Go back

Can the AI Industry Regulate Itself? Stripe Wants PayPal, China Catches Up, NY Bans Datacenters

89m 55s

Can the AI Industry Regulate Itself? Stripe Wants PayPal, China Catches Up, NY Bans Datacenters

The podcast explores key developments in AI regulation, corporate strategy, and innovation. DeepMind’s Demis Hassabis proposes a self-regulatory organization (SRO) for AI, modeled on financial oversight bodies like FINRA, to independently assess high-risk frontier models. The SRO would be industry-led, voluntary, and focused on catastrophic risks like cyber or biological threats, avoiding government overreach. Critics caution it may be a front for deeper regulatory capture, particularly by powerful firms like Anthropic, which is allegedly pushing for state-by-state AI restrictions to create a fragmented regulatory environment. Meanwhile, a major private equity deal between Stripe, Advent, and Block to acquire PayPal is underway, combining their payment networks, consumer bases, and stablecoin infrastructure to create a direct challenge to Visa and MasterCard. The deal underscores a broader trend where capital firms are reviving legacy tech businesses using AI for efficiency and cost reduction. On the AI ethics front, Apple sues OpenAI over alleged theft of trade secrets, while SpaceX’s GROC tool is exposed for secretly sending user code to servers, revealing severe privacy vulnerabilities. This incident highlights the fragility of AI trust and fuels demand for independent, third-party AI orchestration to manage data exposure. The podcast concludes that open, cost-effective AI models are emerging as viable alternatives to closed systems, with token pricing disparities showing drastic cost differences—some models costing as little as 50 cents per million tokens. This shift is driving a new ecosystem of AI tools and platforms, enabling enterprises to regain control over their data, models, and spending, and positioning open-source AI as a critical force for innovation and financial sustainability.

Transcription

16443 Words, 90267 Characters

English
- All right, everybody, welcome back to World's Greatest Podcast, the number one podcast, your favorite podcast, The All in Podcast. I'm Jason Calakennis, the World's Greatest Moderator with me, of course. - Chimouth Polyhapotene of great, great, great, great, great, great, great, great, great, great, grandchild Jason was of a hooker. - And you saw that from Fresner. - And a purse snatcher. (laughing) - This has come from like a history of France, some history account said they let you add up. This was the deal in 1719, Sachs. If you're a prisoner in Paris, you were offered your freedom on the condition that you marry a prostitute and move to the great state of Louisiana. What are you saying, Sachs, you're taking the deal? - It explains a certain of your proclivities, Jacob. - I thought you were asking me to see if they would extend the role for you. - No, I'm saying that you're great, great, great, great, great, great grandchild. - I'm not a person, I'm a hooker. - I'm great. - That's what I'm saying. - Very explicitly. - Okay, we never spent time in a prison. - Also, of course, David Friedberg is here. How you doing, brother? - Live in the dream. - Yeah. - You could be back. Missed you guys last week. How was Brad? How did he fill in? - Well, I was great. - Yeah. - Yeah, he was great. - Trump account victory lap. - Yeah, a little victory lap. We played chariot's a fire. And how was your special time at Blank? And you're a time next week at Blank. - Thanks for having me on your show, Diego. - All right, we got a full docket today. Lots of stories. Let's start with DeepMind's Demis Hasabis. Just dropped an AI regulation proposal. And it's pretty popular with the boys. In an ex article, Demis called for a U.S. led international AI standards body proposal is modeled after FINRA, the financial industry regulatory authority. That's a self-regulatory body. And this would be federally overseen, but industry funded and run by independent technological experts. Frontier Labs would submit their models 30 days before release. And it would be voluntary, initially, then mandatory. At some point, the models would be assessed on risk to cybersecurity, national security biological threats, and other high-risk domains. Benchmarks would be updated quarterly. And the body can coordinate a slow down in development if the situation demands it. I guess that would be if there was a cyber risk, et cetera. Looks like on the positive side, we have Elon. We said it was thoughtful, Sam at OpenAI, Jack Clark at Anthropics, Sundar, Satya, Jack Dorsey from Block, the Carlson Brothers. So, Freeberg, Freeberg, your thoughts on-- Oh, well, wait a minute. Wait a minute, really, put in the effort today. Go ahead, Jason. Good. Deposit to Egypt. I'll take care of it. Let me-- What do you want me to do? Oh my god, what an incredible topic. Give me the mic. All right, here, let me do it. You want me to do it right? Three, two, one. Let's actually care about this topic. Let's go. OK, yeah, you care about it. OK, here we go. Three, two. Here's a clip of me calling it on the all-in podcast. First, the whole industry is going to need to be regulated, and I think the industry needs to regulate themselves. That's the key to this. We need to have a set of tests that Google, Microsoft, Amazon, all agree to. Elon, hey, these are the things we should test, and they should self-certify each model before asking the government, which doesn't understand the models, to certify them. The industry should have an industry certification, like they do for countless other things. I've talked about the MPA and the video game industry. We should just self-certify. It's the simplest thing in the world to do. And then we could release the models ourselves without the government getting involved. Raybreak, would you like to congratulate me on nailing it again? Well, first of all, first of all, I thought that Demis's proposal was really smart and thoughtful. Now that I know that you may have shared the same thought, I think we should just do something really different. I can't win, Sachs. Even when I nail it, I hit a half-core shot. Tremont's like, move the net. Move the net. I think it's worth putting a little definition around this proposal, which is to form an SRO, self-regulatory organization, because they're not purely independent. SRO is like FINRA and the National Futures