Meta Shifts the Blame + Do Data Center Bans Work? + The Final HatGPT

Meta negotiated an unusual provision in their landmark settlement: If TikTok and YouTube also agree to penalties and changes to their products, Meta will pay more.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Companies are pouring money into AI, but few leaders can explain how those AI investments work with the systems you already have. You know, the ones that actually run your business. Without systems, you don't have to start over with AI. You can choose the projects where AI will have the most impact. And Outsystems gives you the platform to make it agentic on your terms with complete control every step of the way. So you can trust AI with the mission critical systems that run your business. Own your agentic future. Learn more at outsystems.com/NYT. That's outsystems.com/NYT.

• 0:36Kevin Roose?

  Now, I thought you were going to bring up another story which happened last night, which is so you and I last night are having drinks with, let's say, a very fancy technology person.

• 0:46Casey Newton?

  Yeah, a legend even.

• 0:47Kevin Roose?

  A legend. And we're sitting there at this like very small table at the restaurant, very nice restaurant. And all of a sudden, you just do like a Mr. Bean, like spill all an entire glass of wine on yourself. And you revert like you are not a clumsy person, but you are like tall.

• 1:07Casey Newton?

  Yeah.

• 1:07Kevin Roose?

  Which often leads to you just like sort of flailing your limbs around. So you are like trying to clean up the wine on yourself while also like making a joke about how you just got so excited talking about the future of media that you like spilled your wine on yourself.

• 1:21Casey Newton?

  Kevin, it was so horrible. And you have to keep in mind, like Kevin and I don't even drink anymore. Okay. But all of a sudden, there's some very good wine being poured in front of us and our guests are drinking wine. And I just had the feeling of like, this is going to be one of those times where I have a glass of wine.

• 1:36Kevin Roose?

  Yeah.

• 1:36Casey Newton?

  And how does my body repay me by almost immediately spilling half a glass of what I believe was a very nice Chardonnay all over my shirt? So I don't know how our, you know, guest received what I did, but I was very embarrassed.

• 1:52Kevin Roose?

  I thought it was charming because I, you know, you're so composed. And it was just a moment where you turned into Mr. Bean for 30 seconds and I appreciated that.

• 2:01Casey Newton?

  I was flailing, bro.

• 2:08Kevin Roose?

  I'm Kevin Roos, a tech columnist at The New York Times.

• 2:10Casey Newton?

  I'm Casey Noon from Platformer.

• 2:11Kevin Roose?

  And this is Art Borg.

• 2:12Casey Newton?

  This week, Meta agrees to a $17 billion settlement over child safety. Why they caved and what it means for social media. Then Princeton computer science professor Arvind Narayanan returns to the show to share his thoughts on why banning data centers won't slow AI progress. And finally, it's all hats on deck for the final at GPT.

• 2:39Kevin Roose?

  Well, Casey, we got some big news just before we started recording today, which is that Meta has settled its big multi-state lawsuit with all of the attorneys generals. Attorneys generals.

• 2:53Casey Newton?

  Attorneys generals.

• 2:54Kevin Roose?

  I always mess that up.

• 2:59Kevin Roose?

  They have agreed to pay up to $17.1 billion and make a series of changes to their platforms. This is a big deal.

• 3:09Casey Newton?

  It is a really big deal. This is a case that has, that I have been following since it was filed in 2023. Initially, you can go back and read the first thing I wrote about it, which is that I didn't think that the, the case as filed looked all that compelling. But then Kevin, an unredacted version of the suit came out and I thought, oh, this company is in trouble. And indeed, fast forward to today, and this is the largest settlement that Meta has ever agreed to. And one of the biggest probably in the history of tech.

• 3:38Kevin Roose?

  Yeah, I think so. So let's talk about the, the actual suit because there have been so many of these kind of lawsuits going around that it can be hard to keep all of them straight. This is not the New Mexico case from back in March where Meta was ordered to pay a bunch of money over various child safety violations. This is sort of the big omnibus multi-state lawsuit and investigation.

• 3:59Casey Newton?

  Forty-seven states plus DC and US territories. The cases are related in that they're both about child safety. And while that New Mexico case was really important, the jury there only ordered Meta to pay 375 million for child safety violations, although the judge later did tack on an additional 567 million. But this one is just orders of magnitude larger. And there were really two major things at issue here, Kevin. One was just a straightforward violation of a law that is supposed to prohibit companies like Meta from collecting information about children younger than 13 without their parents' permission.

• 4:41Casey Newton?

  We talk all the time on the show about how we have very few privacy protections in this country, but this is one we do have. You cannot collect data about a 12-year-old without getting their parents' permission. And so what Meta did for a long time was they just said, well, you can't join unless you're 13. But the thing that was in that unredacted version of the lawsuit was just tons and tons of evidence that Meta absolutely knew that millions of kids under 13 were using the platform. They were not asking for their parents' permission. And so that's what I wrote in my column. I think the AGs have Meta dead to rights here. And I think it was a major reason that this case was settled.

• 5:15Kevin Roose?

  And this one was settled, like I guess Adam Mosseri, the head of Instagram, had already testified. Mark Zuckerberg was expected to testify, but before that happened, the lawyers kind of got in there and struck the deal.

• 5:26Casey Newton?

  That's right. And that leads into the second set of issues that were under consideration here, which were just all of the things that Meta does to get you to pick up your phone and look at Facebook and Instagram as many times a day as it humanly can.

• 5:41Kevin Roose?

  Right, the addictive features.

• 5:42Casey Newton?

  Yeah, so you know, what do we mean by that? Well, the fact that they're sending push notifications at all hours of the day or night, that they're using ranking algorithms to try to show you the absolute most enticing material. The fact that they're not enforcing any real screen time limits. So there was just a litany of things that the company was doing to try to get teens to look at it as much as possible. The AGs came in and they said, hey, this is actually just addiction that you're trying to create here. And Meta said, well, I guess we're not going to fight that one anymore.

• 6:15Kevin Roose?

  Yeah, so the financial settlement here is significant. Around $12 billion is what Meta will be required to pay initially. And, you know, for Meta, that's, that's real money. It's not like all of their money. They'll be, you know, they'll be fine. They can sort of amortize that over a multi-year period.

• 6:31Casey Newton?

  Not only that.

• 6:32Kevin Roose?

  Right away.

• 6:33Casey Newton?

  Not only that, Kevin, but there was reporting from Jeff Horowitz in Reuters several months ago that Meta expected that it would make about $10 billion in ads related to scams this year. So they will unfortunately have to give up all of their scam money to pay for this settlement.

• 6:49Kevin Roose?

  Yeah, just move the scam budget over to the settlement budget and it basically nets out.

• 6:54Casey Newton?

  Yeah.

• 6:55Kevin Roose?

  But there's this additional wrinkle, which is that the settlement dollars will go up to roughly $17 billion if TikTok and YouTube also settle and agree to penalties and changes to their products. So what is going on here?

• 7:08Casey Newton?

  So the basic logic is like, hey, don't make us unilaterally disarm in the war for teenagers' attention. Right? Like, why do we have to do the responsible thing if these other guys don't have to as well? So what we're going to do, Kevin, is we're going to hold America's teenagers hostage. And we're going to say, we're not actually going to give them the safest experience possible unless these other guys do too. And they are, of course, presenting this as industry leadership in creating a new safety standard for teenagers.

