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!}

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.

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!}

Today, I’m talking with Illinois Gov. JB Pritzker, who has a lot of thoughts about AI, tech, and privacy.

If you’ve been listening to the show, you know that one of my running theories is that those issues are driving a big and maybe kind of unexpected political realignment — and with the midterms coming up next month, and early voting already underway in a lot of places, the stakes are pretty high right now.

So I asked Gov. Pritzker about all that, and he was surprisingly willing to dive right into the absolute existential weeds of what government is even for. You’ll hear him say — and it’s hard to disagree — that some problems are just collective action problems that require the government to do a lot of work. We can’t solve all these problems one at a time, or even one state at a time. It’s a pretty deep conversation, and we really got into it on a lot of issues.

And of course, I had to ask him: Are the Bears gonna stay in Illinois?

Before we get going, do me a favor and subscribe to Decoder on YouTube, where we put out new episodes every Monday and Thursday.

Okay: Illinois Gov. JB Pritzker. Here we go.

Gov. JB Pritzker, you’re the governor of Illinois. Welcome to Decoder.

Thanks, Nilay. Great to be with you.

I am very excited to talk to you. We’re in the heart of midterm season. You are running for reelection. I have to tell you. I have to be very honest with you. I personally feel a lot of pressure in this interview, not only because I’m speaking to a governor, but because I went to school in Chicago. My sister still lives in Chicago. My wife grew up in Illinois. Her entire family is farmers in North Central Illinois. Boy, do I have a list of questions for you. I have to do a good job here.

Well, we’re claiming you. Now that I know all that, we’re claiming you. You’re an Illinoisan.

I don’t know about that. I grew up in Wisconsin. Here’s my first question for you. I’m a die-hard Packers fan. Are you going to let the Bears move to Indiana?

That is not our intention. We are, in fact, in discussions with the Bears and the NFL about keeping the Bears either in Chicago or in Arlington Heights, but in Illinois.

I’m saying, as a Packers fan, nothing is funnier than the outcome of the Bears moving to Indiana. I just want to put that out there. Openly biased in this case — I own two shares of that stock — but I’m going to make the comparison here. And the reason I started there is not only because I think that’s a funny outcome, although I do, but it feels like we are in the middle of a generational political realignment.

I’m sure you feel that, in this election campaign, the idea of big business and how that should interact with the government, and how the government should be able to push back on big business and not give in to big business. All of that feels up for grabs.

And the comparison I will make in this specific case is your fellow governor, Gavin Newsom, in California. They sued the Ellison family, Paramount, over the Warner Brothers merger. Paramount threatened to leave. They made a lot of noise about Nashville, Texas, Miami, or wherever you make noise about these days, and it feels like Newsom caved. It feels like he pressured his Attorney General, Rob Bonta, to settle that lawsuit and keep them there.

They settled the lawsuit. The next day, the Ellison family is like, “We never… We’re from California. We would never leave.” I see a parallel here with the Bears that is connected to that larger realignment, how government and business should interact. Do you see that parallel? Do you feel that realignment?

Well, what I can tell you is we’re pretty tough negotiators in Chicago and Illinois, and that’s really what we’re in the midst of now with the Bears. But I understand your point about realignment. I mean, there is a generational change, and I think it’s also an attitudinal change about protecting taxpayers, protecting people who frankly are among the most vulnerable to all the technology that’s overtaking people’s lives and invading people’s homes.

And so I do believe that the government has to be more active now and become a fighter for our people and not just a collaborator with business on everything. I’m a businessman, as you know, before I became governor. But I also know that, for the people of Illinois anyway, my job is to protect the working people of this state who often don’t have anybody protecting them except a government that will stand up for them. So that’s kind of the realignment that I see.

And that generational shift, I agree with you. It’s partly a Democratic Party generational shift. Generationally, we’re a little more aggressive. And I’m probably older than the next generation that’s already possibly taking office this November. I’m 61 years old, but I think of myself as having come out of the tech world and as somebody who has been a fighter for progressive values that, yeah, we’ve got to become more aggressive and make sure we’re standing up for our people.

There are two places where I see the realignment in particular. One is data centers, one is privacy, and you just see that as a bipartisan backlash to those things. I would actually add a third, which is antitrust broadly. It’s weird if you go into Silicon Valley. David Sacks is retweeting Lina Khan from the Biden administration talking about whether the AI industry needs an antitrust exemption to manage safety.

They both agree that these companies don’t need antitrust exemptions. They actually should be more competitive. Again, putting that in the context of regulating these companies, thinking about the dynamic between the government and the biggest companies in the world. I’ll just ask the question, I guess, more directly. Do you think Newsom was right to give in to Paramount, or do you think he should have forced them to make good on that threat to leave?

I can’t speak to the Paramount situation well enough to give you an answer, so it would be unfair for me to do so. I can say once again that our orientation today — and I think about the big AI companies and the big social media companies as well — has to be like, wait a minute, too much power in too few hands.

Particularly when we talk about AI, where it’s potentially existential, but certainly transformative, which is probably a kind way to say it about the economy, that we’re going to have to get very engaged. Guardrails, of course, on both parts, but also addressing what I think on the AI front is potentially a significant change in employment in the United States. I’m not somebody who is necessarily convinced that we have to see a whole bunch of job loss, but that does feel like that’s the direction this is going.

What I’m suggesting is we better be prepared, and we better be protecting people who are going to lose their jobs, or at least it appears they’re going to lose their jobs. And I’ll just give you this thought. If these days 4 percent unemployment is kind of the acceptable near full employment number, I think the problem we’re going to see is — if that’s sort of the level that we’re going to hopefully aim for and stay at — that in very short order, we could end up at 7 percent and have that be the baseline, or maybe 10 percent.

And if you think about what’s happened, the upheavals of economies and of governments when you get to 10 percent unemployment in any country. We better be focused on how we’re going to give people the dignity of work and enough income so that they can make a life for themselves when you’re going to put people out of work by virtue of this technology. By the way, much of the benefit of that is going to go to a very, very few people. So we’ve got to wrestle with that and come to a conclusion.

I wanted to start with some of the brinksmanship we have seen in the negotiations between, particularly, states and the big companies, because that brinksmanship is real. The threat is we will leave. We just covered, I don’t know, Kevin O’Leary in Utah talking about data centers, and the people of Utah really pushed back against Kevin O’Leary building that data center. But his argument was, “Well, I’m just going to shop around.”

This is what states do. They compete with tax incentives and benefits, maybe for data centers, which will put everyone out of a job. They compete for land use rights. You’ve got a rural state with a lot of farms in it. How are you thinking about that dynamic? Do you feel like you’re in competition with the other states, or is this bipartisan realignment creating more of a level playing field where these companies are going to have to actually give something?

We are in competition. We just are because it isn’t bipartisan, at least if you ask me. Unless there is a change in the government. I’ll pick on Texas for a second, and there is a chance that you’ll see a new governor in Texas as of November 3rd. In fact, a good chance. But if you look at Texas as it’s run today by a three-term, hoping to be a four-term, Republican governor and a Republican legislature, they have no intention of changing their alignment about incentives.

In the state of Illinois, we don’t want to have to do that. I mean, we obviously want to protect the revenue that we’ve got for the state to pay for the things we think are valuable to our people, but we also want to make sure that we’re attracting jobs and not losing jobs. And in a world where South Carolina, Michigan, Texas, Florida — pick your poison. Michigan may be slightly different just because it’s got democratic control, but these are our competitors. When I’m competing to have a company move to Illinois, I’ve got to make sure, first of all, that I’m somewhere in the ballpark when it comes to the incentives, because otherwise we don’t even get considered.

And then when I say somewhere in the ballpark, I mean, I want to give away less than more, and then I want to provide whatever other advantages I can that aren’t financial so that I can protect the resources that we have. An example of that is, we like to talk about a kind of white-glove service that we offer to companies. If you’re going to bring a factory here, let’s say, just to give an example, we want to make sure that we’ve got somebody who’s kind of a concierge for your company that’s walking you through each of our departments where you need a permit. It doesn’t mean we’re lowering the standards. It just means, a lot of times, the bureaucracy eats up so much time that it makes it impossible for a company to actually do what they want to do in your state.

We try to make sure that if we’re going to attract a large company, with 1,000, 2,000, 3,000 jobs, that we’re at least making it a little easier for them to go through without having to give them massive tax incentives. So that’s the way I think about it. We are in competition. There’s just no doubt about it. Should we be? There’s a lot of discussion about whether we shouldn’t, and maybe at the federal level we should do something about leveling the playing field, but this is the world we’re living in right now.

I wanted to ask those questions just to set the baseline. I really do think something is happening. A lot of young people are dissatisfied with the status quo. A lot of people in general are dissatisfied with what big tech companies are trying to do with AI, with the potential for job loss.

And the relationship between the people, the government, and those companies seems more fraught than ever, especially as they’re trying to expand their physical infrastructure with data centers, as they all become defense contractors, literally taking our tax dollars to sell weapon systems and collect data for the government. That’s a big swirl.

I wanted to start there, but I just want to take one second here and ask you the Decoder questions because I personally think the operation of government is so opaque. It’s very easy to figure out how big companies are run. The CEOs won’t shut up. They’re on podcasts all day long. I think most people have no idea how your job works.

So you were elected governor. How is your office set up, and how have you structured the state government of Illinois?

Just starting from where I sit, and then, of course, we look at it from a customer service perspective. But starting just at the top, I actually did something that no governor of Illinois has ever done — which is that I created not just one deputy governor. We obviously have a lieutenant governor who’s elected also, but a deputy governor is somebody getting appointed by me to serve under me, to help manage the government with me. What I did was put four deputy governors in place, a general counsel, and my chief of staff.

Why is that important? Because what I’ve tried to do is to break down the silos of government. I took all of the health and human services-related departments — that’s the Department of Public Health, the Department of Human Services, the Department of Healthcare and Family Services, everything from health insurance, Medicaid, and public health during the pandemic — and put it all under one deputy governor working directly for me. The idea is that instead of my having, let’s say, 26 direct reports, I’ve got four or five direct reports plus my chief of staff, who each have, let’s say, six or seven departments underneath them.