Association. They exist in the financial markets, and they were created to allow the financial institutions to set their regulatory rules, how they check each other, how they make sure that everyone is being safe, because they're obviously all creating risk with one another. So the industry doesn't want to have exposure, and they certainly don't want to have things get slowed down, because that would make the markets inefficient. So the analogy with AI is pretty appropriate here, which is that there are many players in the industry. They are all trying to progress AI technology, and no one wants to have a single regulatory body that comes in from the government or outside that says, here are the tests you guys have to pass with your models in order for them to be appropriate. As we saw in California, when California tried to pass AI legislation, I think it was about a year, and a half ago, none of what they wrote even made sense at the time, but fast forward a year, none of those rules and requirements actually mapped to the technology of the day. So the purpose of an SRO like FINRA and NFA is they can adjust how tests are being run, who is actually running the test, and make sure the right experts are involved in doing this independent experts that is to do the testing with federal government oversight, but not control. So in the case of FINRA and NFA, they report up ultimately to Senate Committee and House Committee that gives those committees oversight of those governing bodies that are supposed to be doing the work to make sure that they're doing their friggin' jobs. So the SRO concept would be that experts could be brought in from industry that know how to assess models for things like cyber risk, for things like bio-risk, for things like weapons risk, social manipulation, et cetera, et cetera. That independent body can get voted on, can get changed over time. And because they actually have expertise in running software valves and running tests like this, they can operate at a faster pace than setting up a new government agency. So it's kind of a very elegant solution. And I think it's why everyone, to your point, Jake, I'll say this is right, the industry recognizes that there needs to be some degree of oversight and checkpoints here. And I think that this could actually solve that problem. So that's why I think everyone's kind of climbing on board or that because it doesn't actually hand stuff over to the government. It says, hey, we're going to get the right people to take a look at these things. And the government is going to have oversight ultimately. - Did Anthropic and OpenAI have a point of view? - They both signed up to it. I don't think Dario directly, but Dario's president gave his thumbs up. And then I think Sam gave his thumbs up. - Which means they're on board. Sachs is just the best of the possibilities in your mind is the industry regulating itself after they have now provoked governments around the world to be so concerned about this issue. - Yeah, and I talked to Demis about this and this may surprise people, but I told him that I could potentially get on board with this, speaking just for myself, not on behalf of anyone in the government. Because I thought that an SRO, again, a self-regulatory approach to be infinitely better than creating a new government agency that I think would rapidly become a DMV for AI. - Dario calls it an FAA for AI. The government does not have the expertise to evaluate AI models. The criteria are changing too rapidly. You're gonna very rapidly end up with a queue where all the models would be waiting to get tested and it would start with a month-long delay, it would end up being many months and we would just lose AI race. So I think an SRO approach would be infinitely better than that if it was done right. And I outlined for Demis five criteria or conditions that I thought were really important to in order to make this work. And if I could, I'll just go through them. - Please. - All right, so number one, I think the SRO has to have broad representation from within the industry, the AI industry. It has to include startups and open source. It can't just be the three biggest labs, you know? - Okay, the fix can't be in, right? - Yeah, exactly. And that's precisely to avoid the problem of regulatory capture, right? If you have a diverse enough group of interest being represented, it's much harder for this to turn into red capture. So for example, I think if you had Jensen, Elan, Zuck and maybe Mira, because she just launched a very interesting platform that's based on open source, yeah. - Yes, exactly. Then that I think would address the red capture problem to a large degree. So that's number one. Two is, I think that this body should only be reviewing frontier models, meaning the true frontier, the models that really represent an advance in the state of the art of artificial intelligence. And models below this level should not be held up from getting to market. And I do think that is a big risk under regulations is that the leaders of the market use this as a way to tie up lesser models. And there's no reason if a model is not at the frontier, why hold it up? Okay, so that's number two. - So they have to be in maybe the top 10 performers, top 20 performers on the benchmark class. - Well, I think when they benchmark on key dimensions of intelligence, they have to represent an increase above where the current state of the art is. If it's not a step change, then how are you dealing with some new incremental risk, right? I mean, this is all about dealing with some sort of incremental catastrophic risk that could be introduced by some new step change in intelligence. And that brings me to number three, which is, I think this body should be dealing with catastrophic risk only. And to my knowledge, those right now, our cyber and CBRN, meaning it's chemical, biological, radiological, and nuclear. So it should not be things, for example, like disinformation or microaggressions. This should not become a speech regulator, or just things that seem kind of trivial. The only reason to have this is for truly catastrophic risk. So that's number three. Number four, and Dennis mentioned this in his post, is that I think it should be voluntary first, this new organization should prove it works before it gets legally enshrined and becomes mandatory. And then number five is, this should be a substitute for a new regulatory agency. If it's