• 7:37Kevin Roose?

  Yes, I love the way they're spinning this. Have you seen the full page ad?

• 7:40Casey Newton?

  No.

• 7:41Kevin Roose?

  So Meta is, according to Mike Isaac, my colleague at The Times, Meta is preparing to release a full page ad, an open letter in the country's major newspapers this week, calling for TikTok and YouTube to, quote, "Join us in supporting teens."

• 8:01Kevin Roose?

  Says, basically, you know, we, all platforms should empower parents and support teens in these ways because we know that when teens are restricted on one app, they simply move to another. So basically, they are worried that if they have to sort of unilaterally disarm and implement these new features, which we'll talk about in a second, into their apps, teenagers will just go to TikTok and YouTube instead.

• 8:24Casey Newton?

  Yeah, and I mean, look, like, is that narrowly true? Yes, but please do not wait until truly the last possible second to do the bare minimum, effectively at gunpoint from 47 attorneys general, and then say, we're excited to announce our new leadership position in teen safety. Like, the depth of cynicism in this approach is breathtaking to me, even as a person who's covered this company for a really long time.

• 8:50Kevin Roose?

  Yes. So let's talk about the product changes that are being required as part of this settlement. What is Meta being forced to do or implement?

• 9:01Casey Newton?

  So it is a bunch of things, and I will just hit some of the highlights. A big one is that there is now a default two-hour time limit that is cumulative across both Facebook and Instagram. So your teen will be able to spend a mere two hours a day browsing the feed. There will also be a default block on its apps between midnight and 6:00 AM. So your teen will not be able to like post to their feed or look at stories during that time when presumably they should be asleep. And also, for the first time, Kevin, they will now mute push notifications between 8:00 AM and 3:00 PM because of course, for the past decade plus, they have been continuously

• 9:44Casey Newton?

  interrupting children at school to try to get them to look at Instagram.

• 9:47Kevin Roose?

  But Casey.

• 9:48Casey Newton?

  They're not going to do that anymore.

• 9:48Kevin Roose?

  How am I supposed to chat with my Nancy, nasty Nancy AI chatbot during high school chemistry class?

• 9:54Casey Newton?

  Here's the great news, Kevin. Direct messages have been exempted from this plan.

• 9:58Kevin Roose?

  Oh, good.

• 9:58Casey Newton?

  So you can continue to get push notifications about all your Instagram DMs while you're trying to learn calculus. A few more changes to mention. They will finally hide the like count on Instagram posts by default. So there has been research here that seems to show that this, this may have some modest mental health benefit to teenagers. They're also going to disable some, what they call extreme makeup filters. I would love to know how much makeup you have to be wearing for it to be considered

• 10:30Kevin Roose?

  Like the Juggalo filters?

• 10:31Casey Newton?

  Yes, exactly.

• 10:33Kevin Roose?

  How much makeup are we talking here?

• 10:35Casey Newton?

  When a teenager puts on a Juggalo makeup filter, Kevin, it gives them a sort of illusions of beauty that they may not be able to realize in real life.

• 10:45Kevin Roose?

  You can't unsee that.

• 10:46Casey Newton?

  You can't unsee that. So those are the big ones. One other unbelievable change to mention, you know, I said before that Meta is holding America's teenagers hostage based on what TikTok and YouTube do here. So there's another provision, which is that if TikTok and YouTube will agree to Meta's terms, that Meta will reduce the daily limit for Facebook and Instagram to one hour and to expand night mode hours to 10:00 PM to 7:00 AM, which will be up from midnight to 6:00 AM. So Meta is basically saying like, look, it would be a real shame if something happened to the children of this country, but you have a way out. Simply agree to

• 11:30Casey Newton?

  our terms and then we will expand these hours.

• 11:34Kevin Roose?

  It's a really interesting bit of like game theory now. Like if you're TikTok or YouTube and you're looking at this, I imagine that you are saying, well, obviously we're not going to like join you in your like, you know, your court mandated or settlement mandated changes because unlike you, we are better for kids. I can imagine especially YouTube pushing back on that. They have always insisted like, we are not social media. We are more like TV. We are like, we are not doing the kinds of like addictive and predatory things that some of these other apps are doing. Their educational uses of YouTube, a lot of, you know, a lot of schools use YouTube in the classroom. Like clearly this is a different thing than like Instagram or Facebook. I imagine that TikTok will have their own view on why they are different than either of these platforms

• 12:18Kevin Roose?

  too. But like, what do you think those other platforms, Meta's main competitors, will or should do in response to this sort of weird hostage situation?

• 12:27Casey Newton?

  I actually assume that they probably will adopt these standards because we now know that if they don't, they might have to go sign their own $17 billion settlement. So I suspect that Meta believes that these things are actually coming and this will now be a talking point so that if and when TikTok and YouTube do commit to these things, Meta will go out and say, we led the industry in calling for new standards and we got our peers to adopt these standards which we set. So that is sort of the next wave of cynicism that I'm expecting here.

• 12:55Kevin Roose?

  And we did it totally voluntarily with no court requiring us and no threat of, you know, many billions of dollars in penalties if we didn't.

• 13:04Casey Newton?

  You know, I was going back to read, read my first column about this when the case was originally filed and Meta had a comment that said something to the effect of, you know, we're disappointed that the state AGs didn't work with us on something more constructive and instead pursued this series of changes. I'm looking at this. I'm like, this seems pretty constructive to me. It seems like we got a lot further than we did just waiting for Meta to adopt some new standards.

• 13:24Kevin Roose?

  I think that the product changes are a lot bigger deal than the, than the financial piece of the settlement here. It is really like the, these are not sort of cosmetic tweaks around the edges. It will require like, it will make for a much different experience for a teenage user of Instagram or Facebook.

• 13:42Casey Newton?

  It will. But even, you know, even that said, and I do agree with you, Kevin, I think it's important to remember that more and more democracies around the world are just banning these apps for teenagers, period. And so that is the real alternative that Meta is staring down the barrel of here. And it is willing to go, you know, pretty far by its limited standards to try to avoid the fate that it is now facing around the world.

• 14:04Kevin Roose?

  Yeah. And so do you think this actually is going to change the sort of mental health picture for teens? Like if you had to guess, are these the kinds of changes that actually do make social media healthier for, for kids? Or is this just kind of a company doing the bare minimum is it is required to do to at least stay out of bigger trouble?

• 14:25Casey Newton?

  Well, at the, at the risk of overusing an analogy, Kevin, I do think that cigarettes are relevant here in the sense that the way that we gradually got people to stop smoking was by just making it a little harder and a little worse experience over a long period of time. Right? The price of those cigarettes kept going up. The number of places that you could smoke kept going down and the amount of information about the negative health benefits just kind of continued to permeate the environment. And eventually most people said, you know what? I don't think this is for me. I think we are going to see a similar thing here where it's just going to get a little bit harder all the time for kids to use social media. They're going to continue to hear about all of the terrible outcomes

• 15:09Casey Newton?

  that, you know, lots of teens are having on these apps. And over time, they're just going to sort of move into safer and different spaces.

• 15:15Kevin Roose?

  Yeah, they'll start vaping instead or whatever, whatever the social media.

• 15:19Casey Newton?