From my perspective, what I wanted to do was make sure that I’m breaking down the silos of government, making these departments that are often building walls, and they don’t want to talk to one another because they’re afraid they might lose jobs in one department to another department, or lose control of a program if they’re talking to one another. That’s the way it used to be. Now we’re like the deputy governor is there to either beat the heads together or at least bring them together so that they will be operating the government more efficiently. Okay, so that’s from the top.

From the bottom, which is: how do people who live in Illinois interact with the state government? And obviously, technology is one of the upgrades that’s occurred and made it easier. Illinois, frankly, had not significantly invested in those processes before I became governor, or in the technology that was necessary. And I’ll just give you one example of this: We created something called BEACON, which is designed to address the problem that parents and families have with mental health for children. It turns out that there were seven different ways in which people approached the government to get help, and we weren’t coordinating those, and we weren’t helping to provide all of the resources.

I’m talking about outside resources. How do you find a therapist? How do you find a psychiatrist? And how do you pay for those things? Medicaid, if you can’t afford it on your own. But the point is, there’s one door to enter through BEACON that allows you to get access to all of those resources, even if they’re in multiple departments. So that’s just one example. We’re trying to think of this as a customer service operation. It’s one thing to say this is how the org chart looks and another thing to say, this is how you access all the resources of the government that you need.

We provide programs that really matter to people. We have a birth equity initiative to reduce maternal mortality, particularly in Black and Brown communities. And free diapers for some people. The problem is, people don’t even know that the programs exist, and how would you ever figure out that the programs exist, especially if you’re a working person who’s working two minimum-wage jobs? You don’t have any time, and you don’t have any money, and you don’t even know how to talk to the government. And so we’re trying to fix all of those problems of the government with the way that we interact with people.

It’s funny. It feels like that is one of the bigger opportunities when it comes to AI, just letting the AI navigate a bureaucracy for you and communicate what resources are available. The flip side of that is that people hate AI. They truly dislike it, and it doesn’t feel like that connection has been made — that a lot of these tools can actually just navigate a bureaucracy for you. Are you thinking that should be an investment that you make, that it might be what turns the tide in terms of how people feel about these tools?

Yes, but I’m not plunging headlong into it. And I realize that there are probably states that are plunging headlong into it.

I mean, the United States government rolled out its AI chatbot to look at webpages across the government.

Well, there you go.

I guess what I’m trying to do is make sure that… I created something called the AI Cabinet in my government, and that is to essentially bring the experts on AI together with the leaders of my mainstay agencies of state government, so that we’re thinking about privacy, safety, and efficiency. And those things have to be talked about together. You can’t just say we’re going after efficiency and we don’t really care about the other two.

So that’s the idea, the AI cabinet. It’s also that, honestly, there are things, as you know, about AI that are dangerous. And so we’ve got our emergency management agency on that AI cabinet. We’ve got our state police on that AI cabinet. And remember, a lot of the people that work in those agencies aren’t particularly proficient at AI or really understand the potential and the potential dangers.

That’s why we brought in experts, for example, from the University of Chicago, the University of Illinois, just as two examples of places where we’re drawing expertise. So yeah, there’s a lot to be done. I would say we’re trying to approach it carefully before it gets out of control to a point where we have no way to pull it back in.

The other Decoder question I ask everybody is about decisions. You have a big job. You have some constraints in your decision-making process, right? There’s a state legislature, there’s a federal government, you have other agencies in your state. How do you make decisions? What’s your framework?

Well, I don’t do it the way Donald Trump does.

It’s funny you say it that way. I guess I start with the idea that we have a problem to solve and that decisions have to get made. Are those decisions ones that need to come to the governor? Because you’re right, I only have so much bandwidth. So the question is: which are the most serious ones that can’t be solved by other people, or are unlikely to get the outcomes that I would want by handing them over to other people? And then those automatically come to me.

So what I’m making decisions about is kind of the first answer to your question, and then it’s how do I actually make the decisions? For me, I am not one of those people who thinks that I’m right 100 percent of the time. Maybe a good way to describe it, and I’m joking a little bit when I say it, is that I’m 90 percent sure I’m right, but there’s also a 10 percent chance that I’m dead wrong. I want to make sure that I’m getting input and a debate before I actually make the final decision.

Someone once told me that the best CEOs are ones that, in their organization, are a little bit below average in terms of their capability and intellect. I’m not saying we want below-average leaders. I’m just saying you’re so good at hiring that you’ve got people in your organization who are really far better than you are at various things that you’re not particularly good at. Maybe knowing what you don’t know and being willing to ask for help is a philosophy that I have. Be willing to ask for help if it’s something you really don’t know.

And I’ll be honest, when you become governor of a state, there are a whole lot of topics within the purview of a governor. Making decisions about all those topics, maybe a human being who has super intelligence might be able to do it, but most people don’t start out knowing everything there is to know about public health, public safety, and education. And so you start out with what you know and then try to add expertise to it and then make decisions based upon the best experts debating one another in front of you. At least that’s how I like to do it.

Give me an example. Governor Kathy Hochul from New York was on the show. She said in her first week she needed to declare a state of emergency because of a hurricane, and she just didn’t know how, which was very humanizing in its way. Give me an example of when you became governor, and there was something where you just didn’t know.

COVID.

Sure.

I mean, honestly, no one runs for governor thinking there’s going to be a global pandemic. You think you’re going to solve education problems for people or put more money in people’s pockets by raising the minimum wage or whatever, but COVID comes along. And I have to admit, the level of expertise, I don’t think any governor… Well, maybe Josh Green, the doctor who’s the governor of Hawaii, maybe he had a lot to [of expertise] start with — but for the rest of us humans, that was one where we were learning on the job.

We were working 18 hours per day. My entire team was all in, and we had to do things like emergency procurement of ventilators and masks, and we had to go outside the box. It’s not like we could just put it through our central management services, look for a contract, or whatever. This was like, I need masks in three days.

I’ll tell you a quick story, if you’re interested, about my interaction with Donald Trump at the time because I think it’s interesting, anyway. But I’m not a big fan of Donald Trump, in case you didn’t know. I was one year into office when the COVID pandemic hit, and I had not… I mean, I talked to his administration, but I didn’t talk to him directly. So I picked up the phone and called him, and I said, “Mr. President.” By the way, I wrote a script for myself because I know he likes to be flattered, and I’m not somebody who normally likes to flatter him, but I wrote a script for myself. I saved it; I even have it today.

And I said, “Mr. President, you’re a great businessman, but you can understand that paying $8 for an N95 mask that should cost us 75 cents means we’re in a national emergency. We need to be able to get these things and afford them, and I’m competing against all the other states. We need to invoke the Defense Production Act in order to make sure that we’re making enough masks in the United States.” That’s what I told him. And then I said, “But I need masks right now. What can you do for me?” I said, “I need 2 million N95 masks, and I need 4,000 ventilators.” And he never delivered, just so you know, even though he promised that he would deliver.

The challenges in COVID were mighty, and the organization that we had to create around it… I had meetings every morning just on this topic, figuring out, okay, how many hospital beds [are available]? We didn’t have a system that would tell us statewide how many hospital beds are available in each region. What happens if you have an outbreak and it really is overtaking some region? What do we do?

And so these were all the things we had to learn on the fly. And all I can tell you is, once again, back to hiring great people to have around you, I really felt like I proved that I had done a good job of hiring because the people around me were tremendous. One of whom, by the way, is now running as my lieutenant governor partner in this election.

It’s interesting you brought up COVID in the context of our conversation about generational political realignment. I would actually point to COVID as the beginning of a particular realignment around what the government should measure, how much control the government should have over people, and all of that has led, I think, directly into the bipartisan pushback against Flock cameras.

The very notion of privacy is not, in my mind, left or right anymore. The CEO of Flock got himself in all kinds of trouble because he kept saying all the people who wanted to ban Flock cameras are criminals, and he would go on MAGA media and say this. I think that position was just rejected. We can see in states around the country that there’s pushback against Flock cameras. I would point to COVID as the beginning of that.

The idea that the government could be too intrusive, and in particular, the government should not be able to measure things. “If you don’t test, there won’t be COVID” just became an idea. And the idea that we shouldn’t measure things, or we should tear down our systems of measurement, is a big part of the second Trump administration. But I see that privacy connection very clearly to COVID. In one world, the government coming together to protect its citizens and build a bunch of systems could have gone a very different way. In the one we live in, there’s ferocious pushback to that, on the left and the right in some ways. How do you feel about privacy right now?

I know Illinois leads the nation. You’ve got the Biometric Identification Protection Act. Every time I fly to Chicago, I’ve got to push the button at the airport to say that it’s okay to look at my face. That’s one way of going about it. But then you do have, I think, hundreds of Flock cameras in Cook County alone. People have Meta glasses with cameras in them. There’s something happening with privacy that is running right into the aftershocks of COVID and how people feel about government intrusion. How are you finding a way through that balance?

Well, and don’t forget AI.

Yep.

As you’re suggesting. I mean, talk about a collision. This focus on privacy is warranted and long overdue, to be honest with you. I understand what you’re describing about COVID, but I think something that came out of COVID got accelerated, and that was conspiracy theories.

Yes.

And I’m not suggesting that everything you hear now about the pushback around privacy is a conspiracy theory, but it is easy for these things to spread, and people have misinformation that’s informing them about how these things are used. Having said that, I guess what I think is that we are having to solve multiple problems at the same time, and that AI is coming.

Let’s just go to AI for a second. It’s here. I mean, I say it’s coming, but it’s here. It’s not going to stop. We’re not going to become Luddites without any AI. So the question is, in the context of privacy, what guardrails are we putting on AI, and how are we managing it? This idea that the president and David Sacks had, where they got all the companies together and said, “Hey, how about you guys self-police?” That’s not going to work, at least not for protecting people’s privacy. And frankly, it’s not going to provide any safety either because everybody’s going to operate in their own self-interest. It’s one of the reasons why you need a government, in my view.