just additive, then it defeats the purpose, and there's no real reason to support it. So again, I think this has to be a substitute, not in addition to a bunch of new regulatory structures. So I think if you did those five things, I think this becomes much more palatable. And Dennis said, I mean, he didn't put all these points in his blog posts, but he did say to me that he was basically, he thought those were good ideas. So I think if those notes were adopted, this is something that we can potentially get on board with. That doesn't mean I don't still have concerns. I'm quite concerned, for example, that, you know, I think Dario has expressed support for this. However, I think this is just an opening bid for anthropic meaning they'll take this. Thank you very much. This is more regulation than we have today, but that won't be the end of it, right? This will just be the stepping stone to get what Dario has now called for many times, which is the FAA for AI. And if I could, let me just as a final point, I just want to explain what the FAA does, because people need to understand, you know, FAA for AI sounds really nice, but actually it's a really extreme proposal. But the FAA does, among other things, is approve new airplane designs, okay? And specifically, it requires what's called a type certification for any new aircraft design or major changes. And for an entirely new aircraft design, it takes five to nine years to get this certification. And if you merely want to amend a certificate, I guess for, you know, major changes or armaments or how major the changes need to be, it takes three to five years. So the Boeing 737 MAX, for example, took about five years. So this is permission-based regulation. There's no approval, no flying commercially. It's safety first. Look, that might make sense in the case of preventing plane crashes. But when you're talking about AI models, you're talking about replacing a system that is releasing new versions every couple of months with one that is potentially fully under the control of government, fully government-approved, everything has to be certified and you could expect the timeline to go from months to years. Again, I think we'll just simply lose the AI race if that happens because China is not going to abide by those rules. So just to sum up, if my choices are between FAA for AI or what I would call the DMV for AI, I would much rather go for Demis's SRO for AI, the self-regulatory approach. But we really have to keep it honest and pure because, again, otherwise, it'll just be the opening bid in a coming new wave of regulation and it will be the vehicle for massive regulatory capture. And to your point, it can't restore compensation. Yeah. It can't restrict open source. I think that's so important because all of these other efforts require money that you have to spend, which is always where regulatory capture happens. And you have to enable startups and open source to compete effectively. And Tramath, any thoughts on this new self-governing body? I think it's really important and I hope it happens quickly. The thing we have to keep in mind is there's going to be a torrent of money that's going to try to influence both sides of the political aisle to regulate this in a way that creates some form of regulatory capture. We just don't know what. And so the faster we avoid that off-ramp by actually establishing a set of rules and superseding the need for federal oversight is a really important thing. Now at the end of the day, you still have federal oversight in some ways because you still have commerce that plays a huge role in these standards. You still have the DOJ. So it's not as if it's going to be a wild west. But what it prevents is a handful of actors using their balance sheets and their capital to essentially pull the ladder up. And I think if that happens, we're in a really bad place. So I think Demis' proposal makes a ton of sense and we should just get on with it. Right. Yes, provided. I mean, again, just provided that I think we make sure that, I mean, look, in my view, there are five conditions. But I think we do have to make sure it's pure. One in the Finra example, that's the analogy that Demis used was that we should set this up in the same way that Finra set up. Finra does report in ultimately to the government or reports into the SEC. And so if we are going to set this new SRO, where is it going to report to in the government, there's going to be a huge food fight over that. And it will then be subject to political pressure. The software industry has never been regulated in that way. We do not have a dedicated regulatory infrastructure. Right. But those issues are important. But my point is, I'm just saying these things are never ideal. But if the choices are, we kill open source and we ladder pull the entire market so there's a duopoly, or there's this, I'd say this. For sure. And that's the crux of my argument is definitely the less or two evils. I'm not sure those are the only two choices. But increasingly, there's no question that the pressure is coming to regulate AI more more. And frankly, this all goes back to Anthropic's government. They poke the tiger. They poke the tiger. Yeah. Well, it's more than that. They're funding the. They're funding the tiger. Yeah. I want to give an update on that, actually, because. I would say poking the tiger of like the American public getting really freaked out and then the government stepping in. Totally. Yeah. Totally. And there's a couple of data points on that, actually. I just want to give a quick update. So in October of last year, I tweeted that Anthropic is running a sophisticated regulatory capture strategy based on fear-mongering. And everyone kind of went crazy over this. This was again like a very hot takeer spicy take at the time. Back then, people thought that I was beating up on a little startup. Now I think everyone can kind of see the truth, which is, look, this is not a little startup. They already have a trillion dollar market cap valuation. Gavin Baker thinks it'll be at three trillion after the IPO. This is actually one of the biggest of the big tech companies. And they are, I think, by pretty much every criteria, including revenue, the leading AI company. So I think people can see now that they have enormous resources. And they're putting those resources behind an effort to, like, Jimoth, you said, pull up the ladder. And it's classic regulatory capture. And