  They'll be over on Cali, turning their allowance money into less allowance money.

• 15:24Kevin Roose?

  I realize that sounds very cynical, but I do feel like there is some parallel here with the cigarette industry because they had this massive multi-state settlement back in 1998. And out of that came this sort of regime of like, you have to put, you know, you have to, you can't advertise cigarettes in certain places. And I think what really moved the needle on smoking was not any of those things. It was like, as you said, it was sort of this, the cultural milieu and the like, the fact that there just weren't smoking sections in restaurants anymore. And like the sort of vibe shift of smoking in culture. And so I wonder if what you're saying is like, this is, this is an important symbolic step and, you know, making the apps a little less addictive will mean that sort

• 16:07Kevin Roose?

  of teens have some distance to say like, wait a minute, do I like what this is doing to me and my friends? But that it might actually be some of these cultural factors that end up making more of a difference when it comes to use of social media.

• 16:19Casey Newton?

  That's what I think. And look, I mean, there are limits here. You know, I think that people are going to continue to watch a lot of short form video. You know, I don't yet see an off ramp from that particular phenomenon. But some of the, you know, other mechanisms here, I do think will just make social media a little bit less fun to use. And, you know, maybe that will actually result in teens using it less.

• 16:42Kevin Roose?

  Yeah. What does this say about Meta as a company that they are making the settlement now and that they are going to make these changes?

• 16:48Casey Newton?

  I think they realized that the state AGs had them dead to rights on some of this stuff. This was an interesting case in that it was going to be decided by one person, which is this judge, Yvonne Gonzalez Rogers. And she has a reputation for being really tough. And I think they listened to the first few days of testimony. They were looking at all of the lawsuits that they had already lost recently on similar subjects. And they estimated that the fallout from this could be over a trillion dollars, like getting close to their, their total market capitalization as a company. So this case truly was too dangerous for Meta to pursue all the way to the end.

• 17:26Kevin Roose?

  Yeah. I mean, I'm, I'm also curious if you think this will have sort of knock on effects for them as a company. I'm thinking about like the Microsoft antitrust investigations of several decades ago. And one of the sort of conventional, you know, narratives that came out of that was that all of the, the antitrust investigations and the justice department and the trial and like all of this had a, an effect on Microsoft, not because, you know, the breakup was reversed on appeal, but it was like so distracting and it took away so many executives' attention at a time when things were shifting under their feet. And everything just became very cautious and there were lawyers in every meeting and like they missed the, the, you know, the platform shift to mobile. They missed,

• 18:10Kevin Roose?

  they missed search because they were just so tied up in all of this expensive and distracting litigation. So I'm curious if you think there's any parallel to Meta here and just the amount of time and energy that this company is now having to spend defending itself in these lawsuits.

• 18:25Casey Newton?

  It's a good question. That is a story that the people at Meta know very well. And this has always been a very paranoid company. They have always assumed and have lectured their employees about how likely it is that they will get outcompeted in the marketplace. And so truly they think about this constantly. And I think you have seen them react by shifting all of the resources that they did to AI. Look at how this company talks about itself. They do not talk about a bright, bold future for Facebook and Instagram and connecting the world. Right? I mean, they, you know, they'll make noises about creators here and there where it's useful. But when you look at what this company says it's doing, it's building super intelligence. It's releasing a Mac app that like plugs into your calendar to do work for you. Like this company's public posture is that it

• 19:09Casey Newton?

  is running away from its own products to build something completely different. That tells you a lot about what it thinks about the stuff it's already built.

• 19:15Kevin Roose?

  Yeah. I wanted to bring up this other Meta story that came out today, which I thought was fascinating on a very different topic. Katie Paul, the great reporter over Reuters, has a story about Meta's attempts to overhaul its workforce. Basically, Mark Zuckerberg and his lieutenants have been plotting for months now to sort of tear up the org chart at Meta and replace these sort of like big overstaffed teams with these small nimble AI native pods, which could involve slashing the size of many teams across the company by as much as 60%. She reports that also this did not happen in the way that they had wanted to. Basically implies that Mark Zuckerberg sort of got cold feet sort of midway through this slash and burn reorganization and called off planning

• 20:00Kevin Roose?

  for future cuts. But to me, it seems like this is a company that realizes that it is just, it is built for the last era and it is not quite, it has not made the jump to the new era. And I wonder if you think the, the social media addiction and harm lawsuits sort of factor in there?

• 20:17Casey Newton?

  It's hard to say because, of course, the social media business is still so incredibly profitable for them. You know, Facebook and Instagram just print money for this company. They remain hugely popular despite everything that we have talked about. In fact, you could argue that these lawsuits are essentially targeting the fact that they are too popular. At the same time, I think this company, you know, having talked to many of their executives over the years, they got really uncomfortable with a lot of the employees they had. They thought their employees had too many ideas. They were too entitled. They wanted too many things. And I think they have frankly relished getting rid of lots of them. And so I expect that to continue. Like, here's a prediction. Those 60% cuts that they got cold feet about this year? I bet they try again next year when the AI systems are better.

• 21:01Kevin Roose?

  Yeah, I find this totally fascinating. I think it'll be very interesting to see whether teens do actually go to sleep earlier and pay more attention in their classes, or whether they just switch to some other more horrible app.

• 21:13Casey Newton?

  Here's the thing. You cannot actually solve the teen mental health crisis at the level of app design. Like, you need more people involved and you need different solutions. But harm reduction is a very effective strategy to have in your toolkit. And I do view the changes that Meta is making today as harm reduction.

• 21:31Kevin Roose?

  I do, too. I mean, I feel better raising a kid in a world with these restrictions on these platforms than I would without them. And I think there's a lot of, you know, we give a lot of guff to sort of regulators and lawmakers when it comes to technology on this show. But I think this is one instance in which they were focused and they were persistent and they got the goods on one of the most important companies in the world. And they got what they wanted in the form of these stronger protections for kids. So I think this is a case of democracy working.

• 22:02Casey Newton?

  This was a case of state attorneys general doing what Congress tried and failed to do, right? Congress considered legislation that would have mandated some of these changes. But the state attorneys general got this over the finish line, and I am grateful that they did.

• 22:17Kevin Roose?

  Yeah. Among other reasons, it means that I will not have to fumble my way through saying "attorneys general."

• 22:23Casey Newton?

  Imagine fighting for your constitutional right to send a 13-year-old a push notification at 3:00 AM, saying that there was a new reel that they might be interested in. At some fundamental level, that is what this case is about.

• 22:37Kevin Roose?

  When we come back, a surprising take on data centers from Princeton computer scientist Arvind Narayanan.

• 23:02Speaker 03

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• 24:09Speaker 00

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• 24:45Kevin Roose?

  Well, Casey, we couldn't let a week go by on this show without talking about the hot topic du jour, which is data centers.

• 24:52Casey Newton?

  Yeah, I would say it's the hot topic du year because it seems like since January, it's almost all we hear about.

• 25:00Kevin Roose?

  Yes, and there's been so many, we've done so many segments and so many shows about the data center backlash and what's driving it and what's, you know, where it's going and what it means for the AI companies and for AI progress as a whole. But today, I thought we should drill into one specific post and one specific angle that I thought was really interesting on data centers and these data center moratoria and bans. This came from Arvind Narayanan, former Hard Fork guest, professor of computer science at Princeton, and someone who is widely considered a serious critic of AI hype. He's the co-author of AI as Normal Technology, the essay we brought him on to talk about about a year and a half ago.