I’m not suggesting the government is any smarter than these companies. But one of the reasons you have any kind of collective action of the government is because, separately, as you know, people operate in their own self-interest. I mean, you could have a Hobbesian world where people are killing each other, and there are no rules about it. So I think we’ve got to use the government as a tool and also be smart within the government. And that’s where the generational change, I think, is hugely important. Use the government as a smarter, less bureaucratic collection of people devoted to protecting the privacy of everyone and making sure that we’re addressing all the other challenges that come from AI.

So I guess I’ll just say, I don’t think we’re anywhere near where we need to be, but I will say, if we don’t have a federal government, now I’ve got a lot of… I’m very proud of the things that we’ve done here in Illinois around the AI Safety Measures Act, which is the toughest in the country, the Children’s Social Media Safety Act, and so on. I’m proud of the work we’ve done, but state by state, this is not the way to do this. We’re doing the best we can in the absence of a federal government that is addressing these issues.

And when I say federal government, I’m not just pointing at Trump. I’m pointing at Congress. No action on their part means that we’re going at it alone. And right now, I don’t know how many AI safety measure acts have been passed, but it looks like three to me. I mean, it’s New York, California, and Illinois. Maybe you could name a couple of others, but we three were the first. And yet, we’ve got 47 other states.

This worries me a great deal. You’re raising issues, and I’d love to tell you I have all the answers. I can tell you what we’re trying to think about is that we are the… People sometimes say that the states are laboratories of democracy. They’re actually laboratories of policy, and we are trying to, at least in Illinois, use ourselves as a laboratory for policy while not creating disadvantage for ourselves. And so that’s a very challenging thing to do, and why we need to change what’s happening at the federal government.

Focus on privacy for one second. I understand what you’re saying about AI. I think part of the privacy debate around Flock cameras, for example, is, well, sure, you can have one license plate reader in one intersection. And if the cops had to go there and pull the SD card out of it, drive it back to headquarters, upload it to their Apple IIe, and look at it manually, maybe people would feel one way about it.

But those cameras are all networked. They don’t have any access controls really. There are infinite reports of local police chiefs tracking their girlfriends across state lines with these cameras. You add in a system like Palantir, which can synthesize multiple databases and do all kinds of tracking across all kinds of systems. People see that.

The turn that is being made is that you can connect a lot of databases of information together, search them without a warrant, and track people across the entire country. You could ban that state by state. You could regulate it city by city, which we’re seeing happen with Flock, and you could maybe have some federal controls around privacy there. None of it’s really happening, but on the ground, people are ferociously pushing back. And that’s the connection I’m making to COVID, conspiracy theories, and how much power the government should have to surveil you and look at you.

Something happened in there where people’s attitudes about that really shifted. And I would say one of my core beliefs is that Americans do not like being told what to do. Party politics aside, Americans don’t like being told what to do. Something about that flipped and connected to: we have a network of license plate-reading cameras, and we’re going to tear them down when we see them because there’s something about that that offends us as Americans.

Illinois does have privacy laws. I think the last update to the biometric law you did was in 2024, and it has changed again. It’s gotten more vociferously opposed to tracking and surveillance in this country. Do you think you need another update to that privacy law?

I think we should be looking at that question every year. I’ll give you an example of it. We passed it, and again, I’m back to AI because I think how you’re describing it was a perfect way to say it. If it was an SD card that they had to go grab and then analyze back at the station, it’d be a different thing. But it’s AI that’s operating these things, and that’s allowing this stuff to move instantaneously and track people.

Look, should we be addressing it? Yeah, every year. It’s like the issue of ethics in government. What I mean is, the minute you put an ethics law in place, there’s somebody who’s trying to get around it. I mean, every year, it’s like every law… this is probably true across all of capitalism, maybe. There are always people trying to find a way around the law. Put a tax law in place, and someone’s trying to figure out how to get around it. And I think the point you’re making is that that’s why you need to have a proactive government, less bureaucratically and more aggressively trying to address these things. Are we going to be able to keep up with it? I’ll be honest, I don’t think so. And I also don’t think you can say, “Well, we’re just going to shut it all down” because there are things you’re missing out on.

It’s sort of like, and again, I keep going back to AI, but I think a lot about it. My children are 21 and 24. They’re going to live to 100 or 110 years old because AI is going to solve a whole bunch of medical challenges, and already is. There’s a cure now for sickle cell anemia, and people who would otherwise die at 25 or 30 years old are going to live full lives. This is going to happen across the board in cancer and everything else. And so there’s all good in there, and then there’s the bad. So I know what you’re saying. I guess all I can tell you is I’m a believer that we can progressively — I don’t mean that in a political fashion — address these challenges.

In Illinois, we passed a law that disallows the use of AI in therapy for people because we think too much information gets collected, not enough humanity in the process, and we think that it should have humanity in it. Again, we’re not trying to shut it down across the board, but we’re going to have to see how it gets used and where it’s improper.

And I know that sounds imperfect because the technology is moving so fast that the idea that we’re going to be able to keep up with all the ways in which someone’s privacy could be breached seems very difficult, but I don’t know any other way to do it. That’s why you have a government, and maybe in the end we’re going to have this competing use of things like AI, where AI is monitoring AI, and AI that’s kind of privacy-friendly or focused on privacy is going to be monitoring the AI that’s not. But again, I know you don’t want to just talk about AI.

I am concerned. This issue of privacy has been around for a long time. You’ve been talking about it, I’m sure; I’ve been talking about it since before AI. This is like everybody giving over their personal information in exchange for access to something. And that was happening for a while, and then we’re all getting ads that are personalized to us based on stuff that we’ve essentially given up privacy for.

No, it’s funny. People believe, and we can write as many stories as we want about how your iPhone is not actually listening to you, but the ad tracking is so good that everyone believes that their iPhones are listening to them. The next turn is that it is now technologically feasible for these systems to listen to you all the time. And I can’t fall back on the idea that it’s cheaper for them to do the ad tracking when you hit I accept than to listen to you all the time, which was, for a decade, the right answer.

The economically correct answer was that ad tracking was cheaper than listening to you all the time. That might be very different in the future. There are already devices that we cover here at The Verge that purport to listen to you all the time and turn that into some actionable data. And it feels to me like the tech industry is trying to drive a truck through our privacy law, through our lack of AI regulations, through an entire system of governance that is designed for the pre-AI era.

The notion that you don’t have privacy in public worked really well when everyone didn’t have a cell phone that could connect to the cloud and instantly search every photo all at once, all the time, and do facial recognition. We live in that world now. I would say the public sentiment towards the idea that you don’t have privacy in public places has turned.

They don’t like the Meta glasses. They call them pervert glasses for a reason. And somewhere in there is, well, the federal government should pass privacy law. It is a failure of imagination in the United States. We don’t have federal privacy law. And then somewhere in there is the notion that the states are laboratories of democracy and policy.

It is amazing, by the way, how often on this tech and business show, Thomas Hobbes comes up and the very notion that the government is there to serve as an extension of us solving collective action problems. It comes up over and over again because I think the tech industry does not want to respect that dynamic.

This is why I started with that relationship between government and business, and the pushback and the negotiation, because here it feels like the tech industry is in a bubble of its own making. Truly, in a media bubble of its own making. And then all of the polling is, well, we hate AI. In particular, young people hate AI. And then all of the action is around data centers where NIMBYism, the most American of policy levers, is being pulled to keep these data centers out of communities. And that’s one way to stop AI.

You just pulled back on data center tax incentives in July. You’re pushing the state legislature to adopt a suite of guarantees on reforms for new construction. Do you think data centers and the pushback on data centers is an effective route towards AI regulation?

No, I don’t. I think it’s an effective route toward data center regulation. I know that people have conflated and put together their opposition to data centers with their opposition to AI. And a lot of people can’t describe why they’re opposed to one or the other because they’re conflated with one another. But I can say that — I mean, at least our aim is focused on the idea, and people really feel this, right, and there’s real data to back this up — the data centers themselves put aside what they’re doing inside a data center.

The data centers and what’s happening are eating up the available electricity, and that’s causing your electric bill to go up. At least that’s how everybody feels. There are a lot of things that we should have been doing in many years gone by to get to a point where electricity bills shouldn’t have to go up now. And that has to do with building out the grid. It’s a world where regulation and cross-border challenges have made it nearly impossible for a lot of the grid to get built the way that it should have. We produce a lot more electricity in the United States than we use, but we just don’t transport it well enough, and we would have a lot more available if we transported it better.

Okay, but even if you think that can’t happen efficiently, we need to build more capacity on the grid. My only point is the opposition to data centers is, in part, a result of the economic situation that’s happening right now in the country, where electric bills, gas, rent, everything has gone up. Your electric bill shows up every month, and it continues to go up, and people kind of scratch their heads and say, “Who am I paying for?” This is happening, and this is particular to Illinois.

We’re not going to have a whole discussion about energy policy, but I could just say this: We produce more nuclear power in the state of Illinois than any other state. Roughly 53 or 54 percent of our electricity comes from nuclear power, and we’re a net electricity exporter. So we have an excess in Illinois, but our bills are going up, and that’s because of the methodology of the regional transmission organizations. Again, not to get into all the details of it, but essentially, if Ohio decides to build a hyperscale data center, our bills in Illinois are affected, and that’s shocking to people who live in Illinois. But what they know is they don’t want their bill to go up, so they don’t want another data center nearby — even though the one in Ohio is actually causing the problem, even if you choose to oppose data centers.

So this is a challenge. I think there’s a lot of information that needs to be spread. But most of all, we just need a whole lot more capacity and a whole lot more grid that will, I think, subside some of the concern about data centers. To your point, privacy is, I think, more related to AI than data centers. And it’s not just AI, but the way AI is used. So we’re going to have a lot of opposition. You make an excellent point. I think this feeling of being out of control — you are not in control of your environment anymore — that’s the thing that is causing anxiety.

I want to go back to something really important that I was saying earlier. We need better people running for public office. We need smarter policy development in government. And part of that is a generational shift that’s needed and a better understanding. We have people who are serving in the United States Senate who have no idea. Was it the Secretary of Education, Trump’s Secretary of Education, who called it A1? I mean, because we’ve got older people who don’t have any exposure who are making policy theoretically on these things, and it should disturb us all. It’s one of the reasons we’ve got to advance the cause of better people and better systems in government.