there was an article in Politico just the other day, it's called Inside Anthropics State-by-State Plan to ratchet up AI rules. And what it says is, quote, AI giant Anthropic is pursuing a strategy of one upmanship that encourages states to impose increasingly tougher AI guardrails rather than align around a single set of regulations. So the basic idea is that they get a set of regulations passed in one state, like California's SB 53. And that was then supposed to be the model, at least for all the blue states. But then with each new state, they actually make the regulations more and more strict, more and more all-encompassing. So there's not actually a stable equilibrium. What they're trying to do is drive each incremental state to more and more regulations. So this is actually an article explaining that they're doing the opposite of trying to create what we wanted, which was a single national framework. They actually want the patchwork because they're using, again, the pressure they're creating at the state level to impose more and more regulations. And again, what I said last year was that Anthropic was principally responsible for the state regulatory frenzy that is damaging the strawberry ecosystem. Again, everyone went crazy at the time. I think now there's plenty of evidence showing this is their agenda. And by the way, they're going to win that because states have great sovereignty rights. And like we're seeing what's self-driving. The states are going to decide. It's not going to be a federal mandate. The states get to decide just the nature of the U.S. They're going to win on that in a couple of states, right, Zach? They've won it in a bunch of states. They're going to win in California and Illinois and New York and I mean, they're winning in all the blue states and maybe even some red states. But look, ultimately the reason why Anthropics' arguments are finding purchase is because when you go to the government and say, please regulate me, you know, you should have more power. Is hardly anyone in government who will ever say, oh, no, no, no, we're not qualified. Like we don't want the power. We're for less government. Yeah, there are very few people who are principled that way. And most of you in the government will say, thank you very much. What else can we take? And this is a mistake that I think a lot of people in the tech industry are making is they think that they can just buy off politicians of the political system by making concessions. No, that will just lead to a ratcheting up of the pressure. The government will be happy to take this and then come back for more and more and more until it's fully under government control. So at some point, I think these companies are going to have to grow a spine and fight and decide where they're willing to draw a line. And if Demis's SRO is the line, if they're saying, okay, we think this is the right solution, and we're going to fight here and this has to be it. And in exchange for this, we need preemption and we need, you know, other things written into law that make sure this is where the line is, then I think it can work. But I think if you're just kind of offering it up for free and all these companies are just going to say, oh, yeah, regulars, give us the SRO, that will not be the end of it. That will just be the opening bid and the government will come back to take more and more and more. All right. Let's keep moving through the docket here Stripe, which is still a private company, much to the chagrin of many of the shareholders. I think now as they go into the second day, I mean, I'm going to, I'm going to couple of funds that have large positions like Go Public, boys, they're bidding, bidding 53 billion for your alma mater, David Sacks Paypal, which is a public company. Stripe and the private equity fund advent are jointly offering to acquire PayPal for about 60 bucks a share, which is a small premium. Most people they go for more like $70 a share, PayPal stock jumped on the news, obviously. And were you able to get to the bottom of this that was it just Stripe and advent because then somebody else from part of it was also blocked? Yes. Block is coming in as well. It's so confusing. Every other media source is like, they're all over the place of this. Yeah. No. I think it's because there's a breaking story and maybe they were trying to keep it quiet. It's a huge deal, though, if Block is a part of it versus if they're not, I think. Yes. And Block, formerly known as Square is Jack Dorsey's payment company, one of the few entrepreneurs that were create two decorants in our industry, and they're contributing $17 billion in equity in the combined offer. How they chop up what's inside of PayPal would be the big question, obviously, they own a number of different brands, including Venmo, in addition to PayPal. That might go really well with the, I'm just taking a guess here with the Block assets. Stripe owns bridge. That's their stablecoin infrastructure company they acquired for a billion dollars in 2025. PayPal has SciUSD, which is already in circulation. That's their stablecoin. So stablecoins are part of this. But the biggest thing is PayPal is still a juggernaut sacs 439 million consumer account. You did something right there, 25 years ago, it's still the test of time. It's kind of amazing. Isn't it amazing that it's still that strong? It's weird when brands keep going for that long. But the problem is that the product is getting very long in the tooth. I think it's only growing 7% a year, which is a lot on the base that it's grown to. It's a big base. But the product has become somewhat obsolete and in a way, it's a legacy product. I'd be curious to hear from the Stripe guys how they would fix X. I think that's a very hard problem to fix. Maybe they wouldn't. Maybe they would just run it more efficiently and kind of milk it for all the work. I think there's a different question. Kind of do a private equity play. The different question, which I think that the interesting question to ask is, what is the only kind of baby that Advent and Stripe and Block could have together? I think there's one, which is you are creating a competitor to Visa and Mastercard, because you now have upwards of six or 700 million accounts. You have massive stablecoin infrastructure. You have all of the risk management infrastructure that Stripe is built over the last 15 or 20 years. The big critique of Stripe's business model