• 25:41Kevin Roose?

  And he has been following this data center backlash as we have and has come to a surprising conclusion.

• 25:47Casey Newton?

  Yeah, and that conclusion is that stopping the construction of new data centers will not meaningfully slow AI progress.

• 25:56Kevin Roose?

  Yeah, and in particular, he gives some real numbers to this argument. He says that if a typical US state enacts a one-year moratorium on new data center construction, it would only slow AI efficiency progress by five to 10 hours. So basically, if your concern is all this stuff seems to be moving too fast, opposing data centers in your state or your city is not an effective way to slow it down.

• 26:22Casey Newton?

  Yeah, and there are some questions about how much opposition to data centers is really about AI progress. I think there are a lot of other factors. We'll get into it. But we did think that Arvind's point was worth dwelling on a bit because I suspect that as we move forward and more and more data centers get proposed, there are going to be a number of people who see this as a meaningful way of getting some control and agency back in the AI future.

• 26:47Kevin Roose?

  Yeah, and I've even heard it expressed by people who are generally, you know, supportive of and optimistic about AI but are worried about some of the risks of this moving too quickly, which is like, well, maybe the data center backlash is sort of based on these like, you know, these sort of local fears about water use and electricity. Maybe they're not quite fact-based when they're out there protesting data centers. But if the net effect is slowing down AI progress, that might be a good thing. And so I really, I really was challenged by and provoked by Arvind's work on this subject because he is someone who's been very skeptical of the claims being made by some of the AI lab leaders. And yet here he is sort of saying, well, stopping data centers is not the way to stop AI progress.

• 27:31Casey Newton?

  All right. Well, before we bring him in, Kevin, should we quickly do our AI disclosures?

• 27:35Kevin Roose?

  Sure. I work for the New York Times. We're just doing OpenAI, Microsoft, and Perplexity.

• 27:39Casey Newton?

  And my fiance works at Anthropic.

• 27:47Kevin Roose?

  Arvind Narayanan, welcome back to Hard Fork.

• 27:49Speaker 05

  Thank you, Kevin. Thank you, Casey. Great to be here.

• 27:52Kevin Roose?

  So it has been nearly a year and a half since we last had you on the show to talk about your AI as normal technology paper, which argued that essentially there are all these bottlenecks that are going to prevent AI from being universally adopted throughout society and getting this sort of rapid takeoff that some people out here in San Francisco believe is imminent. And so it was a little surprising to me that we are having you back to talk about one sort of potential bottleneck that you don't think is going to be a big issue to continued AI progress, which is all of this backlash to and opposition to the construction of data centers. So tell us about your thesis on data centers and whether they will or won't slow down

• 28:37Kevin Roose?

  AI progress.

• 28:38Speaker 05

  Absolutely. I think the backlash can be a real constraint to AI progress, but maybe not if it's directed toward data centers. It's a different kind of backlash if it's directed at, for instance... Governments or other decision makers using AI for consequential decisions. I think that would have much more of an impact. And we're maybe seeing some of that, but most of it is directed towards data centers. And the reason I think it's, you know, it could be a good way to push back if you're concerned about noise or water or other local environmental concerns. But what if you're actually concerned about AI progress as a whole? What is this going to mean for society, for jobs? What is this going to mean for safety?

• 29:22Speaker 05

  And you generally want to push back on the pace at which this technology is developing. Data centers, to me, are not the way to go.

• 29:29Casey Newton?

  Yeah, well, so let me make the naive case that not building data centers would slow down AI progress. And then you can give me your math, Arvind, and I'll pretend like I understand math for the purposes of this segment. So I think that the naive case might go something like, well, we know that to sort of spread AI throughout society, we need to train ever bigger models. That means building more data centers that can train those models. And then we also need those data centers to serve those models. And so the fewer data centers we have, the fewer places there are where we could train these models and serve them to other people. And so for those reasons, I could imagine somebody thinking, well, maybe I'll just stop this data center from being built in my backyard and I will be doing my part to stop AI.

• 30:14Casey Newton?

  What's wrong with that argument?

• 30:16Speaker 05

  I think that's a good starting point to think about it, but then we have to get into the details. So you helpfully separated training and inference or serving the models. When it comes to training, most of the data centers, as I understand it, are not used for training. That requires some degree of specialization and those are done in particular clusters. And so stopping a few data centers here and there is not going to slow down training at all. For that, you need some kind of national moratorium or even global. So the real question is about inference. So is stopping a few data centers, you know, either in one's local community or a statewide moratorium or something like that, which is where the action really is, is that playing

• 30:57Speaker 05

  a meaningful part in decreasing the total amount of AI capacity available in the world? And so to turn that into something a little bit more concrete where we can do some math, we have to look at the total amount of capacity available at a given capability level. Right? And so the reason that is important is that one way in which AI is advancing that people don't often think about is not through building new data centers and putting new GPUs into them, but by making more out of the ones that we already have. The industry is getting more efficient at building AI to do a certain kind of task at a certain capability level using less power, less machines.

• 31:39Speaker 05

  And then the second factor you have is that GPUs, newer GPUs are more power efficient. And those are not all going into new data centers. Those are also going into existing data centers. So it's really those first two factors, what you can do with the existing data centers that really dominates the increased capacity from new data centers.

• 31:57Casey Newton?

  So you're saying that data centers are becoming efficient at a rate faster than demand is growing, or at least to the extent that demand is growing, stopping a data center here, a data center there, isn't going to be enough to counteract the effects of these efficiency gains that you've just described?

• 32:17Speaker 05

  That's right. The efficiency gains, both from software and from hardware, are about an order of magnitude more than the capacity gains from literally new physical buildings.

• 32:27Casey Newton?

  I'm trying to wrap my head around this because I know that what you're saying is true. The models get more efficient to serve over time, right? The labs keep discovering new ways of running their models more efficiently so that the query that might have, you know, eaten up a certain amount of compute last year, this year, you know, only needs a 10th of that amount. But my understanding is that those efficiency gains are the product of increased compute and having bigger models that are able to help researchers discover the efficiency tricks in the, and the new algorithms that allow them to serve the models much more cheaply. So isn't the overall size and availability of compute important in, in keeping that efficiency curve going?

• 33:12Speaker 05

  Absolutely. But again, I think we're looking at, you know, really, really marginal changes to the total capacity. We're looking at, you know, 0.1% of the national or world's capacity of data centers that can be affected by the actions that one community or even one state can take. And, and so the way to look at it is, yes, it's true that compute is an input even for future development of AI. But whatever decrease you bring about in total capacity, you know, through stopping data centers, whether that compute is going to be used for serving models or for further

• 33:53Speaker 05

  AI research, that same amount of progress can be made through these gradually continuing efficiency improvements at a rate that, you know, I did the numbers on this. If one state stops new data center construction, that translates to something like 10 hours, right? That's how much it takes aggregated for the AI industry to catch up through efficiency improvements to the compute that has been foregone.

• 34:16Casey Newton?

  It's just so counterintuitive because of how hard the companies are all working to build new data centers, you know? Like throughout most of this year, most of the big frontier labs have been in this capacity crunch where they're basically selling as much AI as they can make.