We are on the cusp of an election. There might be a new Congress. There might be new leadership in Congress. There are a bunch of old Democrats too. In fact, I could probably point directly to Joe Biden’s age in the last election as the reason that he lost. Do you think that you need a wholesale change of leadership of the older Democrats as well?

You said, “Do we need a wholesale change?” I mean, I can tell you that I don’t think we should be telling —

Well, now I live in New York. I’ll just ask you, do you think Chuck Schumer should be the Senate majority leader if the Democrats take the Senate?

That’s a decision people in the Senate are going to make. I have no influence over it. I can tell you this: I am opposed to term limits because I think that you should have all the choices. You’re a voter. If you want to vote for the 75-year-old, I mean, go ahead.

I’m just suggesting that a great case could be made for the 45-year-old who’s just as smart as the 75-year-old was when he was 45, or maybe is now, but has a modern look at the issues around AI privacy, everything else we’re discussing, and a more aggressive view of how we ought to be reining in big corporations in their invasion of our lives. But I think people ought to make their own choices. I mean, for us to say, “Well, we should have an age limit. You’re 70, that’s it, you’re out.” I think that belies who we are as a democracy.

Well, you convinced me. I’m 46. I’m announcing my run for president here with you, Governor. That was a rousing speech.

Listen, I would vote for you in a second if the choice was you and Donald Trump.

A low bar, but I’m glad I crossed it.

Let me tie two ideas together at the end. We’ve talked a lot about AI regulation. You mentioned social media regulation a little bit earlier in this conversation. I know that Illinois has a social media law. You have a bell-to-bell ban on phones in schools for kids.

I’m just going to pick on Mark Zuckerberg. It’s easy to pick on Mark Zuckerberg. If you look at how he talks about social media regulation, he basically describes the tragedy of the commons. You signed the landmark settlement with him. I think Illinois is due to get $750 or $760 million out of that settlement. And a big part of it is that TikTok and YouTube have to agree to the same terms, and then Meta will pay the rest of the money. And Zuckerberg very clearly has said that’s because if Instagram falls back on engagement bait and TikTok doesn’t, the kids will just use TikTok. And so the government has to get everyone to agree.

I will tell you that Neal Mohan, the CEO of YouTube, does not agree. He’s not going to sign onto this. That’s one whole fight. Look at how Mark Zuckerberg talks about AI regulation. There’s none of that dynamic at all. He’s like, “It should be a free-for-all. We’ll all compete. If it’s not safe, the market will tell us. We’ll be fine.” And in my mind, these ideas are at total odds with each other.

In the market where he makes all the money, the government has to step in and stop him from hurting kids because apparently there’s no market demand for safe social media. And in the market where the AI CEOs are telling us they might kill us all if we don’t stop them, it’s a free-for-all, and the market will tell us if they accidentally kill everybody. How do you reconcile those things? Are you just happy that you got the social media case done after a decade of failing to regulate social media, or do you think you can solve AI with regulation this time instead of letting it just cook?

Look, I’m an optimist at heart, so I’m not going to suggest to you that I absolutely know that we can solve all the problems that we’re now facing, but I don’t know what else we can do. Other than, again, progressively making sure that we’re trying to address each of these things, trying to anticipate them to the extent we can. Can we be faster than AI is developing? I don’t know. But we can’t stop trying. I know that. And I would suggest to you that my optimism is founded because I think the vast majority of people want what you’re describing, which is reining it in.

And again, without destroying companies. I don’t think we’re all trying to do that. What we’re trying to do is stop the invasion into our home, stop the invasion into our children’s lives. I do think we can do that, but that’s because we’ve solved a whole lot of huge problems. That’s kind of like my answer to: is AI potentially existential? The answer, of course, is yes. And can we solve it? I don’t know. Nuclear weapons… I mean, just to give something of an analogy to something else. I mean, nuclear weapons are still hanging over us as a danger to humanity. And so far anyway, we’ve managed not to blow up the world. I don’t know whether that gives you any optimism, but it does to me.

We, as a country, can figure out how we want to rein it in here. That we, as a country, can work with our allies to figure out how we want to collectively try to rein it in. And then we have enemies in the world and competitors in the world, and we’ve got to figure out how we’re going to… Maybe it’s mutually assured destruction, like it was with nuclear weapons, but these are all things we’re going to have to work on, and work on fast.

And it’s scary because someone analogized this to… I mean, think about the early 1950s when every kid had to learn that if there was a nuclear blast, an atomic bomb that went off, get under your desk. That wouldn’t have been very effective. But the point is, people lived with the idea that a terrible nuclear holocaust could occur with a nuclear explosion. And so I think we’re heading into that world again with AI. I hope I didn’t stray too much from your question, but —

Let me ask you this, and it’s a little bit of a wild card here at the end.

We cover this industry so closely here, and the big difference with nuclear weapons is that there weren’t five companies building bleeding-edge nuclear weapons in private capacity, led by five guys who all hated each other. But that’s the dynamic of the AI industry. They all truly hate each other, and they’re all trying to make as much money as they can as fast as they can.

And then some of them think the AI is alive. If you ask Anthropic, and we’ve done this, “Is Claude alive?” They don’t say no. They will argue with you about the definition of alive and suggest that, to them, alive means having a biological component and Claude doesn’t have that, but it might be conscious.

There’s a race to build AGI in the industry. Some people truly believe they’re building alien minds that have a different kind of consciousness. I’m not sure any government at any level has ever had to regulate that, or has ever come up against an industry that is religious about the fact that it might be building the next kind of intelligence.

Where do you stand? Do you think that they’re building a next kind of consciousness that stands alongside humans, or do you think that this is normal technology as some others do?

Boy, that is really another podcast for us, but I’ll just say this one thing: I just want to disagree with you for a second. Nobody could ever imagine a nuclear weapon either. And…

But the government built nuclear weapons. It wasn’t —

I understand. I’m not suggesting it’s the same. I’m suggesting it’s so new at the time that figuring out how you’re going to rein it in… Because remember, it’s not just one government, and the same thing with AI. It’s not just those five guys either. I mean, it’s like there’s somebody in China. Maybe five of those. I don’t know, and somebody in Europe or whatever. You could say we’re ahead, or they’re ahead. I don’t know.

But all I’m saying is, yeah, this is a proliferated situation and it’s not government-controlled. One hundred percent, you’re right; it’s not like nuclear weapons in that sense. But it is like nuclear weapons in the sense that nobody’s ever seen it before. It’s a complete mystery to start with. How are we going to rein it in? I mean, nobody thought Russia was going to get the bomb, and they got it. We’ve figured out somehow how to deal with it.

Again, you’ve got to be an optimist to believe we can end up with the right solution here. I don’t know that we have the answer to “how do we rein it in?” I will say, though, that if we had the power to create it, we have the power, in my view, to rein it in. Is it conscious? You’re asking a deep question.

Have you felt the AGI?

I mean, do you think it’s conscious? Because I understand why people think it might have consciousness or it’s going to be conscious. But I think that’s why the ethicists and technologists need to be involved. And especially, in my view, the government’s got to be involved because how else are you going to rein in the five guys and the companies that have developed this? There is no other way.

I will tell you, I don’t think it’s conscious. And every now and again, you have an experience where it’s blindingly clear why other people believe that. When you watch a reasoning model take 90 steps over an hour and arrive at a conclusion, it’s impressive, and you can see why people believe that. I do not, and I have a lot of reasons for that.

It just occurs to me that if you set out to regulate a technology like this, if you believe one thing, you would maybe go down one path. And if you believe that you were building a consciousness, you might go down another.

Again, the whole industry itself does not agree on this. Jensen Huang and Dario Amodei do not agree on whether it’s alive. Jensen just wants to sell a bunch of chips, and he will happily tell you it’s just technology and you can control it. I think Dario thinks he’s building AGI, and that’s a different… There’s a whole reason he proposes different kinds of regulatory structures there. I’m just asking you, have you felt the AGI? Do you think it’s one path or the other?

I’m not going to give you a satisfactory yes or no.

I mean, I haven’t felt it. I guess that’s what I’m… My basic answer is I haven’t felt it.

Governor Pritzker, this was very fun. Thank you for indulging this last existential loop of a question. You’re going to have to come back to Decoder soon.

I would like to do that. Thanks, Nilay.

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

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In this episode of Version History, we tell the story of the overhead projector. David Pierce is joined by The Verge's Jake Kastrenakes and Stanford professor Antero Garcia to discuss how overhead projectors were developed, how they made their way into classrooms, and how they changed so much about the way kids learn. …

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Today, I’m talking with Walter Piecyk, a partner and analyst at LightShed Partners who covers tech, media, and telecom, about SpaceX’s recently announced plan to become a major wireless carrier.

Last week, SpaceX agreed to buy a big chunk of low-band spectrum to expand the Starlink network, spectrum that’s been traded around the telecom business for decades now. SpaceX’s ambitious plan is to use that spectrum to help build “the world’s most advanced mobile network.”

Combined with news that the FCC approved the deployment of 15,000 next-gen Starlink satellites and the company’s previous agreement to purchase close to $20 billion worth of EchoStar spectrum last year, it’s now clear SpaceX is serious about competing with AT&T, Verizon, and T-Mobile.

I’ve covered the telecom business for a long time, and I’ve always known that these companies can say they want to do something until they run into the harsh reality of how expensive it is to actually do it. The telecom graveyard of pivots, bad ideas, and failed acquisitions is vast.

Walt has been closely monitoring SpaceX’s acquisition, and he’s correctly predicted that the company was headed in this direction for months now. So I wanted to dig into whether SpaceX can pull this off, why Walt thinks the existing telecom giants have really fumbled their response to SpaceX’s growing threat, and what happens when Elon Musk’s rocket company jumps headfirst into a business everyone loves to hate.

Okay: LightShed Partners’ Walter Piecyk on SpaceX’s plan to expand into mobile. Here we go.

This interview has been lightly edited for length and clarity.

Walter Piecyk, you’re a partner and a tech, media, and telecom analyst at LightShed Partners. Welcome to Decoder.