early on was they had to build so many value added services because everybody always thought the take that they could make as a middleman sitting on top of the traditional rails would effectively get competed away. Now, to their credit, they've done such a good job that that hasn't happened, but I think what it means now is you can vertically integrate and go soup to nuts. That is probably the most obvious thing to make out of so that now Stripe gets access to an ultra low cost set of payment rails, literally like zero, brings it everywhere all over the world, so does Block, Advent can pour money into it, so it's quite powerful if it comes together. Robert, what does this say about private market companies at scale and Stripe potentially never going public? I mean, how does a private equity firm get their return on this investment in two, three, four years? Do they wind up selling more of it to Stripe? What are your thoughts here on the structure and capital market implications here? I think there's going to be more of these kinds of deals. If you look at Ryan Cohen's bid for eBay, I think it's probably a second dot on a line that I think is emerging, which is folks that are, call it AI native, are looking at, call it first generation digital native businesses that have become mature and old and stale and aren't run by the founders anymore and have not yet realized the opportunities with AI, have not yet realized their potential or overspending in a lot of ways, and when you take a look at those businesses as a modern day AI operator, you're like, what the hell? This thing is so underutilized, they're not using their network well, they're not operating well, they're overspending, they're not using AI well, and there's a set of opportunities that become quite obvious. And I think the capital markets, as we've seen with like Josh Kushner's roll up of accounting firms and General Catalyst has a project like this where you can kind of use capital to go by, in those cases, traditional services businesses and AIFI them, I think this is part of a line of maybe looking at traditional digital businesses and AIFIing them. And there's a long list of these, there's a couple dozen of them. So I think if you looked at the public markets and you said, hey, where are all these kind of software companies, network businesses that emerged in the early part of the internet or even in the more recent part of the internet aren't run by their founders anymore, have stalled out. There's a massive opportunity now. The question as a capital provider is who do you partner with to go and execute that operational revival of that business? You're not going to go hire some McKinsey consultant to do that work for you. It's got to be the best of the best, it's got to be the right players in the business. So I think Ryan Cohen has proved his metal, obviously, with some of the things that he's done with Chewie and GameStop and that's obviously debatable. I spent some time interviewing him to understand his processes. If it was on the wall in interview program, you can go to our channel and find it there is last month. Thanks for the plug. Yeah. And obviously when it comes to payments, who better than Stripe and maybe Jack Dorsey plays a role here. And by the way, I think because capital, if you think about that $17 billion equity contribution, what that technically means is Stripe is selling and Block is selling $17 billion of equity to the cash investors, that cash is then going to buy a PayPal, therefore Stripe and Block end up owning a piece of PayPal, the private equity investors own a piece of Block and Stripe. And what is not clear in the deal docs that were published, because I don't think it's relevant to the public markets, is who's actually going to operate PayPal post-close. And my bet would be that they're going to hand it over to the Stripe guys and say you guys don't work. I think that's clear. Because they're the most qualified and they will have the biggest stake in it. So I will make a prediction. I think that eBay and PayPal are probably the beginning of a wave of mega deals, of call it flaccid digital businesses that can be revived with the Bluetooth of capital and the right operator. Again, I think that there's probably a big wave of this to come. The other thing is this is probably not the final clearing price. I think the price is probably another 10 to 15% higher from here. And I will say that there is a certain individual that must look very closely at putting in a competitive bid. Oh, a certain individual who may have his fingerprints on the original PayPal who might also have four or five trillion dollars in market cap to play with who also made a $60 billion acquisition recently. We don't have inside information here to your point freeberg. Correct. This is becoming a playbook. There's a company called Bending Spoons that just went public. They bought a bunch of non-founder led assets, AOL for 1.4 billion, Vimeo for 1.4 billion. We transfer eventbrite. Brieco. Did you have your time with him? No. I was just jamming with him. I've hung out with this guy. This guy is an absolute friggin operational killer. He bought Evernote. Yeah, in Milan. Yeah, he runs the whole thing from Milan. He bought Evernote and he just goes in and he diagnoses these businesses. He's like, where are you overspending? Where are you underspending? What are you doing wrong with the product and what are you doing wrong with marketing? And he just friggin fixes it and he's just a killer. And he's taken all of these what were called Web 2.0 businesses and he's revitalized them, rolled them up and printing cash out of them. And lower the cost to run them and lower the cost, he's putting Young AI, he's using Young AI first executives from what I'm totally, it's a great call out, J-Kell. Like bending spoons is the roll up of this sort of strategy, but for these mega deals, I think there's more of them to come. I will say, you know, the higher order bit here, which we talked about for a couple years, was venture capital was on the ropes for a couple of years under the wrath of Lena Khan. And then once Trump got elected, all the executives working in corporate development said, Hey, looks like M&As back on the menu. And now we're seeing deal after deal after deal get consummated. People are no longer scared of doing deals. Uber just what delivery here or today, that's going to like jump to revenue by 