• 34:31Speaker 05

  Yeah.

• 34:32Casey Newton?

  So it certainly seems like there is something very important to them about being able to build these data centers. So how do you think about that, Arvind?

• 34:40Speaker 05

  Yeah, so that is all true. And that doesn't contradict what I said. And here is the way to square both of those things. So this progress that's happening through improved GPUs or improved software efficiency, for the most part, that is shared by all AI companies. And so that factor kind of cancels out between companies. And, and the competitive advantage that one company is going to have over another really comes down to how much compute they can control. And so while the total amount of compute is not a big factor in the aggregate rate of AI progress, the relative amount of compute is a surprisingly big factor in the relative competitive positions of companies. Both of those, the things are true at the same time.

• 35:24Casey Newton?

  Interesting. So regardless of, you know, what moratoriums might do for overall AI progress, if you are an individual lab, it's still really important to you that you got as much compute as you can get your hands on.

• 35:35Speaker 05

  Exactly. If only to stop your competitors from getting their hands on that.

• 35:39Casey Newton?

  I mean, I think a lot about this in terms of the nuclear power opposition in the 1970s and 1980s, where you had this, these like, you know, series of accidents, including Three Mile Island. And after that, like a huge chunk of the American populace, or at least the politically active American populace, decided that nuclear power was bad and dangerous and we shouldn't build it. And so there was basically a successful campaign. I mean, we didn't build nuclear power in America for like 30 years. And it didn't stop the technology, but it just sort of changed the geography of where it could be built. So instead of happening in America, it was happening in France and other places around the, around the world that did build nuclear power. Is that what you think is the likely outcome of data center opposition in America?

• 36:22Casey Newton?

  That it won't sort of stop the technology, but that it could, it could change the distribution of where it's being built?

• 36:27Speaker 05

  You're right that I don't think it'll stop the technology. I'm also very skeptical of whether it's going to meaningfully change the distribution of where it's built. State versus state, maybe, but if I understand correctly, one reason stopping a lot of nuclear plants from being built in the US was so successful was by raising the regulatory cost. And that's just a very different model from how the AI data center backlash is proceeding. It's not, you know, it's not nationwide regulation that forces AI developers, wherever they are in the nation, to go through a whole lot of extra review or a whole lot of extra safety technology that is going to raise their costs tenfold and change their timelines,

• 37:11Speaker 05

  deployment timelines tenfold. It's rather, you know, moving it from one location to another, which locally might seem like a big win, but at a national level, I don't see it doing much.

• 37:22Casey Newton?

  Yeah.

• 37:24Kevin Roose?

  That's interesting. I'm curious, Arvind, if stopping AI progress is not a realistic goal of the data center opposition that we're seeing right now. Like, are there other things that it could accomplish that may be constructive rather than futile?

• 37:39Speaker 05

  Absolutely. I've looked a little bit at what is driving the anti-data center movement. And I'm certainly not claiming that this kind of slowing AI is the main goal of the movement. A lot of it is driven by local concerns, a lot of it is driven by procedural concerns, the lack of transparency, the way that local politicians enter into these deals without giving citizens a voice. But whatever the ultimate reasons are, I would say that what is happening right now is arguably a pretty rational way to go about it, because you have to have the credible threat of bans and moratoria in order to force companies to come to the negotiating table. So companies are making a lot of money. I think maybe communities can channel their opposition

• 38:24Speaker 05

  in a way that they can ask for direct payments, investment into local communities, much more than we're seeing today from AI companies, so that local communities can benefit.

• 38:34Kevin Roose?

  What do you think does drive AI progress if it's not availability of compute? You've said algorithmic efficiency, the sort of notion that these models become cheaper to serve over time. But what else should people be, if they are interested in slowing down or stopping AI progress? Like, what is the better fight to be having?

• 38:54Speaker 05

  Yeah, I mean, there are many different dimensions of progress, right? So one can think about what is the most powerful, capable model out there. And that might matter to you a lot if what you're concerned about is some of the incidents we've seen, like the hugging face incident and some of the safety risks. There's another sense in which you might want to stop the rapid march of AI, which is people doing things with AI that are not really suitable for AI, delegating too much decision-making to AI. So when I hear things like the colloquially named AI psychosis among CEOs, right? CEOs using Claude code to try to replace what an employee does. And of course, it does a first cut version, which superficially seems like it does the job,

• 39:39Speaker 05

  firing a bunch of people and then recognizing, oh, shit. Now, when something goes wrong, there's nobody to fix the mess, hiring people back. We've heard this kind of story many times over. And of course, in some cases, these models are good enough to, in fact, replace certain tasks that people do. But the level of premature decision-making that we've seen from CEOs has been a cause for concern. I would have hoped that these people, who frankly have a lot of money on the line, would just for rational, self-interested reasons, make better decisions that take into account not just AI's potential, but also its limitations here and now. So this, in my view, would be a much better target for opposition.

• 40:20Speaker 05

  And that's less at the community level and more at the workplace level. Better aligning incentives and decision-making and information between the individual workers, who in many ways have a much more grounded understanding of what AI can and can do in a particular company, and management, which in many ways is forward-looking, and that can be a good thing, but can also make some misguided decisions.

• 40:49Casey Newton?

  Yeah. At the same time, I think there are probably a lot of people out there who do want to sort of have more control and agency in a world where it seems like AI is advancing quickly. And I suspect they're not going to be satisfied with the answer of like, well, you can just rely on the inertia of your organization to slow the progress of this. So are there other things out there on the horizon that you think could give people more of that feeling of control?

• 41:19Speaker 05

  Absolutely. I think we have a lot of control in how we ourselves use AI. So this is something I constantly confront in my own use of these tools. I mean, I am a pretty heavy user of AI tools and AI agents. And I find that by default, they do things that I'm not very happy with in ways that I feel like I'm losing control. So if I ask an agent to find papers, materials, reports on a given topic, so that I can start to analyze it, it will, without my asking for it, turn that into its own analysis, its own opinion. And so I have to put specific things in my prompts so that I can get it to do the grunt work for me, not to do my thinking for me. So that's just one simple example.

• 42:04Speaker 05

  But the broader point is that these tools are not only powerful, they're very, very flexible in how we can use them. And I think each of us should not just accept the way that the developer has created the tool, but configure them, personalize them in ways that meet our appropriate comfort level for what should be delegated to AI and what should be in the domain of people. That's not an answer to your broader question about AI as a kind of powerful global force and how we can slow that down. But I think at an individual level, I do want to emphasize that we have a lot of agency.

• 42:38Kevin Roose?

  The Marxist historian Eric Hobbesbaum has this famous phrase about the Luddites of the Industrial Revolution, that they were conducting collective bargaining by riot. Basically, that all of the opposition to machines was a form of collective bargaining, because those industries had not been unionized. And the only means of expressing their discontent that workers had was to break the machines that were threatening their jobs or threatening to concentrate wealth to the owners of the factories rather than to the workers. And I've been thinking a lot about this, obviously, and thankfully, we're not at the point of violent riots over data centers yet.

• 43:21Kevin Roose?

