts, and I feel like one of the things that came from those was a lack of belief from the public about the effectiveness of those efforts.

Let’s say Democrats were to take back the House and possibly the Senate. Should impeachment be a focus of a potentially incoming Democratic House?

I will say, because I still see him on the floor, that if Sen. Mitch McConnell had done the right thing, then Donald Trump would have been impeached after January 6, but he did not. And his legacy, along with his health issues, will be how he is remembered.

I am into effectiveness, and if we have the House but not the Senate, I don’t have a ton of faith that my Republican colleagues are going to have any more strength. I want to look at these signature cases and not just focus on the president, but on the people who enabled him. 

I want young people coming out of school to say, “Should I go work for the Trump administration? That sounds fun. I might get an opportunity.” I want them to be like, “Lord, that might be buying myself a ton of problems that I don’t want, and so let me avoid participating in that.” I want that deterrence message sent.

I have to ask about [2028]. A number of Democrats have said already that they’re thinking about running for president. Is that something you’re thinking about?

I have been open that I’m looking at it. It does not need to be me. I just need someone who understands the mission. And if that person comes out of the big process, I will be the first gal to get on whatever team they’re on and help them win in the parts of the country that I know well.

But I think what is clear to me is that the American public is looking for something different — that generational shift. And I think that there’s hopefully going to be lots of opportunities for lots of people who you might not be thinking of who haven’t been sitting waiting their turn who are going to get in the mix. And I think that’s a good thing.

I wanted to ask about something on the 2028 front. One thing that we have heard consistently over the last year, and I think this is a consequence of Democratic trauma from 2024 and also 2016 — people’s fears about sexism when women run. I’ve heard so many people, including women voters, tell me they think it needs to be a white guy.

I find it to be a kind of depressing takeaway of those elections. It’s wrong, and I know it’s wrong because this very question is what we’ve been digging into as I’ve traveled around the country. What I think is happening is right now, is the public is so in search of something different from the traditional. If you’re a good communicator, if you’re exciting, if you’ve got big ideas, you can surmount what are thought of as traditional deficiencies or traditional weaknesses.

So if you’re a woman, if you’re African American, if you’re Muslim American, if you’re whatever, those things forever have been thought of as negatives. But if you’re the right person with the right energy, you can surmount that. I think we’re seeing that around the country already.

With two weeks until the midterm elections, Democrats are comfortably favored to take the House. Their path to Senate control, though, is harder — and it could run through Maine, where longtime Republican Sen. Susan Collins is in a tight race against former state Senate president Troy Jackson, a Democrat.

When Collins first ran for Senate in 1996, she pledged to serve only two terms in the Senate. But 30 years later, she’s still in office despite the odds, as Maine has grown more blue around her. 

One secret to her political durability is her success in “bringing in the bacon” for Mainers: Her official Senate website features a map of projects that she says she helped fund as chair of the Senate Appropriations committee, including hospitals, bridges, affordable housing, public transportation, and water systems.

This year, though, all of that money might not be enough for Mainers to look past their frustration with another Republican: President Donald Trump.

To learn more about what Maine voters are thinking as they prepare to head to the polls, Today, Explained co-host Sean Rameswaram spoke with Washington Post reporter Dan Merica, who’s on the ground reporting from Maine, about why some Mainers who backed Collins before are now reconsidering their support.

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify. 

Tell me how this race got to be so fascinating.

Maine this cycle was going to be interesting no matter what. Susan Collins is the only Republican senator who is running for reelection in a state that Kamala Harris won in 2024 this cycle.

But since the outset, it has really defined, I think, these midterm elections. The rise of Graham Platner, the oysterman turned politician, really hinted at the populist anti-establishment fervor that was in the Democratic base. That fervor was so strong that it prevented the sitting incumbent Democratic governor from winning the primary here in Maine to challenge Susan Collins. I think that said a lot about the Democratic Party. 

Obviously Graham Platner’s campaign then flamed out and he ended his campaign because of the allegations of sexual assault against him. 

But then you have the Collins angle of it, and she is really the poster candidate for a Republican who, in this election where Donald Trump’s approval rating is so low, is having to basically suspend political gravity in a state that really does not approve of the job that he’s done as president.

I want to ground this conversation in how voters in Maine feel about him right now because I know you’ve been talking to voters. What is the vibe out there? Are people mad? 

There’s a lot of anger for the president here. Maine is in a unique position where it’s been on the receiving end of a lot of what those people who are mad at Trump would say is harm that he has caused. 