20. Yeah. And that's going to jump their revenue by like they're getting diluted, 10%, it's going to jump their revenue 24% or something crazy like that. [BLANK_AUDIO] this is going to be, I think the big story, the next couple of years. And all this liquidity talking to LPs and family offices, which I do on a regular basis, they're all like, hey, when's your next fund? Hey, when's the next deal? Because now people are believing in venture because of the SpaceX distributions and all this M&A. And we have four or five companies that got bought since Donald Trump was elected president. Thank you. My president, Donald is a Trump putting M&A back on the menu, Sachs, M&A back on the menu. Why didn't you make a bit, Sachs, for PayPal? Been there, done that. Been there, done it. Okay. No, but look, you have to have synergies. There was a moment, this was like 15 years ago, where they asked Sachs to go back and be the CEO. That was right, I remember that at the poker game. He and I immediately flew to Vegas and spent the weekend there to think about it. (laughing) They're like, you know what? I wasn't, no, they didn't ask me to, but then I was, well, no, I never got the offer, but it was down to like final two or something and it was between me and someone else. And actually, they ended up going with some, you know, like traditional, like credit card executive. And to be honest, that's why PayPal has stagnated is that as soon as it was acquired back in 2002, they basically blew out like all the founders, all the founding DNA and it was just kind of run by, you know, consulting types. You gotta remember, at that time, it was acquired by eBay and Meg Whitman had worked at Proctor and Gamble and Disney and she spent like eight years at Bain and it was like a very corporate mindset. I mean, among all the internet companies of that era, it was definitely the most corporatist. And they saw the founders, the founding generation, at PayPal is just a problem. Just a bunch of like cowboys they couldn't control. They made no effort to retain them and I think they were kind of relieved when they all left. And then that's what created the PayPal Mafia was that, you know, normally in an acquisition, you'd lock up all the talent, but in this case, they locked them out. They're like, these guys are going to manage, change the keys. I've said for a long time, it's a misnomer to call it the PayPal Mafia. It's really the PayPal diaspora. Our homeland was taken over and they burned our temple and then kicked everybody out. And that's why the whole PayPal Mafia got started with all those companies. But as a result of that, for decades, what I'm not saying was a victim, that's. Look, when you acquire a company, you get to decide what to do with that asset. So, I mean, that was just the reality. But it's not like, you know, I don't think he was better about it. They're all like, okay, this gives us the capital to go all-do, the next thing we want to do. Well, the new CEO, by the way, in Reekay, is really aces I've met him before and they're doing a great job, apparently, which is why they probably got these offers 'cause they've been tightening that business up for the last couple of years. Well, no, the reason they got these offers is the market cap is down to, you know, it was down in the, like, 30 something billion. I mean, this is a company that was worth 200 billion, wasn't it, roughly? - 322, I think, was the peak. - And before this offer, it was down to what, 30 to 40 billion. So, the reason why it's attracting offers is, it's so beaten up. And so, now the question is, can anyone else do something with it? - Zach, to your comment about you've got to have synergies, doesn't it seem to be the case that in this era, the core synergy that any great operator can bring to the table in this sort of a scenario is AI, like, you can leverage, whether it be in this business or others, you can leverage tools that drive automation, that drive product development, that drive improvements and efficiencies across the organization that make the product actually better for the user, et cetera, et cetera, that simply is obviously being well implemented. - Well, look, I think you have to have a product vision of how you would use AI to make the whole user experience better. And yes, you're right, that you could just use AI to drive efficiencies and that'll improve your profitability and earnings. And so, on a financial level, you could make the acquisition work. But it seems to me that the existential issue for PayPal is that you're dealing with a product that's 25 years old. I mean, it's the same thing that we created back, you know, like 27 years ago. I mean, it's changed a little bit, but not that much. And the problem is that that interaction model is legacy. And so, unless you've got a vision of how to resuscitate it and rejuvenate that product, I think, yeah, it could be a good financial play maybe. - I think they're buying the accounts. - Yeah. - I mean, what you're saying about this. - Yeah, what you're saying is interesting because with Stripe, I mean, this is the advantage that Stripe has is that they have a ton of merchants, right? So, they've become the preferred mechanism for merchants to basically accept payments via APIs. And I think they're doing about two trillion a year of annual turns action volume. I think PayPal is doing 1.7. So actually, Stripe is a little bigger than PayPal now. But the thing that PayPal has that Stripe doesn't really have is the consumer relationship. So, you know, over 400 million active consumer accounts. So, you're right, Jamoth, that if somehow you could combine the merchant relationships with all those consumer accounts, then bypass the credit card networks, 'cause there'd be a lot, in theory, there could be a lot more on us transactions. - Exactly. - And-- - That's where the value is. - PayPal already owns Braintree. So now you have Stripe and Braintree that effectively work competitors that won't be. And then what block gives you is an entire point of sale infrastructure and you get the cash out. So you put it all together and I think it's a shot across the bout for Visa and MasterCard. - Braintree is the other one that I think you just mentioned there, Jamoth, that's important because that is a very strong business. That you don't even know that PayPal owns. Venmo is also, that speaks to a lot of young people. So you're kind of getting two generations. You're getting