  But I think there is a possibility that we end up there. And I think your point, Arvind, about this being a form of collective bargaining without any formal mechanism, like this is, to me, when I see people protesting data centers, I think this is about what's in it for these communities. If the data center companies came in and said, we're going to build this data center, but we're also going to build you a high school and a really nice public park and improve your roads and make your everyday life better. To me, that feels like a much better deal than they're getting now. And so I think of this sort of data center backlash as a form of collective bargaining by another name.

• 44:00Casey Newton?

  Well, and the traditional form of collective bargaining has been pretty effective here, right? We've seen workers in Korea rise up and threaten to go on strike if they didn't get a greater share of the profits, the record profits that their companies were realizing, in part due to the AI bubble. So I think good old-fashioned unionization can do a lot here. We also saw it in Hollywood, right? Where the last time the big unions got together, they negotiated for a lot of protections against AI.

• 44:25Kevin Roose?

  Yeah.

• 44:26Speaker 05

  100% agree with the collective bargaining perspective.

• 44:29Kevin Roose?

  All right. Well, Arvind, thank you so much for coming on. We really appreciate your expertise and wisdom, as always. And yeah, I guess we won't see you out there on the picket lines for the data centers. We'll see you in the spreadsheets.

• 44:45Speaker 05

  I'm happy with that rule. Thank you. This has been really fun.

• 44:47Kevin Roose?

  Thank you.

• 44:52Kevin Roose?

  When we come back, hats off, folks. It's time for the last installment of HatGPT.

• 45:06Speaker 03

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• 45:40Speaker 06

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• 46:13Speaker 04

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• 46:49Kevin Roose?

  Well, Casey, we have a bittersweet final segment of our episode today. We are doing the last ever HatGPT.

• 47:03Casey Newton?

  That's right, Kevin. After almost four years of slips of paper being lovingly handcrafted and fed into a variety of stylish hats, this will be our final opportunity to take a slip from the hat, discuss its contents, and then when one of us gets bored, we'll say to the other, "Stop generating."

• 47:23Kevin Roose?

  We've been through so many hats, at least three by my count, and so many slips, and we'll never forget them.

• 47:30Casey Newton?

  Hats are now out of fashion, and so we are retiring it as a vehicle for podcast content creation.

• 47:39Kevin Roose?

  All right, let's do one final trip through the hat.

• 47:46Casey Newton?

  Wow. Sometimes I forget that we record in front of a live studio audience.

• 47:51Kevin Roose?

  That's beautiful. Our producers just hit us with the applause sound effect. And Casey, this is, I think, our longest-- was this our first ever segment that had its own title and gimmick?

• 48:03Casey Newton?

  I think it was.

• 48:04Kevin Roose?

  It's our first ever gimmick segment.

• 48:06Casey Newton?

  Yeah.

• 48:06Kevin Roose?

  And it's only fitting that we go out in a bang.

• 48:10Casey Newton?

  My only lament is that because we're doing this segment today, we won't be able to continue with our bit of launching a new segment for every show until the end of the show.

• 48:21Kevin Roose?

  All right, Casey, let's open the hat one last time.

• 48:26Casey Newton?

  All right, Kevin, our first item today. The Apple Vision Pro is being used in surgery. A study from UC San Diego in which the Vision Pro was used as a primary display for a tear duct procedure, which of course I know better as an endoscopic de cryos-- oh my God, that's really hard. De cryo--?

• 48:50Kevin Roose?

  Keep going, you can do it.

• 48:53Casey Newton?

  De cryocystorinostomy.

• 48:57Kevin Roose?

  Let's go!

• 49:00Casey Newton?

  Anyway, there were 32 total procedures, and key findings included that by using the Vision Pro, the operating times were 19% shorter, they had 100% functional success with no post-operative complications, and a significantly lower surgeon-reported workload. Kevin, have we finally found an ideal use for the Vision Pro?

• 49:21Kevin Roose?

  Yes, it turns out that the people most in need of the Vision Pro were the Vision Pros.

• 49:28Kevin Roose?

  And by that, I mean the surgeons operating on people's eyeballs.

• 49:32Casey Newton?

  Stop generating.

• 49:35Kevin Roose?

  Wait, no, I have more to say about this.

• 49:36Casey Newton?

  Okay, what more do you have to say?

• 49:38Kevin Roose?

  As a Vision Pro owner--

• 49:40Casey Newton?

  Yeah.

• 49:40Kevin Roose?

  I would like to formally offer my Vision Pro, which has sat on my shelf collecting dust for the last year-plus, to any surgeon who would like to use it in an operation.

• 49:52Casey Newton?

  Oh, I thought you were gonna offer to operate on my tear ducts.

• 49:54Kevin Roose?

  Oh, I will also do that.

• 49:57Casey Newton?

  Do you think it's the sort of thing where there's just like an app and it's kind of like paint by numbers, you know, and it's just like poke here, prod here, a snip there, and congratulations, your tear ducts work again?

• 50:05Kevin Roose?

  I think about it more like you could just keep the surgeons as like a higher energy level because they could be doing their surgery, but also like checking their email and also playing Fruit Ninja.

• 50:13Casey Newton?

  Mm-hmm, that makes sense. You know, I actually have a cheaper alternative, which is if your tear ducts are busted, just look at the price tag for your Vision Pro. You'll be crying in no time!

• 50:24Kevin Roose?

  Stop generating.

• 50:25Casey Newton?

  All right.

• 50:26Kevin Roose?

  This next one comes to us from Kotaku. "Oh, boy, have you been following the GTA 6 chaos?"

• 50:33Casey Newton?

  I absolutely have. It has been the industry's most anticipated video game for well over a year now, and yet Grand Theft Auto 6 is still not out, Kevin, except in some ways it kind of is.

• 50:46Kevin Roose?

  So, yes, so there was a leak of some footage, actually multiple leaks of footage, from the new Grand Theft Auto game that have appeared on the internet ahead of a big planned reveal by Rockstar, the gaming company that makes GTA. Rockstar has taken to the internet to apologize to fans for these unfortunate leaks. They say that while it is unfortunate that the intended game experience may now be impacted by some spoilers, we hope that everyone will wait a bit longer to experience the game for themselves on November 19th.

• 51:20Casey Newton?

  Yeah, people are not gonna wait. They're gonna look at every single leak as it comes out. As you noted, there have been a series of them. And I mean, look, you know, I don't know how these leaks were obtained, presumably through some sort of crime, so I don't want to advocate for that. But people are really, really frustrated, and in particular, they're frustrated, Kevin, that to watch a trailer for Grand Theft Auto 6, the sort of thing that used to be released completely for free, since after all, it is just a marketing item, this time around, Rockstar said, "Yeah, you can see the new trailer for Grand Theft Auto 6 if you have a Netflix subscription, because we're gonna put it there first." Now, I think they've said they're gonna, you know, put it out on YouTube and everywhere else later, but this is just one more reason why people have been very frustrated with

• 52:05Casey Newton?

  Rockstar and why I think they were not too sad to see some of these leaks come out.

• 52:09Kevin Roose?

  Now, if you had to guess, what is the probability that these leaks were caused by a rogue OpenAI agent hacking into the computers at Rockstar Games, stealing the footage and uploading it to the internet?

• 52:21Casey Newton?

  I will never rule that out, and I think we have to consider it. The main thing I know from these leaks is that part of Grand Theft Auto 6 apparently does take place in a nudist colony, Kevin.