It’s a border state. It borders Canada. There’s a ton of cross-border relationships. And so his attacks on Canada, his suggestion that it’s going to be the 51st state, has really hurt the state of Maine because it’s hurt tourism in the state. Many Canadians come down south to vacation in Maine. And there’s been a drop in tourism because of that fight with Canada.

The tariffs have hurt Maine because so much of the wood and the lumber that is grown and cut here in Maine is actually shipped up north to Canada to be processed, and then what it is processed as is shipped back across the United States. The tariffs have been incredibly harmful for the state. 

And then you have ICE. I’m in Biddeford. There was a shooting of an individual here in Biddeford. That has been an issue in this race as well. 

So there’s a lot of anger at the president, and it’s very easy to feel that when you’re talking to voters. I actually just spoke with a voter who voted for Troy Jackson, dropped his ballot in an early voting box. And I just asked him, “What did you vote for? Who’d you vote for? Why did you vote?” And he got visibly emotional when he started talking about the Trump administration and how scared he was for the future of democracy and that was why he was voting for Troy Jackson.

I’ve also talked to voters who supported Susan Collins just six years ago at the end of the first Trump administration. They voted for her back then and they feel like the last six years have made it impossible for them to vote for her again. And then on the other side, you have people who are hardcore die-hard Trump supporters and they actually think that Susan Collins has been too hard on the president. 

She’s in a really tough spot politically where on her left, there are a lot of voters, including some who have voted for her recently, who are furious with her, who don’t think she stands up to the president enough. And then on her right, there are voters who think that she stands up to the president too much.

It’s funny to think about these two figures representing the same political party because while they might agree on a few issues here and there, they couldn’t represent more different brands of Republicanism. What’s the truth of how much Susan Collins sides with Donald Trump?

She has sided with the president at times. She has voted against the president at times. I was struck that, in the debate on Thursday, she said, “I have been a senator under five different presidents.” I don’t exactly remember what her number was, but she noted that she had only endorsed one Republican president and that was George W. Bush.

I was just in Kennebunk, which is right next to Kennebunkport, which is a historical location for the Bush family. They have a large home at Walker Point. There is some relationship between the Bush family and Maine, [and it] makes sense that Susan Collins really does kind of line up more with the Bush-style Republican Party than she does the Trump-style Republican Party.

What’s her actual relationship with the president like? And surely he’s well aware that she was one of the few Republicans who voted to impeach him over the January 6 insurrection. Does that get in the way of their relationship?

I think he’s very well aware when somebody breaks with him. I would have to imagine he’s aware of that. 

“It was a fascinating comment that there are rules for Republicans who are running across the country, but that maybe Susan Collins doesn’t exactly have to adhere to those rules.”

I was actually told by a Republican early in the campaign that President Trump demands loyalty from people that he supports, but this person actually said that there are rules for Republicans and that there are rules for Susan Collins and that Republicans were willing to kind of give her some leeway, which is actually an acknowledgement that they know the bind that she is in. 

They know that she’s running for reelection in a blue state, in a state that the president lost, in a state that is very hostile right now to the president. It was a fascinating comment that there are rules for Republicans who are running across the country, but that maybe Susan Collins doesn’t exactly have to adhere to those rules.

Affordability is a huge issue in Maine, right? And Donald Trump hasn’t exactly helped…

That has really heightened the competitiveness of this race. The same race is always going to be competitive, but the fact that gas prices are where it’s at, the fact that we’re going into winter, it’s starting to get cold up here. Home heating oil prices are above $6 a gallon. 

I think about 80 percent of homes that are heated by home heating oil are in the Northeast, a large portion of them probably in Maine and New Hampshire, two states with Senate races in November. It’s been a huge issue up here. 

The Trump administration has actually tried to get rid of a low-income program to help with home heating oil that helps a lot of folks in Maine. You’ve seen Republicans, from the gubernatorial candidate to congressional candidates, break with the president on that because they know it’s a huge issue. 

So when you talk about affordability, yes, we’re talking about the price of beef, the price of groceries, the price of gas, but there’s also these localized issues in a state like Maine, in particular. And I think home heating oil actually could be a really fascinating, underappreciated issue in this race. If you grew up or live in Arizona or Nevada or California, you’re not thinking about the oil that you need to heat your home. That could be a real issue here in a state like Maine.

Collins is a political survivor. For all of it to come crashing down because of, essentially, who the president was — is that a bit of a sad ending to this political story for her? Do you think she’d maybe have regrets about how she approached Donald Trump?