Thanks for having me. I’m looking forward to it.

I’m excited to talk to you. I feel like we’ve been tweeting or posting around each other for many, many years, but I’m a telecom nerd at heart. I’ve been covering the space for ages. SpaceX is going to make a big splash. It’s going to be the fourth major mobile carrier in the United States and maybe the world. It bought some spectrum to do it.

It’s EchoStar spectrum by way of private equity. It is at once very simple and also very complicated. Give us the state of the state. SpaceX bought 800 Mhz spectrum for $8 billion. They spent nearly $20 billion already on separate EchoStar spectrum. What is SpaceX trying to do here?

It’s definitely complicated, but maybe less complicated than trying to figure out how to put a data center out in space and making that work. Or something on the moon. But they don’t typically want to own spectrum and spend for spectrum. If you think about how Starlink was built, satellite companies don’t typically pay for spectrum. And then as the business evolved and as they saw the opportunity in telecom, they purchased some spectrum initially from EchoStar.

The feedback they got from investors at that time was very positive and they said, “Wait a minute, you should do more here.” This is a trillion-dollar enterprise value business in the US alone. Obviously they have global aspirations both for Starlink as well as what they’re doing with this mobile telephone service. So they bought more. They went back to EchoStar. That’s a key thing to pay attention to, in that they bought some spectrum and then they went back and bought some more.

Because with a lot of things that Elon Musk does, he learns as he goes. He bought the spectrum, got feedback, talked to people in telecom, and bought some more spectrum. Then we didn’t hear from them for a while. Now, you have this thing that happened last week where they bought some more spectrum, and I can go through the history of it if you care, but it’s long, wonky telecom stuff. This was originally the Nextel spectrum, if you remember that company.

I do. Actually, I do want you to go through the history because I think the telecom business is best understood as a bunch of lobbyists trying to make everything more complicated than it should be. Yes, spectrum auctions are complicated and what spectrum is good for what is deeply tied to the physics of the radio spectrum and all that.

But here it’s the 800 MHz spectrum from the Nextel service, the old push-to-talk, walkie-talkie service that Sprint had to divest as part of the deal to get sold to T-Mobile. They’ve been trying to sell it for ages. They sold it to this company, Grain Management. They’ve been sitting on it, and when Starlink showed up, Elon bought it. Nobody else wanted it. What did he see in the spectrum that no one else did?

When you realize that you need to build a terrestrial network to support what you’re doing with satellites, because satellites work fine if you’ve got your dish on the top of your house and you’re getting your broadband, but when you’re trying to connect with a phone that doesn’t have the same type of power or you’re going inside a home, you’re going to need better coverage.

Sirius Satellite also has supplementary towers. There are not that many of them, but sometimes when you get out of Sirius coverage, you will connect to a tower. When they bought that EchoStar spectrum and then got FCC approval, and if you looked into those details of that FCC approval and what was required, you would see that they can’t do this by satellites alone. There had to be terrestrial.

Then SpaceX, as Elon is wont to do, tries to send some diversions like, “We’re going to do Femtocell, we’re not going to do macrocell, this, that, and the other thing.” But they realized that they were going to build a terrestrial network. Now they finally realized, “If I’m going to offer mobile service, I need some form of a terrestrial network.”

At the same time, the telcos are not going to help them out. They’re not going to give them a wholesale agreement. Then when they go back and say the companies that had the lowest churn, what is the fundamental value you need in a terrestrial network? It’s low-band spectrum. Why? It travels further, you can get better coverage, and you have that connectivity.

So getting this low-band spectrum piece was just an important part, not to make the satellites work better, but to actually give them the spectrum assets that they need to build a terrestrial network. That’s why the stocks reacted, because people finally came to terms with the fact that Elon is actually going to build a terrestrial network.

I’m less interested in the stock and more interested in just the cost structure of how this works. If I rewind my brain to being a baby blogger at Engadget 100 years ago, the FCC told all the TV networks they had to stop broadcasting on 700 MHz and we were going to run an auction.

Verizon and AT&T bought big chunks of 700 MHz spectrum and that’s what 4G is built on. That’s the low-bandwidth spectrum that you’re talking about. It goes everywhere. This was a big victory that we reallocated 700 MHz, and 800 MHz was sitting right there the whole time. This is the Nextel spectrum. If it is so valuable, why wasn’t there a market for it until Elon showed up just now?

It was part of this transaction. T-Mobile ended up having to sell it because the government said, “If we’re going to allow you to take out the fourth competitor, which was Sprint, then in order to enable another fourth competitor out there, we need to have you guys give up some of your low-band spectrum.”

Part of the deal that T-Mobile and Sprint had with the government was that they would sell it to EchoStar. Why? Because Charlie Ergen, CEO of Dish at the time — it’s EchoStar now — was going to be the fourth competitor. This was the rationale that they gave in terms of the approval of the transaction. Dish needed low-band spectrum. The problem is Ergen went about his business, he was trying to build a network, and then he just couldn’t afford to buy that.

They had the rights to buy. Then at that point when Ergen failed on the bid to come up with the dollars to buy that spectrum, it enabled T-Mobile and actually forced them to put it up for auction. Now, your question: Why didn’t someone else show up then? Again, from SpaceX’s standpoint, as I mentioned at the start of this podcast, their strategy has been evolving over time.

In terms of the other telcos, they can’t really use it. There are some limitations that they have. But in hindsight, maybe Verizon or AT&T should have bought this 800 MHz spectrum for whatever it was, let’s call it $8 billion. They’re probably losing more in enterprise value over the concerns of what’s happening with SpaceX than what it cost them just to buy it in what’s known as foreclose. They basically just take it, even if they don’t use it or do whatever they need to meet those build out requirements and stop SpaceX from having unnecessary assets. I don’t think even these companies were taking Elon seriously and thinking that he would actually build the network.

Do you think that’s colored by the failure of Dish? We covered the promises of Dish Network to build a fourth wireless carrier in this country so closely. Their attempt was predicated on some amount of technology innovation.

They were going to build this thing called an O-RAN network, which had a more competitive supplier base instead of just Nokia or Siemens or whoever, and they were going to run it on AWS and that was going to reduce costs. Man, eventually they supported one Motorola handset in Vegas and even that was backstopped by AT&T. They literally could not do it. These promises never came true. Dish is a different company and Charlie Ergen’s a different CEO and their ability to just throw money at a problem until it’s solved is very different from Elon.

But if they couldn’t innovate to make a cheaper, faster network, what’s the evidence that Starlink can stand up an entire terrestrial network at a cost basis that allows them to compete selling service to consumers, while they’re also standing up an entire network in space? Because that feels like adding up a lot of cost.

I’m going to go back even deeper than that. Remember when Sprint was struggling, Masayoshi Son from SoftBank was claiming the same thing. They were going to cut their CapEx to nothing and they were going to use these small cells. They innovated how wireless was going to get delivered. That failed. Obviously, they had to get bailed out through the purchase when T-Mobile bought Sprint effectively for just the spectrum.

That network got completely decommissioned. To your point, Dish got a network built, but they couldn’t resonate in the market. The difference between Dish and SpaceX is Elon’s ability to get customers. That’s where Dish truly failed. They built the network. The network worked fine. They had the wholesale agreements that they needed.

I’ll push back on you a little bit there. I have a very funny email from a Dish PR person from several years ago where they said, “We’d like to issue a correction to your story. Our network does exist.” That was the level that they were competing at, where they had to insist to us that the network was real, even though we could not find it in our tests in the various cities they claim.

Maybe there was a network, they built some amount of network, but they had not built anything that competed at the national scale with the big three.

Absolutely. It’s not like your phone. The phone that I was using, I had an iPhone that it was mostly going to roam onto the AT&T and T-Mobile wholesale agreements that existed. The theory is you get the customers, you have a go-to-market strategy, and then you backfill the network. This is probably going to be something similar.

You can even go back to when John Legere first took over T-Mobile. They had a crappy network, and then Legere promised, “We’re going to build it,” taking on customers saying that the network was great before the network was great. Then it caught up because they actually finally got the Germans, Deutsche Telekom, to give them the money to invest in the network.

The same thing can happen here where SpaceX will sell something that’ll probably rely on other assets that are out there, even if the telcos themselves are circling the wagons. They have the satellites for certain benefits in terms of coverage and then they can build the capacity over time. The point is it’s going to take time. You can’t just turn on a network overnight and start selling service on that.

This has always been my framework of how to think about telecom companies. You can try to run the network cheaper or you can run some kind of different technology to make that cheaper. Or you can just spend and have the best network, which was the Verizon strategy for years and years and years.

Then you’ve got to acquire and manage your customers. That was the T-Mobile strategy. That was John Legere. He was just nicer to people than AT&T was, and he picked up a lot of customers and that drove some investment.

Then you’ve got to get some devices. You have to have the iPhone. We can set that aside because it feels like that era of competition is over. We’re not doing exclusive devices anymore. But those are the two. I’m just looking at the network here. It does not seem to me, from the outside, that Starlink is proposing to build a cheaper network.

It feels like they’re proposing to build a vastly more expensive network because they need the satellites. They’re going to launch 15,000 more satellites to support this network. Then they’re going to build a terrestrial network by investing in spectrum on the ground and building some set of base stations.

Then they’re going to have to convince one of the big three to let them roam over as some sort of mobile virtual network operator (MVNO). The big three do not want to do that. So they’re going to overcharge them for that. I’m just stuck at that being a lot of cost, even if you’re Elon Musk and you can make some set of people buy whatever you’re selling.

The third thing you said is obviously the most challenging. That’s the tent and the pole that prevents you from launching services sooner rather than later. But without necessarily getting a wholesale agreement, there might be other ways. Roaming agreements exist out there. There are roaming partners that exist that these telcos still rely on. It’s very expensive. It’s not something you can build a high-margin business on, but it perhaps provides an entry to the market sooner rather than later.