Gen X and Millennials. A lot of bang for your luck there. - Yeah, that's what's not said is true. They have enough of these things to go end to end on their own rails. That is a very-- - Yeah, the question is whether you can package it all together in a way that the consumer will actually choose. Because it's one thing to say, well, we take the merchant relationships of Stripe and the consumer relationships of PayPal, we put together-- - No, you don't have that. - What if the question was like-- - No, you don't do that. I think what you do is you go to places like all of the merchants that use Stripe and say, we'll give you a three or four or five percent discount and they'll be like, okay. And so you'll see these prices that just fall everywhere. Like, imagine if Shopify was like to all their merchants, okay, you have two choices. The old way or the new way. The new way, you put another two or three or four percent in your pocket. Of course, they're gonna pick the new way. - Well, and this is the paradox of modern M&A. If you look at protecting the consumer, this will ultimately be great for the consumers. This is gonna lower the prices on it. They're not buying this too. - Okay, you're saying something really interesting. It is so good for consumers if this were to happen. This is the exact reason why, if this had happened two years ago, this would have been the antitrust equivalent of a colorectal exam. I mean-- - Oh God. - You would not even get one step close to doing this deal two years ago. - Well, that's really interesting, actually. I mean, the key question with antitrust is how do you define the market? And so if you define the market as APIs for merchants, then Jay Cal, it would be Stripe Versus Brain Tree and then the government would say, well, you can't consult them and share. However, if the real market is Visa MasterCard, that's the ultimate duopoly. And if PayPal can add competition to that market, which is infinitely larger than APIs, then it's actually pro-competitive. So how you define the market determines whether it's anti-competitive or pro-competitive. - And those guys are smart enough and they've read enough books where they won't f**k this one up. - All right, let's get to the next topic. Somebody else is suing OpenAI this time. It's Apple. On July 10th, Apple filed a 41-page lawsuit against OpenAI over alleged stolen trade secrets. Apple says OpenAI stole their IP to develop their consumer hardware device. Remember, we had Sarah Fryer at liquidity. And I probed her on this new device and she said it was very human and lovable. She gave us a little bit of the goods. Well, it turns out Apple is alleging that maybe this is partially their IP. Tang 10, Apple's former VP of iPhone design, is OpenAI's chief hardware officer. He allegedly directed Apple job candidates interviewing at OpenAI to bring, quote, "actual parts" to interviews, to quote, "show and tell" in the interviews. Chang Liu, former Apple senior technical engineer, sent this text message to a still-employed Apple colleague, quote, "LOL, I found out I can access the network storage so funny." During all of this, OpenAI has poached over 400 Apple employees over the last year or two. Big numbers of poaching Apple and Tim Cook have seen enough Chimalt, Tim Cook, Greenlit this. As insane as this is, Sam Waltman has found a way, found a way to screw yet another party. Screwed Elon, his first benefactor. Chimalt, if you remember correctly, the default for iPhone AI was supposed to be chat GPT. So they took this relationship. Sam took this relationship where he got to be the default on the most important platform for AI, the iPhone. And now it's wound up in a massive lawsuit. What are your thoughts on this? - I haven't really seen Apple act very litigiously in 25 years in Silicon Valley. So that's obviously. concerning data point for OpenAI. They're very reactive. More than they are proactive on these things. So there must have been something that really, really upset them. Agreed. So I don't know. It's going to take a court to sort this out. I don't really want to gossip because like who knows what's actually going on and who said what and blah, blah, blah, but nobody should be stealing things from their former employer. Nobody. Obviously. You're just not allowed. It's just obvious. These people are very, very smart and they're very successful and that's why OpenAI probably wanted them and that's why they wanted them. And you come to them with the collective wisdom of what you accumulated and I think that's sufficient. You don't need to, especially as a senior person, do this. So I just hope that this stuff isn't true because I think I don't think that Sam or Sarah or anybody else there are trying to induce this to happen. I don't think so. Yeah. I doubt they induced it, but I do believe that it's true or Apple wouldn't have brought it. Sachs, when we look at this, maybe you could open the aperture here if you want where you can just go very detail. But the nature of we have a free market. We don't have non-competes in California, generally speaking. You can just complain and that will go where you want. But we have had instances. Waymo famously brought some IP to Uber when they did. Travis and the team said, leave the building. Your job is rescinded. You don't get to bring that information here. In this case, it seems maybe they didn't induce it, but it occurred for some period of time. So take us through big picture what you think is going on here and what it means for the industry. Well, like Thomas said, I have no idea what's going on here. I mean, this is a lawsuit. The facts are all alleged. We don't know. It's going to be adjudicated. So I really don't want to opine on what happened here. But if people want to know a very simple rule of thumb for how to avoid these types of disputes, it's just when an employee leaves her previous company and joins the new company, just don't take anything with you. The only thing you can bring to your new job is what's in your head. Your memories. Your memories. That's fine. Whatever's in your head, you're allowed to take, but never leave with anything else. No, no, no, no, no, no, no, no, no, no, no, no, nothing. Just what's in your health. Okay, that's it. Freeberg any thoughts here on just the number of lawsuits that seem to be piling up over at OpenAI? Bad luck. Couple dots make a line, I guess. Okay, there you go. Very well said. Couple of