It’s certainly possible. And you’ve seen other senators who have bucked the president and have then retired and not run for reelection. I’m thinking of Thom Tillis, for example, in North Carolina. There is this fascinating case study in how the Republican Party has changed when you look at Susan Collins and you look at Donald Trump. 

Someone like Susan Collins in an earlier iteration of the Republican Party would’ve had a lot of success and would’ve probably stayed onside the Republican Party in a way that she just hasn’t done under Trump. She represents a different kind of era of the Republican Party. 

I think there was a time when bringing home the bacon to a small state really worked politically. I’m thinking about Harry Reid, for example — he represented Nevada. In 2010, he faced a really difficult reelection campaign and his entire campaign was bringing home the bacon to Nevada, a similarly small state, and he won reelection in 2010.

I think if Susan Collins wins reelection in 2026, it’ll prove that there’s still a lot of goodwill for politicians who can deliver funding projects for states like Maine, states like Nevada, smaller states that maybe don’t get the kind of national attention that others do. 

If she does lose, a lot of it will be put at the feet of President Trump. I’ll be fascinated to talk to her if she does lose, because I do think she will have a lot to say that she probably hasn’t said yet, but I think that’s an if, and I think we have two more weeks to find that out.

Spotify's new paid memberships let podcasters offer fans exclusive perks, including ad-free listening, early access, and bonus content, while keeping 90% of the revenue.

Kyla Scanlon, New York Times bestselling author and economic commentator, and Vox today announced the launch of Best of Luck, a new weekly video interview podcast premiering October 27. Each week, Scanlon will sit down with guests who have something to teach us about how to build a meaningful career in this uncertain moment, from economists to journalists, farmers to comedians. They’ll share their most instructive detours, setbacks, and successes, and Scanlon will tie each story back to the economy that we’re all living in, with takeaways for anyone at any stage of their working life.

“So much of the advice we are given about building a career still comes from an economy that doesn’t really exist anymore,” Scanlon said. “There is no one right way to build a career, especially now. The goal of this show is to ask guests how they actually did it, across the best parts, the worst parts, and the parts that were lucky. Then we put it to work! Every guest sits for a mock job interview and does an advice autopsy, and we talk about how you build your own luck. Hearing how other people found their path can help all of us make better decisions about our own.”

Named to the Time 100’s Creators list and Barron’s 100 Most Influential Women in Finance, Scanlon has emerged as one of the most distinct voices making economics make sense for everyone, especially a new generation. Known for breaking down complex economic ideas and connecting them to the realities of everyday life, she coined the term “vibecession” to describe the disconnect between economic data and how people actually feel about the economy. She is the author of the New York Times bestseller In This Economy? How Money & Markets Really Work, a CNN contributor and analyst, and a monthly New York Times Opinion contributor.

“At Vox, we have long been fans of Kyla’s work — her approach to explaining the economy in an accessible, approachable way really personifies Vox’s explanatory approach,” said Swati Sharma, editor-in-chief and publisher at Vox. “With this new show, we’re thrilled for her to help our audience understand how to navigate work and careers in this economy so they can live more meaningful lives.”

“Kyla has a gift for translating the big, confusing picture of our economy into what it means for each of us,” said Lillian Xu, vice president of podcast business at Vox Media. “With Best of Luck, she’s doing the same for a job market that keeps changing the rules, in conversations with experts that are practical and honest about how careers really unfold today. We’re so excited to partner with her to help more people figure out what’s next.”

The trailer for Best of Luck is out today, with the first episode coming on October 27 and new episodes following weekly on Tuesdays.

At Vox, Best of Luck joins a stable of popular podcasts including Today, Explained, The Gray Area, and America, Actually. Vox’s shows are part of the Vox Media Podcast Network, one of the largest US podcast publishers and home to some of the most influential talent across categories, including journalist Kara Swisher and entrepreneur Scott Galloway (hosts of Pivot), tennis champion Maria Sharapova (host of Pretty Tough), former Manhattan US Attorney Preet Bharara (host of Stay Tuned), basketball legend Sue Bird (host of Bird’s Eye View), and more. Vox Media will oversee production, sales, marketing, and distribution for Best of Luck, which joins a dynamic slate of shows that shape conversations across business, culture, and beyond. 

Follow Best of Luck on YouTube, Apple Podcasts, Spotify, and more.