As Apple has pitched in terms of satellite connectivity, some people are in the middle of the Utah desert texting because they’re injured. There’s value there. But it’s the soccer field. We have, maybe not in the cities, but in the suburbs, plenty of areas that the telcos have effectively given up on trying to provide coverage because of NIMBY-ism, meaning people just don’t want these cell sites. This satellite coverage can give you not just this basic text messaging that Apple has been doing through the Globalstar constellation, but a true cellphone-type experience.

So that’s a positive. The second differentiation is the fact that these telcos have 60 percent earnings before interest, taxes, depreciation, and amortization (EBITDA) margins. So there’s a lot of fat there that can be eaten off of, that when you’re selling other services in terms of Elon, like home broadband, maybe this becomes an entree in terms of pushing Grok and people’s usage. You don’t necessarily need 60 percent margins, in this case, for him to justify building this network.

They also talk about other data connectivity that these satellites are going to enable. Again, in the current constellation, you need a lot of power and you need a dish. But if you don’t have that, if you have the cell phone-type power, then the internet of things (IOT) and other types of opportunities that exist there become another revenue opportunity that they look at.

It’s just funny. The IOT story — that’s what all these companies promised us about 4G. That’s what they all promised us about 5G. There’s something about this business that just rhymes every time. They’re going to do self-driving cars and robot surgery. I’m confident we’re going to hear about self-driving cars and robot surgery when it comes to Starlink and Tesla and Optimus.

There’s something about these applications for next generation networks that just recurs, and we hear about them all the time. Then I think about our consumer audience at The Verge, and they want long battery life and fast service and [connectivity] all the places they go. I’m not sure how that squares with your phone is going to connect directly to a satellite in the middle of a soccer field. There’s something about that that also seems challenging.

It’s just the performance if your phone does connect to the satellite on the soccer field and it works. A lot of the things that people said wouldn’t work on Starlink in terms of airplanes or even getting customer-premises equipment (CPE) down below a certain price, they’ve delivered on. Obviously, Elon sometimes delivers on them a little later than some of his initial optimistic promises, but they ultimately get delivered on.

There is the ability with these new constellations to give you that type of connectivity on these spaces. Is that enough to differentiate with consumers? I don’t know. The telcos have attacked this by saying, “No one cares about our direct-to-device (D2D) services.” Well, your D2D services are not good. It’s just sending basic text messages. What they’re talking about is giving you that blanket coverage where you get what you expect from your cell phone wherever you go.

That’s fine, but you still have to give it to the person in the middle of the building where their cell phone works today and provide the volume at a cost that is going to be attractive to that consumer. So those are longer-term things that are going to require some amount of terrestrial network build. Then the question is: how much? A lot of the attacks that have been out there have been referencing $100 billion, $200 billion. I get that. Why?

Telcos each spend $10 billion to $15 billion a year, but they are maintaining massive customer bases. To get that initial network up where you have that usage, where you use that low-band spectrum to get into buildings, is not those types of numbers. You’re probably talking like $10 billion, $15 billion for that initial build in terms of CapEx.

The dynamic there is really interesting. I’m just thinking about AT&T when the iPhone came out. The network immediately got overloaded because there was a surge of customer demand that took four years to truly resolve. Part of that resolution was just putting the iPhone on the other carriers.

How do you think that will play out for Starlink here? Because right now, Starlink customer service is not the best in the industry. Their actual service, people love it. And then when they need customer service, it’s a bunch of automated systems and people complaining on Reddit. So there’s some challenge there if you’re running a consumer business at this scale.

For consumer businesses, think about all the advertising that’s done. The fulfillment, dealing with the phones, phone subsidies, and that’s a big part of the financing. How many customers are we talking about? So for the amount of spectrum that they have now in the network that I’m talking about for $10–$15 billion, you’re not taking 50 percent share overnight. I don’t think that would be that expectation from day one.

But then the theory of telco is that when you do that initial CapEx build, you have your initial spectrum purchases — $10, $20, maybe $30 billion — another $10 or 15 billion in terms of CapEx. If you are successful and you do get that five or 10 million customers, the opportunity to invest more happens. If you go back to the old days when the cable view of wireless was going to be, “We’re going to get these MVNOs. We’re going to drive the wireless companies into the dirt and then we’re just going to buy them.”

That happened in at least one European market, and that was the cable bull thesis that was occurring. You could have the same bull thesis emerge from the SpaceX bulls here where they’re going to say, “We’ll get those first five or 10 million customers. We’ll drive them into the ground. Verizon’s going to be so desperate for any type of revenue because their revenue declined. They’re just going to hand them a wholesale deal and then they’ll start selling spectrum. There’s going to be a spectrum auction with the FCC.”

You can see how the narrative can build based on, “An initial CapEx that’s not that big, get in the market, and then if it’s successful, we start investing more.”

Let’s talk about the terrestrial network for one more turn. I heard you throw a little water on the idea that they’re going to build femtocells. That is what Elon and Gwynne Shotwell have been saying — that they don’t need to build the traditional kind of terrestrial network that AT&T and Verizon and T-Mobile have, where you have a lot of fiber back haul, the big sites that require all kinds of zoning permits and everything. That they can basically just put small cell stations next to Starlink dishes, put them anywhere they want, and blanket the world with them. And Starlink itself will be the backhaul.

I sense some problems with this. Starlink is not 100 percent reliable all the time. If you have a network that is not 100 percent reliable all the time, you’ve got some problems, so maybe you have to backstop it somehow. But you don’t think that’s what they’re doing. You think they’re going to build a regular terrestrial network.

I’m sure that’ll be a part of it, but you need macro towers for that type of coverage and penetration and power. Not to explain physics to SpaceX, they probably know it better than anybody, but what you’ll see is as they talk more about this low-band spectrum that they purchase, when we get on the conference calls of these tower companies, you’re going to find out that you’re going to see a lot of those antennas show up on towers.

It’s just natural. You can talk about femtocells, but it’s hard to see that the network’s going to get built without macro towers.

One of the weirder aspects of the telecom industry, as it’s constituted in the United States right now, is that cell carriers own some of their towers and operate some of their towers. And then there are these crazy third parties that literally have names like TowerCo that operate a bunch of the other towers.

Are those captured? Do you think SpaceX can get deals with those companies, or are they beholden to their big partners?

These are huge real estate investment trusts (REITs). American Tower is the biggest one. It’s probably one of the largest companies in this. When you consider any REITs, there are other companies out there. They have these towers. They have space in many cases where basically SpaceX can just go and get an additional antenna. It’s a lot easier to do that now than when the wireless companies were initially building this stuff and having to erect their own towers.

In addition, EchoStar is going through a bankruptcy. They have a lot of radios that could be used, that could be bought on the cheap, that could expedite SpaceX’s entrance in the market. They haven’t shown interest in that yet. The EchoStar bankruptcy process hasn’t yet concluded, but EchoStar can still be a potential partner here by selling them radios that are already on towers.

You’ve lifted the amount of time. Those radios use the spectrum that SpaceX is purchasing, so it can be a quick fix for them to enter the market. Who knows if they do that? They may have their own view like Masayoshi Son did on how to build this new cheap network.

Is there a way to read this as just they’re slowly buying EchoStar or whatever EchoStar tried to do?

EchoStar has some remaining spectrum that Verizon really needs. At this point, there is some strategic sense to just buy EchoStar outright — because EchoStar is getting stock that was issued to them at a discount. If you’re buying them, you’re effectively buying in your own stock.

You don’t have to issue the cash to the company and you’re getting whatever cash proceeds that EchoStar is getting from some of its spectrum sales. They can actually get incremental cash on the balance sheet and buy their stock in. We’ll see if that plays out. By the way, then you don’t have to also deal with Dish, which sometimes can be challenging.

T-Mobile’s in the mix here. I want to talk about Verizon, you’ve mentioned them several times, but T-Mobile is Starlink’s current partner for direct-to-device cell connectivity. Are they just getting rocked? Are they going to be a part of this? How’s that going to work?

If you think about the start of that, that was former T-Mobile CEO Mike Sievert up on stage with Elon announcing this thing and everyone’s very happy. Then Deutsche Telekom decided it needed a different CEO at some point. You had that transition where Mike retired and you brought in a new CEO, and there might just be a different view on how that relationship works.

I’m guessing that it’s been very frustrating for SpaceX to deal with them and certainly they would probably want to avoid any exclusivities going forward. They may need to if they want to sign one of these wholesale agreements that we talked about before.

It just seems like, as you mentioned, SpaceX and Starlink went after a little bit of the consumer market here. They bought some spectrum. They got a good reaction to it. Now they’re going to go after the whole thing and their existing telecom partner is thrown by the wayside.

If you look at the three big telecoms in the United States, they are circling the wagons. They’re saying this is never going to work. They’re never going to sign the MVNO agreements. They’re putting together their own satellite pool. There’s something here where they are panicked by the existence of meaningful competition in a way that does not usually happen in telecom.

Yeah, I agree with that. I don’t know if it’s SpaceX leaving them or T-Mobile leaving SpaceX, but that relationship which started out so happy with the old CEO is certainly not positive. T-Mobile executives have been throwing shade at SpaceX incessantly over the past couple of months. They formed a joint venture (JV) together.

It reminds me of when fixed wireless first hit the cable market and Chris Winfrey talked about it derisively as “cell phone internet” and played it down. Ultimately, that’s what’s really bit them and why cable stocks are in the position they’re in today, given the amount of customers that they’re losing to cell phone internet.

There are some similarities now in terms of how these executives are downplaying what they can do. Is it going to be costly? Is it going to be complex? Sure. But so is Terafab and so are so many other things. So is making an autonomous vehicle or catching a rocket with chopsticks. That’s the reality that they have to deal with. Investors have seen what this management team has done before in other areas and are just applying it here. Whether that’s fair or not, time will tell.

I’m actually very curious about that because I know you cover the company and I know you cover the industry. There’s some part of SpaceX that is just a meme stock. People love Elon. There’s some part of Tesla where it’s not valued like a car company, it’s valued like a software company, even though it is very much a car company. We’ve yet to see where the software multiples might come from for Tesla.

The same is true of SpaceX: huge IPO, but people are buying the physics miracle of the rockets launching and landing. They’re buying the promise of Mars. They’re buying the promise of AI, whatever that promise is, however frothy that market is. Those are valued against hopes and dreams.