• 52:31Kevin Roose?

  Really?

• 52:31Casey Newton?

  And there is full frontal male nudity.

• 52:33Kevin Roose?

  Wow.

• 52:34Casey Newton?

  So let's just say, I'm preordering.

• 52:36Kevin Roose?

  Stop generating.

• 52:39Casey Newton?

  Next up, "Amazon drone delivers package directly into a woman's pool." And I'm gonna guess, if you're listening, you've already seen this. This was a truly inescapable clip, and we loved it so much. "A Texas woman named Lindsay Austin ran outside to film her first drone delivery. She used one of these Amazon Prime drones that we've featured in a past episode, and the drone hovered over her pool before dropping the package straight into the water."

• 53:05Kevin Roose?

  Do we know what was in the package?

• 53:07Casey Newton?

  No.

• 53:08Kevin Roose?

  Like, maybe it was a pool float or something thematically appropriate, and the drone just made the decision, "I'm gonna drop this, like, well, I'm gonna save them the trouble."

• 53:15Casey Newton?

  Yeah.

• 53:15Kevin Roose?

  And just drop it directly in the pool.

• 53:17Casey Newton?

  Maybe it was one of those little systems for putting chlorine into the water, you know? In which case, why?

• 53:24Kevin Roose?

  Well done, Amazon drone.

• 53:25Casey Newton?

  Yeah, well done. Let's give the benefit of the doubt to the drone. Okay, stop generating.

• 53:32Casey Newton?

  Next up, "And here's a question I've truly never asked before. What if your texts traveled as slowly as a carrier pigeon? There are two new messaging apps doing the rounds online, Kevin, Carrier Pidge and Roost, and they deliberately slow messages to the speed of real animals." So this means, Kevin, that if you use Carrier Pidge, a text traveling from Los Angeles to New York City would take 22 hours. And also, there's a 0.2% chance your message will never arrive because the pigeon got lost or died in transit. You will have to replace your pigeon, and it costs 99 cents for a new one.

• 54:12Casey Newton?

  I really admire this because it's rare to see an app that is made this bad on purpose. But this seems like something that might appeal to you as somebody who has, you know, done various tricks to stop using their phone in the past.

• 54:27Kevin Roose?

  No, this is great news for me, and I'll tell you why.

• 54:30Casey Newton?

  Why?

• 54:30Kevin Roose?

  I am not a good group chat participant. I am someone who, you know, lets the messages pile up. I'm not very good about responding in a timely way.

• 54:41Casey Newton?

  You're a lurker.

• 54:41Kevin Roose?

  I'm more of a lurker. I'm just, I'm very bursty. Like, I'll respond to like 18 texts at once, but then I'll like put my phone down for six hours. This is great for me because now, whenever anyone's like, "Why isn't Kevin chiming in?" I can just say, "I did, but I sent my messages via Carrier Pidge, and they just died on the way to your phone."

• 55:01Casey Newton?

  Yeah. All my messages are dead. Sorry. Yeah, you know, for all of the concerns I have about like using my phone too much, like sending messages to people is not really one of the concerns that I have. You know, it's more of like publishers and creators and like social apps sending push notifications, like that's the stuff that I want less of, not like fewer messages from my friends.

• 55:23Kevin Roose?

  Yeah, it is great plausible deniability, though, if you're bad at texting. So for that, I want to commend the pigeon apps.

• 55:29Casey Newton?

  Here's what I would say. If you find yourself using this app to get less messages from your friends, the problem is not your phone, the problem is your friends.

• 55:37Kevin Roose?

  What is more annoying, someone in the group chat with Carrier Pidge installed on their phone or someone with a green bubble? Who are you kicking out?

• 55:45Casey Newton?

  There's nothing wrong with people who have green bubbles. That is such a classist sentence, Kevin.

• 55:53Kevin Roose?

  Okay, man of the people. How many group chats do you have with people with green bubbles? Let me see your phone. Let me see your gun. No, I don't want, actually, I don't want to see your phone. There are some federal crimes up there. Stop generating!

• 56:05Casey Newton?

  All right. "AI agents are turning founders into insomniacs." This is from the Wall Street Journal, which reported on AI startup employees working around the clock to babysit fleets of AI agents. Workers are waking up at odd hours to check what an agent did overnight, or I guess in the middle of the night. And there are some great quotes in here. For example, one founder says, "It's like a drug. I've never actually done drugs, but I imagine it's what it feels like." My advice to this man? Do drugs!

• 56:33Kevin Roose?

  Do some drugs.

• 56:34Casey Newton?

  Do some drugs!

• 56:35Kevin Roose?

  I promise it is better than doing agents in the middle of the night.

• 56:39Casey Newton?

  Another person quoted in the story says, "I don't know if it's healthy for me to be out on a run looking at my watch to give my agent permission to do something." And no, I would say that's very healthy. Please look at your agent at all times. Never, never look at the street as you cross it. Certainly don't look both ways. Just see what happens. I think you'll probably be fine.

• 56:56Kevin Roose?

  I understand why people in the rest of the country want to wipe San Francisco off the face of the map. People here are living in ways that would send shivers down the spine of any red-blooded American.

• 57:07Casey Newton?

  Now, Kevin, you're sort of mid pivot into being a startup founder. Are you waking up in the middle of the night to inspect the agents that I assume you have building our company?

• 57:16Kevin Roose?

  No, I'm waking up in the middle of the night with anxiety, the old-fashioned way.

• 57:21Casey Newton?

  It's funny you mention that. I've been doing that, too. Stop generating. All right. Oh, this next one, I've been looking forward to seeing this.

• 57:29Kevin Roose?

  Wait, you did the last one. It's my turn.

• 57:30Casey Newton?

  Okay, fine.

• 57:31Kevin Roose?

  Don't take this from me. This is our last chance.

• 57:34Casey Newton?

  I got greedy.

• 57:35Kevin Roose?

  All right, next out of the hat.

• 57:38Kevin Roose?

  Oh, this one's a good one. This one comes to us from Business Insider. There's a new term for coworkers who blindly share AI output. Meat proxy coined by Nicholas Groen. The term meat proxy describes people who blindly copy and paste the output of AI systems to their peers. Groen writes, by all means, prompt AI, but don't just relay the output. Read it, understand it, validate it, and then write a response in your own words. Casey, what do you make of meat proxy? And are you a meat proxy?

• 58:08Casey Newton?

  I really strive not to be a meat proxy. This, I don't like the phrase and I won't be using it. But do I know software engineers now whose job just consists of occasionally checking in on a coding agent and saying like, oh, yeah, do that. Or, you know, the agent will say to them something like, hey, I can't access this file. And, you know, they'll just like, kind of go quickly open it. But, you know, it's kind of a funny phrase, but there is a kind of creeping human disempowerment in here that I think is actually bad.

• 58:40Kevin Roose?

  Yeah, don't be a meat proxy. I think the stigma around meat proxies is positive. And if someone in your life, well, I also just want to say, you have sent me some, some Claude slop that struck me as the actions of a meat proxy.

• 58:55Casey Newton?

  Yes, now, I always try to identify it as Claude slop when I do that.

• 58:58Kevin Roose?

  That's true.

• 58:59Casey Newton?

  Yeah.

• 58:59Kevin Roose?

  Stop generating. All right, you're up.