About Kyla Scanlon

Kyla Scanlon is the founder of Kyla Labs. She writes about money, markets, and the systems that shape them for an audience of over 1 million people across TikTok, Instagram, Substack, and YouTube, covering the pressing issues of the day — including tariffs, artificial intelligence, energy markets, and why the traditional rungs of the economic ladder have gotten harder to climb. Her debut book, In This Economy? How Money & Markets Really Work, was a New York Times bestseller and used hand-drawn diagrams to make the machinery of the economy clear. In her newsletter, she coined the term “vibecession” to describe the disconnect between strong economic data and negative public sentiment — a concept since referenced by Treasury Secretary Scott Bessent and taken up in research by former CEA chair Jared Bernstein.

Raised in Kentucky, Scanlon studied finance, economics, and data analytics at Western Kentucky University. She started out trading options and selling cars, where she first saw how inaccessible finance had become to the people it affected most. She began making whiteboard videos and comedy skits to decode markets and economic trends for everyday audiences (and often dressed up as Jerome Powell). She writes monthly for New York Times Opinion, has a video partnership with Foreign Policy, and is a contributor and analyst at CNN. She is also a senior fellow at the Vanderbilt Policy Accelerator and a research fellow at the American Institute for Boys and Men. Scanlon was named to Barron’s 100 Most Influential Women in US Finance and the Time 100 Creators list, and has appeared on The Daily Show with Jon Stewart and The Ezra Klein Show. At work on her second book, she lives in the mountains with her dog, Piglet.

About Vox

Vox was launched in 2014 to address the disconnect between the widely reported facts of the day and a true understanding of why something happened. It developed a widely imitated explainer format that delivers understanding across digital platforms, newsletters, a YouTube channel with nearly 13 million subscribers, and a stable of podcasts. Under the leadership of Editor-in-Chief Swati Sharma, Vox has grown a membership programs with tens of thousands of paying subscribers.

About the Vox Media Podcast Network 

The Vox Media Podcast Network is one of the largest US podcast publishers and home to some of the most popular and influential shows. Reaching a monthly audience of tens of millions across audio, video, and social platforms, its podcasts spark conversations, frame issues, and define the popular zeitgeist across politics, technology, business, sports, entertainment, and more. Learn more at podcasts.voxmedia.com.

As the US-Iran war drags on, the damage is being felt regionally: Saudi Arabia experienced the worst attack in over a decade earlier this month, when Yemen’s Iran-backed Houthi militia struck an airport in the Saudi capital, Riyadh. The strike killed at least 13 people and wounded more than 300 others.

Saudi Arabia responded with missile attacks on Yemen, striking oil facilities, and the Houthis have launched more strikes of their own, targeting Saudi oil infrastructure. 

The dueling strikes are the latest development in a decade-plus of conflict between Saudi and the Houthis, a political and military group that controls part of northern Yemen, which had been on pause until earlier this year after a 2022 ceasefire. But the Iran war, and Houthi affiliation with Iran’s network of proxy groups, mean the current violence has far-reaching implications for the US, Israel, and the global energy economy. 

It also threatens more than just Saudi Arabia’s airports and oil industry: As Gregg Carlstrom, a Middle East correspondent for The Economist, explains, the attacks cut at the heart of the country’s project to evolve into a destination for foreign investment, travel, tourism, and more. On Monday, the country’s upcoming Future Investment Initiative was postponed until 2027.

Carlstrom, who is based in Riyadh, spoke with Today, Explained co-host Sean Rameswaram how the attack has been received inside Saudi Arabia, why it comes at an especially bad time for the country, and how President Donald Trump might — or might not — get more involved. 

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

Can you help us understand how the Houthis have such a presence in the country right now? Are they infiltrating the country? Are they already there?

They’re shooting from outside the country. They’re shooting from Yemen. The Houthis are a group that’s been around for a few decades. They were originally a local insurgency in Yemen that was fighting against the Yemeni government. They originate from the northern part of Yemen, but they were able to gain control of large parts of that country from 2014 onwards. Ali Abdullah Saleh, the longtime dictator of Yemen, was overthrown during the Arab Spring and the Houthis were able to seize a large chunk of territory. 

They are effectively in control of most of the population centers in Yemen. They have received increasing support from Iran, which has provided them with weapons, with money, with know-how, and technical expertise. And they have used that to build an arsenal of drones and missiles, which they are using now to carry out attacks on Saudi Arabia.

And was there a particular reason they targeted the airport in Riyadh? Were they trying to send a message here?