Telecom is not. It’s well known. You can be a telecom analyst and you can examine the value of the spectrum. You understand the build-outs. The customers are not confusing. Consumers are going to pay some amount of money. There are other competitors that are built in at scale. Why do you think SpaceX would chain itself to a business that is easy to value when all of its other businesses are their dreams? You can’t value dreams. It’s just whatever is the biggest number.

I don’t think it’s an either-or. When you look at people’s attempts to justify the valuation of SpaceX, a lot of that value is going to land on data centers in space and the data centers on the ground. That’s where a lot of the value is in Starlink.

But that’s not the launch business, which theoretically is their business. It’s not even the AI provision business. We’re describing them as a hyperscaler.

Yeah, exactly. The AI and those are other big chunks of it. There are a lot of different stories here, but it doesn’t mean that they don’t pursue this if they have connectivity and constellations. They’re talking about connectivity in space because they believe that there’s going to be a demand for connectivity between the data centers, whether it’s theirs or others and their constellations. There are already data centers that I think are using their constellation to connect.

When they looked at it, it was just another part of the narrative that you build in terms of SpaceX and justifying the valuation. Because what do all of these things need? Whether it’s robotaxis, whether it’s data centers in space, they need money and money needs a narrative. This is just another one of the narratives to stack on top to say, “Here’s how we can drive incremental value.”

The value, if you look at the enterprise values of these telcos in the United States, you’re talking about a trillion dollars. That’s a trillion dollars of enterprise value. They’re obviously not going to capture a trillion dollars because part of it is shrinking the telcos down at the same time as getting whatever that stake is and the CapEx related to it.

The fair question is, if capital gets more scarce, how do you allocate between these different things? Don’t you want to push Terafab forward a little bit more or get those terrestrial data centers built so that you can start monetizing the billions of dollars that you’re getting there versus diverting whatever the dollars are here for the telco?

That is a reasonable thing. The problem for the telcos is even if that’s happening at SpaceX and this gets delayed a year, that doesn’t help them. The overhang of when that’s going to occur — whether that’s a year, two years, three years — is always going to be there. They’re not going to say, “We’re just giving up on going after this.” It’s just going to be a capital allocation issue in the near term that’s going to delay when the actual impact hits the telcos in the United States.

How much of this is just that Elon needs to supply connectivity to his own cars and his own factories and his own robots and he’ll just be his own best customer?

I don’t think that’s it. They think they really want to build a revenue business out of it. In fact, they’re going to use the cars as hotspots where they’ll put Starlinks on there and then use them as distribution points. That’s going to be part of the play.

I do want to end by talking about the existing telcos and what competition might do to them because I think that’s a fascinating dynamic. They are clearly not ready for an actual aggressive competitor.

But I want to stick with what you just said for a minute. If I pull that apart, it sounds like what you’re describing is the reality of the SpaceX business, which is that Starlink is the thing that makes profits. Everything else is incinerating money, but investors seem happy with that because the potential payoffs might be huge.

If you take the Starlink profits, you have to make a decision about whether to reinvest them into Starlink, and now Starlink’s mobile business, or into AI or into the launch business or into going to Mars. Regardless of how that allocation happens on what timeline, at some point, enough money will go back into Starlink Mobile to pose a real threat to AT&T, Verizon, and T-Mobile, and that is just a matter of time.

You nailed it, and that is the issue. Capital becomes the biggest benefactor right now to the telecom companies. How does that capital get allocated? That’s in terms of reportive results. They’re 100 percent right on that. But in terms of the stocks, that concern is not going to go away because there will be incremental data points. Maybe one of these telcos has a problematic quarter or two. These are not founder CEOs where they have to do something quickly.

It’s easy to get a lot of wholesale revenue on the books by doing a deal with SpaceX. These are the types of things that they’re going to have to deal with in terms of that long-term risk. Cable’s got this. Look at Uber. Uber’s got the same issue. The threat of Waymo and robotaxis is what keeps that stock where it is.

Waymo with their 3,000 or 4,000 cars are obviously not impacting the two million drivers that Uber has in the United States. But the threat of where Waymo’s going to be two years from now, or three years from now, or the threat from Tesla’s robotaxis… that’s what investors care about and that’s going to obviously impact these companies.

Put that in the context of SpaceX being a public company for me. Is it just that we’re going to get next quarter’s results of SpaceX and we’re going to see that xAI is still burning money at enormous rates, but Starlink Mobile made a little bit more money? And that’s going to keep everybody happy for a minute?

I don’t know. I don’t think we have enough history yet in terms of what moves SpaceX stocks one way or another. To your point, you have a lot of believers, regardless of what’s printed, who are always going to say, “Who cares about this quarter?” Tesla’s got the same issue. Who cares how many cars that they actually sell because it’s all about the robotaxis and the robotaxi business is about to start scaling.

Those very positive people won’t care. Then there are going to be the negative people who, no matter how much traction you see them get in, whether it’s Starlink or progress on the build of space compute, are going to say, “He’s never going to deliver. This is never going to happen.” You’re just going to have those fighting battles back and forth.

The primary issue is going to be whether they can raise capital off of that. And in what ways? Because if you’re burning cash, at some point you need to bring in cash. If these businesses aren’t generating enough cash because you’re consuming it with the other growth initiatives, you still have to figure out ways to continue to issue cash or issue stock to get more cash on the balance sheet.

If I was going to offer that most cynical read, I would say the only business where they can see expanding the service will result in more profits to offset their losses elsewhere is Starlink. They don’t have another business that looks like that.

Just to be clear, Starlink is the broadband business that’s generating the cash flow. This mobile business would be cash negative initially before you get into that positive cash position. You have to look at the robotaxi business, there’s going to be a lot of CapEx initially, but these cars are pretty cheap. That theoretically could be a cash generator.

But that’s a different company.

But we know that, just like I mentioned earlier, it could make buying EchoStar make sense because you’re buying effectively cash in your own stock on the cheap. There are different ways to put cash obviously on the balance sheet in $10 or $20 billion chunks.

Obviously the structure of these companies — they’re all Elon’s companies in the end, and he’s managed them as closely as anyone can manage big public companies. But to make it as dumb as possible, say you have a dollar and if Gwynne Shotwell has a dollar and she wants to light the dollar on fire, she’ll put it in xAI against some return somewhere that might be $50 trillion total addressable market (TAM) or whatever their prospectus said.

Or you could put the dollar into Starlink Mobile in the build-out and you will probably return $1.10. That is what that business looks like because they will get some customers away from AT&T and Verizon. They’re already running that thing profitably.

The idea that they need to show some return somewhere, it feels like that’s why they’re making this move. Not because it makes the most financial sense, it just makes the most financial sense in the context of SpaceX.

You may be right. The problem with that belief is that it’s going to take time for them to get that dollar of profit out of the mobile business. They still have to build the network. They still have to sign up customers. You’re going to be negative EBITDA for a while. If you have two different businesses and you think the returns are significantly higher or more interesting to your investors to get to that next catalyst for space compute or Optimus or whatever it is, that is going to play a role.

What does Elon happen to care about the most at that moment? What is more interesting to him to do? Isn’t space compute a little bit more interesting to allocate those dollars than taking some mobile customers from AT&T?

Although the man’s addicted to his phone and I bet he hates seeing that AT&T logo in the corner. There’s just a part of that that’s always with these guys.

Let’s talk about the existing telecoms. They do seem a bit panicked. For a time, they were juggernauts. These were unstoppable businesses as mobile was growing. They poured a bunch of money into the 5G transition.

I’ve described the telecom industry as a bunch of lobbyists. Boy, did the lobbyists win the 5G transition. Boy, did they collect all the favors and all the capital they could to build out these networks and then reality hit them in the face. We beat China to some kind of network and then the thing that we were supposed to win did not happen.

Now we’re doing it again with AI, but that’s a different conversation. But that was the narrative with 5G: If we didn’t beat China to 5G, something. Who knows what, but we got to cut all the corners to build this network and spend all the money. It just didn’t pay off.

You’re an analyst, you’re in the trades. I skim the trades and boy are all these CEOs saying, “We’ve got to generate some revenue with these networks now.” You mentioned Mike Sievert is gone, the old CEO of Verizon’s gone. It just didn’t pay off for these guys.

Yeah, 5G didn’t deliver. Some of the promises were BS from the beginning. You talked about this earlier regarding autonomous cars. You’re not going to rely on the network to make that millimeter-second decision of whether you’re going to hit the car in front of you or not. Remote surgery, even if that was a thing, how is that a scalable business where you’re generating hundreds of billions of dollars of revenue?

These were all silly. Sievert used to be the guy saying, “People would say the same thing about LTE, there’s no application.” That was not even true. If you remember, the application was video and we knew that LTE was going to enable video and that’s exactly what happened.

You’re 100 percent right. This was just a way for them to get more spectrum because they were going to still have data growth on their networks. Capturing more spectrum to be able to handle the existing growth, and that’s cheaper to get spectrum, even at tens of billions of dollars, than it is to try and build the network for that capacity.

If they had just said, “We’re going to spend all this money and at the end of it, tens of thousands of people will be able to livestream Taylor Swift during the Eras tour on every one of those stops,” Americans would have said, “Go, go faster. Yes, we understand what that is.”

That is truly the thing they enabled. It’s very cool. It’s millimeter wave in stadiums and that’s cool. I don’t know if there’s another one. That said, they are on their back foot. They did spend a lot of money. This is around the time when, in my history as a journalist, they would start talking about 6G, and they want to, but they know they shouldn’t, so they don’t.

They’re having the meetings. They are certainly not as loud about the next round of investment as they would normally be in the cycle. Now they have a competitor. Your analysis is that Verizon is by far the weakest here. They have the most to lose. Explain why that is.

One other thing to mention is you have a very active FCC chair that would like to raise, and put on his resume, $100 billion from spectrum auction. You’re right, they’re going to talk about 6G again and have to come up with some type of revenue stream to justify getting this money. It’s going to be a lot harder though. They’re already pretty levered. They’ve got a new competitor.