• 59:03Casey Newton?

  Okay. Well, I've been looking forward to watching this one, Kevin. The Chinese robot Tian Gong clocked a sub nine second 100 meter run in Beijing. As you probably know, the World Humanoid Robot Games were in Beijing this week. More than 2,000 robots from 16 countries competed. And in the 100 meter sprint prelims, two robots, both the Tian Gong Ultra and Honors Lightning Robot, beat Usain Bolt's world record of 9.58 seconds in the 100 meter sprint. Three days later, Tian Gong Ultra ran it in 8.86 seconds,

• 59:48Casey Newton?

  breaking its own opening day record, which that's the good news. The bad news is that the robot had trouble stopping and ran straight into a padded wall and burst into flames. But I'm telling you, if I ever ran 100 meters in 8.86 seconds, I too would burst into flames at the end of it, just out of the sheer joy of having won.

• 1:00:07Kevin Roose?

  I have been totally obsessed with these humanoid robot games. This is my Olympics.

• 1:00:13Casey Newton?

  Yeah.

• 1:00:16Kevin Roose?

  Less because of the achievements. Like, I don't actually think it is that cool that a robot can run faster than Usain Bolt.

• 1:00:21Casey Newton?

  Why don't you think that's cool?

• 1:00:22Kevin Roose?

  Like, a car can also go faster than Usain Bolt. Like, it's not, it's a, it's a robot. It doesn't, who cares? But the way that these robots run and what happens to them after they finish is the most transfixing thing that I've seen all year. I want to show you a clip from the humanoid robot games because it is astounding.

• 1:00:43Casey Newton?

  Let's look.

• 1:00:46Kevin Roose?

  Okay, so they're running down the track. They're sprinting, they're sprinting, boom! They all run into the wall.

• 1:00:53Casey Newton?

  Now, can they not program them to either stop? Or, I don't know, just not go, not run into the wall?

• 1:01:03Kevin Roose?

  This one goes boom into the wall, falls back, falls down, sparks fly. He had to be carried out in a stretcher.

• 1:01:11Casey Newton?

  It is, it is disturbing because they just go like so completely limp. And because they're, you know, humanoid, you do, you do sort of instinctively sympathize with them.

• 1:01:20Kevin Roose?

  Oh, I don't.

• 1:01:20Casey Newton?

  Oh, okay.

• 1:01:22Kevin Roose?

  I feel like, you know, this is, this is, this is their comeuppance for their hubris of trying to beat us at running.

• 1:01:30Casey Newton?

  When you see a robot running that fast, do you think like, one of these days, something like that is going to chase me down a dark alley? And I've got no hope?

• 1:01:37Kevin Roose?

  I think, why are we building the machines that run faster than Usain Bolt?

• 1:01:40Casey Newton?

  Yeah.

• 1:01:40Kevin Roose?

  Well done to all the competitors in the humanoid games, at least the ones who survived.

• 1:01:44Casey Newton?

  Stop generating.

• 1:01:45Kevin Roose?

  All right, Casey, here we are.

• 1:01:47Casey Newton?

  Final item?

• 1:01:48Kevin Roose?

  The bottom of the barrel, the bottom of the hat. I'm getting weirdly emotional.

• 1:01:54Casey Newton?

  Hmm.

• 1:01:55Kevin Roose?

  We've done so many of these. This one comes to us from Alex Heath, who wrote the cover story in this week's edition of Time Magazine called Inside OpenAI's Reboot. And he talked to a bunch of different executives and leaders at OpenAI who gave an update on their path to AGI. According to Heath, Chief Research Officer Mark Chen estimated that OpenAI is 80% of the way to AGI. And Sam Altman told him that OpenAI was not quite yet at AGI, but that by the end of the year, the company would have an internal system that he would call AGI. Casey, what do you make of this?

• 1:02:35Casey Newton?

  I mean, I, you know, my instinct is to be skeptical, but when they say we're about 80% of the way there, that basically sounds right to me. I don't know. Sound off in the comments if you disagree, but we are at a level where the computers use themselves and you can just type what you want into a box. And more often than not, these days, you'll get it. So I'm basically saying, yeah, that sounds about right to me. What do you think?

• 1:03:02Kevin Roose?

  I mean, I've thought a lot about this question of like, what AGI even is and how you know when you've reached it.

• 1:03:09Casey Newton?

  And what it means to you.

• 1:03:10Kevin Roose?

  And what it means to me. I mean, this is literally the sort of title question of my book that I spent the last year researching. And where I came down on this is basically that by any pre 2022 definition of AGI, AGI is here. Like, if you took any of today's models, if you took Fable 5 or GPT 5.6 back in a time machine to 2017 and showed them to the people who were building AI at the time, they would have said, well, yes, this is obviously AGI. And I think as it's gotten closer, as we, as the systems have gotten better, our goalposts have shifted, our expectations have been raised.

• 1:03:52Kevin Roose?

  And now, you know, everyone sort of has their own different bar for what AGI is or when we should consider that we've achieved it. But basically, we have already long ago reached the threshold that computer scientists from even a decade ago would have said meets the definition of AGI.

• 1:04:08Casey Newton?

  Well, my bar is can, is a system sufficiently advanced that it can build a time machine so that you could take Fable 5 back to 2021 and show it to a scientist and ask them, is this AGI? So that's my bar.

• 1:04:22Kevin Roose?

  Okay, we'll get there. Maybe not by the end of the year, but we'll get there.

• 1:04:25Casey Newton?

  80% of the way there.

• 1:04:27Kevin Roose?

  Well, I think that they are sincerely convinced that AGI is 80% of the way there. There are other companies that may take longer to announce that they have created AGI. But I think this is, I think it is a big deal that they are now talking about AGI in the present tense as something that is more here than not. And I think it'll just be sort of a marketing decision when they want to officially claim that they've gotten there. This is such an arbitrary threshold, impossible to test for. The other thing that I'm certain about is that if and when Sam Altman does come out and say, we have built AGI, there will be many, many people who argue with him and say, no, you didn't. It still can't do X, Y, and Z. It hasn't proved the Riemann hypothesis. It hasn't, you know, it still makes mistakes.

• 1:05:11Kevin Roose?

  I don't think there will ever be a sort of consensus on what AGI is or when we have gotten there. But I think the people at OpenAI are more right than wrong about how much progress we've been making.

• 1:05:22Casey Newton?

  Hmm. Well, Kevin, with that, I'm going to ask you to stop generating. Hats off to you, hats off to me, and hats off to ChatGPT. That was ChatGPT.

• 1:05:35Kevin Roose?

  That was ChatGPT?

• 1:05:39Kevin Roose?

  Wrong sound effect.

• 1:05:50Speaker 03

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• 1:07:34Casey Newton?

  Hard Fork is produced by Rachel Cohn and Whitney Jones. We're edited by Veron Povich. We're fact-checked by Caitlin Love. Today's show was engineered by Alyssa Moxley. Original music by Alicia McItup, Marian Lozano, Rowan Nimaisto, and Dan Powell. Video production by Soya Roque and Chris Schott. You can watch this whole episode on YouTube at youtube.com/hardfork. Special thanks to Paul Schuman, Wee Wing Tam, Brooke Minterz, and Dahlia Hadad. You can email us at [email protected] with your time in the humanoid robotic games.