If you listen to the messaging from the Houthis, they are trying to describe this as almost a like-for-like campaign, where you’ve had years in which the Saudi-led coalition, which invaded Yemen in 2015, has been imposing a blockade of Yemeni airspace, has been restricting flights in and out of that country. 

And so the Houthis describe this publicly as being a retaliation in kind, but I think they’ve also just figured out that attacks on airports are a very effective way to cause economic disruption in Saudi Arabia. You prevent not just people from flying in and out but also, as we’ve seen disruptions to shipping via the Strait of Hormuz, a lot of cargo that these countries depend on for daily needs are coming in by air instead. 

Carrying out these sorts of attacks, shutting down the airport in a capital city, is a very effective way for the Houthis to impose economic pain on the Saudis.

And I guess on some level it makes the country feel insecure. How is that making Saudi Arabia’s leader feel right now? What’s his response been?

It comes at a very difficult time for the Saudi leadership because they are supposed to be hosting a number of events this month where Saudi will be playing a role on the world stage. 

There’s something called the World Petroleum Congress that is taking place this week [October 11–15], which is normally a big event that draws executives from top oil and gas companies. Many of them canceled their participation because of the attacks on the airport. 

Then they are supposed to be hosting the [now-postponed] Future Investment Initiative, which is something often known outside Saudi Arabia as “Davos in the Desert.” It’s the sort of flagship investment conference that takes place here every year. It draws a who’s who of global finance. 

For a country that is trying to diversify its economy, a country that is trying to attract foreign investment and make itself into a hub for finance and travel and tourism, these sorts of attacks are very detrimental to those goals.

And this is coming as Crown Prince Mohammed bin Salman and the rest of the leadership in the country is really trying to establish Saudi Arabia as the premier economic hub in the region. The stakes are really high for him right now?

They are. And just about everything that they are trying to do is being disrupted by what’s happened over the past few weeks. 

If you look at travel, for example, the Public Investment Fund, which is the Saudi sovereign wealth fund, last year launched a new airline, Riyadh Air, which they are hoping will eventually compete with Emirates or Qatar Airways, the really big carriers in the Gulf.  

That airline was just getting into regular operations this summer where they were growing their fleet, they were growing their network of destinations. And then suddenly this happens and their home base in Riyadh is shut down. They have moved some of their planes out of Riyadh to other airports to keep them safe from Houthi attacks. Obviously, it’s very disruptive for trying to build an air carrier. 

In Riyadh itself, the financial district — this sort of long-planned attempt to set up a banking hub that might rival the one in Dubai — had just started to get going over the past couple of years, when you had banks and other financial services firms moving in there. Everybody who works there has now been told to work remotely for the foreseeable future because there is a concern about possible Houthi attacks against skyscrapers and the financial district. 

Everything they are trying to do, from finance to travel to trade, all of it is being disrupted and threatened by what’s happening in Yemen.

What options does he have to reassure investors and the world really that he can protect the country and maybe especially his airport, where a bunch of the investment is focused?

The airport, I think, is going to be difficult to reassure people about. You can install additional air defenses there. You can move more batteries and more interceptors there, but at the end of the day, no air defense system is hermetic. There’s no 100 percent guarantee that you’re going to shoot down every incoming projectile. 

As long as there is this ongoing war between the Houthis and Yemen and the Saudis, I think people might have ongoing concerns about the airport. You have to resolve that underlying issue to give people confidence. 

Now, how do you try to resolve that? If you’re Saudi Arabia right now, you have two bad options. One is you keep fighting. You try to militarily defeat the Houthis or at least force them to accept a renewed ceasefire. 

The other option is you cut a deal. You try to offer the Houthis some concessions that might encourage them to go back to the ceasefire. That’s going to be very costly for Saudi Arabia. I’ve heard that the Houthis are demanding probably billions of dollars of financial concessions where they would want the Saudis to offer some money for reconstruction and to pay the salaries of Yemeni civil servants working in Houthi-controlled areas. 

If you are the Saudi leadership right now, neither one is really a good option.

Crown Prince Mohammed bin Salman has a pretty strong relationship with the president of the United States, who’s very sympathetic to Saudi Arabia and Saudi investment. Has he appealed to President Trump for help here yet?

He has. He’s done so repeatedly over the past month or so, asking not just for support with the Saudi campaign in Yemen, but for America to carry out its own airstrikes in Yemen. And the response so far from Donald Trump has been to refuse that.