In terms of Verizon, the issue is that AT&T has seen this thing developing for some time. They’ve built a fiber network. There’s only so much that wireless can do where a fiber network is ultimately your best connection. If you think about customers that own fiber and wireless, very high-value, very low-churn customers. That’s been their strategy. They’re plodding along. They’re going to get their two or three percent revenue growth and just pay their dividend and do their thing. That is the standard telco.

T-Mobile didn’t have that. They’ve got the dynamics — a lot of politics right now between Deutsche Telekom wanting to own it and not wanting to pay a high price and how that all plays out. Verizon just made a lot of bad strategic bets on spectrum. Obviously, AT&T had their own issues, but at least they got out of DirecTV and Warner quick enough and turned the ship.

But Verizon bought millimeter wave spectrum when they could have bought EchoStar and bought spectrum… even now they’re spectrum-constrained compared to their competitors and they need to go out and spend $10–$15 billion on the EchoStar spectrum. You have a new CEO in there who is not really a telco guy who’s just doing his thing, saying, “We’re just going to cut costs.” The EBITDA is going to look good because they’re just firing a bunch of people and there’s going to be a result.

There is going to be an impact of firing that many people in the organization. It may appease investors to make the EBITDA look good for the next couple of quarters. But at some point you have to show and have a strategy for some type of revenue growth. What is Verizon’s differentiation in the market right now? They have none. They’re the most in the crosshairs of where SpaceX and even the cable companies can continue to eat away at those customers.

That is surprising to me. It’s just my own history. I grew up in the midwest. I went to college in the midwest. That was Cingular territory and it became AT&T. When I moved to New York in 2010, Verizon was the gold standard network in the Northeast. It was the one everyone had. It cost the most money because it was the best network. The iPhone coming to Verizon a couple of years later was a huge deal.

Verizon’s network was so powerful at that time that they could try to force the Blackberry Storm down people’s throats. They were confident enough that their network was the thing holding people to them, that that was a worthwhile strategy. Obviously, it didn’t work. They made the wrong bet. You’re saying they made the wrong bet on millimeter wave. They made the wrong bet on other spectrum acquisitions. The one that I’m not quite tracking is media.

They did buy a bunch of dumb stuff. At one point they owned Tumblr, which is just one of the most confusing media outcomes of all time. But that stuff was all cheaper and easier for them to flip or shut down than AT&T buying all of Time Warner and putting out a 4:3 black-and-white Justice League movie. How did AT&T survive that? But you’re saying Verizon can’t survive owning Yahoo?

That’s a fair pushback, in that the media impact to Verizon was a lot less than AT&T. But these again were separate businesses. Obviously, it was a capital allocation issue for a period of years.

But the decisions on the spectrum front and the competitive front, and T-Mobile’s impact, John Legere’s impact in taking away the claim of having the best network, left them in a spot where they basically said, “We’ll just keep increasing price on our customers and we’ll get that 2 or 3 percent revenue growth.” And they just lost the narrative of what they meant to customers. I don’t really think under the new CEO that’s been regained.

Do you think their ability to say they have the best network is just gone?

That’s completely gone. That’s the crazy thing about this. The networks are effectively commoditized. These networks are basically the same. And they’re getting 60 percent margins.

That’s the whole thing with Dish Wireless — even if it wasn’t on their network and you guys tested it, it wasn’t on their network, you could have been buying AT&T’s network at half price. It’s crazy the average revenue per user (ARPU) and the margins that these guys get for what is effectively a commoditized market. That’s why the AT&T strategy is interesting because at least they’re trying to bundle that with a high-value fiber network. But for the other guys, it’s just commoditized wireless.

I would actually say the other strategic mistake Verizon made along the way was they got away from Fios. They decided it wasn’t worthwhile. It seems like they’re trying to reinvest in that now and go after that AT&T strategy.

Given their lack of spectrum, they can only take fixed wireless so far. You’re right. I wouldn’t be surprised if they got back to investing in fiber. The difference, obviously, with Fios is that you have union issues and a lot of cost structure issues that they were dealing with.

But the pivot to doing more fiber and perhaps laying off the fixed wireless, which is straining the network, is probably the right decision for them and what you’ll see happen going forward.

I want to end on just a big picture question here. We have covered so many crazy telecom mergers and it always feels like the right answer is to put more competition in the system.

We’ve mentioned John Legere several times in this conversation. He only got that job and T-Mobile only got to exist the way it does because AT&T was prevented from buying T-Mobile. They paid a breakup fee, which subsidized a huge portion of that early growth and those early strategic moves that Legere was able to make.

But that was good for the market. Consumers got a CEO who tried to change the market and have better customer experiences, reinvested that money in the network. That was good. The existence of Dish Network is T-Mobile trying to buy Sprint and instead of blocking the deal, we imposed some wild structural remedies and Makan Delrahim, who ran antitrust in the first Trump administration, rightly or wrongly engineered the outcome of Dish Network existing.

That was Delrahim’s preferred outcome: “We’re going to let this happen, but we need to have four carriers. Charlie Ergen is my guy. We were going to stand up a fourth one.” From my perspective, it just seemed obvious that he was never going to do that. And he didn’t.

Maybe I was correct to make that bet, but it just seemed obvious that Dish Network was going to hold onto a bunch of spectrum, watch the prices rise and then flip it when it turned out they never built their network. They had to hit targets with the FCC that they just weren’t hitting over time. Now, we have a true fourth competitor, or at least an aggressive competitor of the market in Elon, who’s probably going to try to actually do this thing and these companies are running scared.

Is this just evidence that we should have four carriers in the United States? And that when inevitably Verizon tries to buy T-Mobile, we should just say, no, the right answer is four and we’re not going to go to three again.

Under Chairman Wheeler, which goes way back, four was the number.

Wheels and I were buds.

If you called him now, he’d say, “I told you it should have been four and it’s going to go back there.” Obviously, in the new administration, they didn’t believe that that was the case. You see Chairman Carr pointing to prices, how he sees them being down and the competition that’s happened in fixed wireless.

But you always want more competition in a market. It drives innovation and it lowers prices and margins are approaching 60 percent in the wireless business. I can’t say we’ve had a tremendous amount of innovation, which gets back to what the telcos are doing in fear by refusing to give SpaceX a wholesale agreement.

That’s their right. But at some point, if the FCC’s mandate is to act in the public interest, we have a current administration — and who knows who gets in during the next administration — but if these telcos are going to push back so hard on what the fourth competitor, in this case SpaceX, is going to do, the FCC can probably get involved in some ways. That is the risk that they run by being so vocally against Elon Musk in the market.

You talk about the ultimate consolidation. It’s funny. We should save all these quotes now where they’re saying, “Elon can’t be a competitor because he only has 80 MHz of spectrum.” Because then when they want to merge with someone, they’re going to claim, “No, he’s actually a competitor.” They’re going to deny that as a competitive threat.

There’s nothing funnier than a giant telecom insisting that a thing that is not a competitor is their competitor. They all do it.

Last question. Again, this is just the big think rattling around my head. We might be on a cusp of an entire paradigm shift in what mobile devices even are. If you look at Meta, they’re going to put up the Muse charm and maybe we’re all going to talk to little cartoon AIs all day that run agents in a data center. Our use of mobile bandwidth to watch video will go down because we’re not even carrying phones anymore. Is that a risk here? Is anybody thinking about this?

We think about this every day at LightShed, in terms of all the different ways that AI [exists] and how we interact with our information and how we interact with commerce and using agents. Muse has obviously been something we’ve been waiting for from someone and there’s going to be other versions of that. But you’re right. It could decrease [phone usage], and it’s an Apple risk.

It decreases the importance of the status of holding an iPhone if you’re just not interacting with your data in the same way. If that happens, that whole paradigm in terms of the telcos and providing the subsidies changes. Whenever there’s change, there’s an opportunity for disruption and for margins to be contracted. It does change things and maybe SpaceX could play.

Elon’s been asked about making a device. I know Qualcomm, when you meet with those guys, says, “We have 40 different guys out there making devices.” I don’t think he’s going to add one more thing to his list, but again, let’s get back to what we’ve talked about during this podcast and narrative.

Will Terafab happen? Will data centers in space happen? It may not happen, but you can maybe talk about building a phone and then that becomes one more issue that the telcos have to deal with in terms of dealing with their customers. Why am I using this iPhone when I should be using this completely different device, whether it’s coming from OpenAI or Anthropic or maybe SpaceX?

The idea of Elon shipping a mid-range Android phone with the Play Store on it is so deeply funny to me. I truly hope it happens because that’s the product you can make today. Maybe there’s a paradigm shift and there’s a different set of products.

But right now you need to have Instagram and there’s really only one path to getting Instagram, which is shipping an Android phone with the Play Store on it. We just saw Amazon essentially capitulate with their new tablets.

If you’re focused on the future, you have to concede to the present. I truly do not believe we will see a mid-range Android phone from SpaceX. But you’re saying they might start talking about it.

No, I agree with you. I’m just saying when you’re trying to build narratives, why not throw that in the hopper? The bigger issue is someone’s going to build something that may resonate with… We’ve gone a long time. We’re spending $1,000 for these phones that are giving us some basic swipe functionality. They’re going to change in terms of how you use them.

This is a bigger and more obvious issue for Apple than anybody else, but it does change how the telcos are going to act and the role that they’re going to play and where that margin should be. They gave up a lot of value to Apple at some point during this continuum of the wireless industry. We’re going through another paradigm change, so we’ll see how those value splits play out.

Walter, we’re going to have to have you back soon because it feels like these things are going to happen fast. I was very happy to nerd out about telecom with you. Thanks for being on Decoder.

I appreciate it. Thank you.

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It's been a couple of days since Apple's big smart home announcement, and we have some more information - and a bunch of new questions - about the Apple HomeView. The device has plenty of computing oomph, is always connected to power, and looks like a perfect place to run a bunch of apps. And yet the HomeView is relying almost entirely on CarPlay. What gives here?

On this episode of The Vergecast, David and Nilay try to make sense of the HomeView's app situation, and why Apple would choose not to make its home hub into its own app platform. After that, they talk about the latest Gemini model and whether building the best model matters if yo …

Read the full story at The Verge.