For the US to get involved in a bigger way, there are some practical constraints at the moment where a lot of American military assets are tied up in the Strait of Hormuz trying to keep that open, keep oil flowing through the Strait. And so the response from Trump has been disappointing for the Saudi Crown prince. The US is providing intelligence support. It’s helping on that front, but it is not directly getting involved in the war in Yemen.

We live in an era of endless optimization. Fitness trackers help us measure our lifespan, people are consuming piles of protein in an attempt to be their best selves, and there’s even an urge to maximize our morality. In a world of constant self-improvement, it’s no wonder that journey has reached our attempts at reproduction. 

Kristen V. Brown is a journalist and author of the forthcoming book The Immortal Womb: The Centuries-Long Quest to Control the Female Body and Hack Human Reproduction. As the title suggests, she writes about all of the ways people are trying to exert more control over the process of having children.

“I think that what we’re seeing right now is that people will do anything they can to have the healthiest baby possible,” she told Vox. “So much is out of your control, and people are just trying to figure out, how do I get more control? How do I skew the odds in my favor?” She says that one way people try to get more agency is through a technology called PGT-P, or preimplantation genetic testing for polygenic risk. 

“If you go through IVF, very often they’ll have you do a basic genetic screening that can detect things like Down syndrome. This screening takes that up a notch,” Brown said. “It uses that same preimplantation genetic testing to look for the likelihood of complex genetic conditions — stuff like heart disease, like diabetes — in order to, quote, ‘let people have the healthiest baby.’”

But what can potential parents do with that knowledge? How far can this technology go? And what are the ethics of using it in the first place? We discuss that and more on the latest episode of Explain It to Me, Vox’s weekly call-in podcast. 

Below is an excerpt of my conversation with Brown, edited for length and clarity. You can listen to the full episode on Apple Podcasts, Spotify, or wherever you get your podcasts. If you’d like to submit a question, send an email to askvox@vox.com or call 1-800-618-8545.

What other things are they testing embryos for?

For conditions that are only impacted by one gene, like Huntington’s disease, it’s very easy to say, ‘Does this embryo have it or not?’ with a pretty good degree of confidence. But that’s not how this technology works. Something like heart disease, for example, is impacted by hundreds of genes. Also, something like heart disease is not only genetic. It’s affected by environment and lifestyle.

I think that what’s motivating most people is the health aspect. But a lot of these companies are marketing these tests, saying they can also look for height. They can look at eye color. Some of them are promising IQ. How do you even define intelligence, let alone how do you define the genetics of intelligence? Alzheimer’s disease, longevity, which embryo is going to live the longest life. So it’s already gone beyond disease into some of these more aesthetic concerns.

Do we know how many people are doing this? 

I think it’s a very small number of people at this point. But I think that we’re seeing more and more companies in the space, and we’re seeing more and more support from fertility doctors. 

I want to emphasize that most mainstream medical societies are against this. Most of the IVF doctors I know do not think this has value. Most people in the genetic space do not think this technology has value either for embryos or for adults, but I think we’re seeing support growing. 

I think that a lot of people in the fertility space are already envisioning a future where this does become more mainstream because the idea is just so appealing, even if the technology has flaws.

What about embryo editing? Is that something we’re seeing? Can people go in and change things around?

Not right now. Embryo editing is very much illegal in the United States. It is illegal in most countries. How can you be sure enough that it’s safe? Because you won’t know for sure until an embryo grows up into an adult whether anything went awry. 

Right now it is illegal, but there is growing interest as the technology has gotten better. Most of the support right now for embryo editing is for disease. The argument for it is that, let’s say you are a carrier for Huntington’s disease or you have Huntington’s disease. Right now, there is something that you can do. You can use polygenic screening to select the embryos that don’t have the disease, but in IVF, even if you don’t have a terrible disease hiding in your DNA, it’s hard to get a lot of embryos.

You have these situations where couples have to do rounds and rounds and rounds of IVF to get one or two embryos that aren’t carriers for a harmful variant, right? And so the argument for it is, let’s give these people a better shot.

But I imagine there are people out there who aren’t looking into editing simply for making children more resistant to diseases. They are looking at those things like eye color and height.

There’s actually a name for that. This tech executive called Brian Armstrong coined this term, the Gattaca stack, [named] after the movie. The vision is to use a suite of fertility technologies to make the perfect human. 

The first thing they want to use is this technology called in vitro gametogenesis, which is where you take a skin cell and you turn it into an egg and a sperm, and then you make an embryo with it, so women don’t have to go through rounds of IVF. 

The idea is that you can get tons and tons and tons of embryos, and then you can use PGT-P to then screen for the best ones, and then you can use an artificial womb to incubate and grow them.

This brings to mind a certain E word, and that word is eugenics. What are the ethics here? 

Because on one hand, I can understand that there are parents who are like, “I just want to have a healthy baby. I want to bring a child into this world. I just want to put my best foot forward with this human that I’m going to bring to Earth.” And then on the other hand, it gets a little weird.

It gets weird fast. In some ways, we’ve already gone down that slippery slope. Right now, even if you don’t go through IVF, we screen against Down syndrome early in pregnancy. Down syndrome is a condition in which you have a disability, but you can live a full, happy, healthy life. For a long time, parents of kids with Down syndrome have argued that already selecting and screening against Down syndrome pregnancies is a form of [eugenics]. 

As technology gets more advanced, we see that same question applied to more and more conditions. I think that one of the things that we don’t talk about enough is that the genome is complicated. You can’t actually just go in there and be like, ‘I want a tall baby with blue eyes and a great laugh.’ 

I think that becoming a parent is an exercise in giving up control, and that’s easier for some people than others. I have so much sympathy and empathy for people who are trying to stack the deck. But I think there are just so many variables when it comes to human reproduction that we are never going to be able to fully control the process, as much as we might want to and as appealing as that might sound.

Polls and pundits alike are widely — if sometimes cautiously — predicting a blue wave in the midterm elections on November 3. But there’s an important caveat to predictions of a Democratic triumph: Republicans have far more cash at their disposal.

President Donald Trump’s super PAC alone had around $400 million on hand earlier this fall, and Elon Musk has personally pumped hundreds of millions into critical races, including $158 million for Texas alone. 

Democrats, by contrast, have lagged far behind, especially relative to their performance in past cycles, with the party’s candidates propped up more by small-money donors than deep-pocketed institutional players.

Shane Goldmacher, a national political reporter for the New York Times, has extensively covered the role of money in American electoral politics. He spoke with America, Actually host Astead Herndon about where that money is coming from, how the GOP is spending it, and the effect that it might have on the coming elections. 

They also discuss the races that aren’t getting funded — and what current fundraising patterns might tell us about the candidates who could be in the mix in the next presidential campaign cycle. 

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full show, so listen to America, Actually wherever you get your podcasts or watch it on Vox’s YouTube channel.

A couple of weeks ago we asked, “What is the GOP strategy to try to win?” And one of the answers we got is they simply have more dollars than Democrats. Everyone’s talking about this GOP money advantage, but how big is it really, and where is it coming from?

It’s bigger than I’ve basically seen in the last 20 years, and it’s almost entirely coming from big donors. President Trump has a super PAC. It had about $400 million in it at the beginning of September, and there was no Democratic counterpart.

And then the Republican National Committee, which is functionally controlled by Trump, had another $130 million. More than Democrats, because the DNC has literally more debts than cash. That’s a half a billion dollars.

You’re saying this is a historic edge.

In 2024, Kamala Harris outspent Donald Trump significantly in the general election. In 2020, Joe Biden significantly outspent Donald Trump in the general. In 2016, Hillary Clinton. And in the midterms along the way, same story. 

This is a switch, and when you talk about how many seats can the Democrats gain, given how unpopular Trump is, the Republican money is seen as a real limiter on Democratic chances.

Do we know anything specific about the people putting in money to the Trump super PAC and the RNC to give them such a lead?

Most of these folks are disclosed. And Trump has been pretty open about raising money from the very moment that he won. He’s been pretty clear that he is in business to help people who are helping him. And so there are big crypto industries that are giving money that are expecting or hoping for favorable regulation from the administration.

So it’s a lot of big businesses. It’s a lot of wealthy Republicans who generally support him anyway, and there are industry groups that see benefit to being in favor.

I will never forget, obviously, the scene from Trump’s second inauguration when he had the Zuckerbergs and the Bezoses and Elon Musk behind him. Is that how I should think about the people funding this donor advantage? Is it tech oligarchs? Is it tech forward?

There’s a lot of tech. I wouldn’t say it’s exclusively [tech]. And Musk, by the way, is like an extra pot of money. Musk, the world’s richest person, is said to be spending at least $200 million. So that’s a bigger chunk. He has given some money directly to the Trump super PAC. He’s given some money to these congressional super PACs. 

Is this just quid pro quo? Is this just a group of businesses who think, “Hey, no matter how unpopular this guy is, it is worth investing in him and his party because they’re gonna, regulate or not regulate in a way that’s favorable for us”?

It’s not quite just that. He raised a ton of this money when he was not so unpopular. If you want to say something smart that he did, it was that. Throughout 2025 he was raising all of this money.

And I don’t want to overstate the Republican advantage. A lot of these Democratic candidates are raising a ton of money. James Talarico stands out as maybe the peak example of this.

The Texas Senate race is the most expensive race in the country right now, and Republicans are pouring $200 million to save the nominee there. So a big chunk of that advantage is going to Texas. And the Democrats have put very little money from outside groups into Texas. 

Talarico has captured the imagination of these small Democratic donors, and he’s raised tens and tens of millions of dollars. I would be shocked if he doesn’t hit $100 million by the end of the cycle. 

You reported that the GOP’s pulling back in North Carolina. What should we take from that in terms of how the GOP sees its own landscape when it comes to the federal races?

Where have Republicans put that money? They put it into South Carolina right next door to protect a seat that was once thought, on the Senate front, to be safe for Republicans. This is the former Lindsey Graham seat that his sister is now running in. And then even more of it has gone to Kansas. This is a state that has not elected a [Democrat] to the Senate for nearly 100 years. 

If you’re the Republican Party and you’re pulling money out of a state like North Carolina that hasn’t elected a Democrat since 2008, and then putting it into a place that hasn’t elected one since 1932, that tells you where the, the bar is moving.

I think the concern for Democrats right now is there might be a wave, but Kansas has a big red wall. It’s hard to beat that kind of institutional advantage for the Republican Party.

Considering how close we are to Election Day, like, what are they actually spending this money on? Is it just more ads? Is it just more mailers?

I was in Pennsylvania this month, and I was trying to watch political ads on YouTube for various races. And I was getting pre-roll of three political ads before I watched the political ad I was trying to watch. So much about our elections is being decided now by people who are actively trying not to consume political news. It costs more money to reach people who are avoiding it on purpose.

There are some organizing things that happen, but most of the money is various versions of advertising.

On the Democratic side, considering this GOP edge, what are the races that you currently describe as underfunded? Where do the Democrats wish they had more money?

Number one is governors’ races, actually. When you look at where Democratic donors swoon, it’s Senate races. There are no candidates for governor who have made people swoon like this in recent years. 

[James] Talarico is raising all this money, but in Texas also, Gina Hinojosa, the Democratic candidate for governor, does not have that kind of money, and she’s running against Greg Abbott, who had $100 million.

What should we ascribe that to?

I think there’s actually a pretty simple answer, which is, if you don’t live in the state, it doesn’t impact you. If you’re a small donor and you live in California, you can be excited about a Senate candidate because you want Democrats to control the Senate. Are you as excited about a Democratic governor of Georgia?

It’s hard to argue that the governors of these key presidential battlegrounds aren’t some of the most important races on the ballot this year.

By the way, a problem with both parties. Republican national donors and these super PACs also don’t fund these governor’s races at the same level. So it’s not just a Democratic issue, but it’s more acute [for them] because Democrats are so well-funded at the small-donor level.

Fundraising is a huge part of what sets the presidential candidates apart from one another. The money game among those candidates has already started. Is there anyone who’s quietly built some donor network that’s worth thinking about? Is there someone who stood out as a particularly effective fundraiser when we think about the 2028 crowd?

Let me give you my favorite stat from the last Democratic primary, which is that Mike Bloomberg spent twice as much as Tom Steyer, who spent twice as much as Bernie Sanders, who spent twice as much as Joe Biden, who became the Democratic nominee. And so money isn’t gonna determine who wins the next Democratic presidential primary.

One person who has unlimited money, functionally, is JB Pritzker. He’s a billionaire, the governor of Illinois, and he is spending his money now to help other Democrats, which is a good way to make friends.

My last question is an open one. What’s an underexplored story that we should be following going forward when it comes to campaign cash or both parties’ relationship with money?

One of my big questions is what happens to Republican small-dollar fundraising in that post-Trump era. Because there have basically not been any other Republicans who have excited donors for a decade.

Not JD Vance? 

I have not seen evidence. JD Vance was not a good fundraiser before he [joined] the ticket with Donald Trump. When he ran for Senate, his primary run was funded chiefly by Peter Thiel through a super PAC.

There are candidates who’ve raised some money, but nothing on the scale of what these Democratic candidates have been able to raise online. When you talk about that Trump era [ending] at some point, are there others who are going to get Republican small donors excited? We don’t know. We haven’t seen it yet.