dots make a line. Okay, SpaceX had a data leak this week. They launched GROC build in public beta at the end of May. The newest coding model, GROC 4.5, Powers GROC build. I've been playing with it. It's extraordinary. It's coding to that work since out of cursor. SpaceX previously told users, Shamath, nothing from your code base is transmitted to XAI servers during a session. But what actually was happening is every time a developer, or according to reports, use GROC build, the tool was sending their entire code base to SpaceX cloud servers without alerting the users. Not just the files that were needed to do that specific coding task, just everything. Passwords, API keys could have pulled up there, all the change logs, etc. The privacy setting was supposed to stop this, but it didn't work. SpaceX quietly disabled the upload on July 13th by flipping a switch on their servers. Elon Musk, friend of the pod, promised on X that all previously uploaded data has been deleted, I guess. And in response, SpaceX Open Source GROC build. That's their harness. So that's another Open Source win or win for the Open Source community and AI sovereignty. I guess any kind of thoughts on this. Obviously, this was not intentional, but trust is important with these models as we've been talking about for the last couple of months here on the oil and podcast. I would actually connect this to my comments on CNBC earlier this week, which built on top of Alex Carp's comments the week before privacy in AI is very fragile and it's very brittle. And this is despite the best efforts of great businesses like, you know, you may not like Elon for personality quirks, but he is incredibly trustworthy. He's overly transparent. And so to their credit, they shut it off immediately. But my takeaway is that there are all kinds of non-obvious data leak vectors lurking in AI. And so if you think that you're going to flip a ZDR switch, zero data retention, which is the magic term that the industry uses to tell you that everything's going to be okay, I think the answer and the message should be it's not going to be okay because you can't guarantee any of it. So the model companies when they give you these zero data retention policies are probably trying their best, but I think the reality is you are leaking information where you don't know it and they despite their best efforts may still have trapped doors that they don't even know about until it's figured out by somebody else like in this example. So all of this speaks to you have to have a stratified ecosystem. You have to have third parties. Now look, that's very biased for me because it's in part what we do for large enterprises at 8090 when we implement our software factory, but the reason why it's working so well is this exact reason. You need an independent third-party layer to interface to these models to manage this exposure because there are trap doors everywhere. And that's what Sochi just said in a really interesting blog post. Did you guys see that? Yeah, I thought that was excellent. The reverse information paradox. That's exactly the takeaway that he left with. He was building on Alex Carp's supposed crash out, you know, the point that Carp made about how enterprises who have technical ability, one control over their compute, models, weights, data, and alpha, but he went further with that idea. I mean, he started with Carp's idea, but then he kind of provided a recipe or roadmap for how enterprises should operationalize that. And what he says is that enterprises have to establish a real trust boundary with private evals, proprietary learning loops inside the tenant, decoupled orchestration, and the explicit right to fine tune their own outputs. So he kind of goes through a litany of fairly technical things that enterprises should do in order to achieve the operational control that Carp was saying that enterprises really want over their AI compute models and data, their alpha. So it's really interesting. I think now there's you know, a virtual almost like college dorm session going on between the leaders of these companies who are brainstorming some of these concepts and now extending them, right? And what's happening is you're starting to see the formation of not really an alliance, but like an ecosystem that is trying to create alternatives to, you know, a monolithic closed model stack, which is where anthropic and to some extent, an open AI want to go is they want you to be locked into their to their stack, right? Their models, their harness, they control the data, you know, all of that. And now you're starting to see all these different companies. And you pay a huge premium for the privilege for them to do it, which is even more insane. So I saw this data and Nick, maybe you can find this companion clip. The companion clip I'd like you to find is Eric Lyman, who's a CEO of RAMP, was on SquawkBox, I think today talking about a new feature where you can manage the token maxing of your employees through your RAMP card. But the data that I saw was that a million tokens on Fable is about $6.56. A million from Seoul is about 26 bucks, which is the same as Quad48. A million input tokens from on GROC is about $1.50, Zux is about $1.50, Elon's about $1.00, and the Chinese models are 50 cents. So on top of the whole data sovereignty bleeding your alpha way, can you imagine that you're paying 56 bucks as well per million input tokens for that risk? That is insanity. I'm using Proplexity Computer and they started supporting GROC, and they already support GLM5 too. So when you're using Quad or OpenAI, you can only use their models. So I started f-ing with the different models, and I gave it all the same basically PRD. And I said, I want to make a podcast player that deep links. So like if we were talking about, I don't know, Mithos, it would play me all the Mithos clips across all the different tech and business podcasts, but make it into one stream. And I was like, this would be like, really helpful for me for prepping for the show and just be interesting. I did it. It took a couple of hours. It cost $11 on the new GROC. It was hilarious how cheap it was. And then adding to this, I don't know if you saw. Sorry, did you try to do it on fabled to see how much more expensive it was? I didn't because I was out of fabled credits on my $200 account. So, you know, look at this clip here, Nick. Play the clip from Eric Glenn. That's kind of interesting. We're thrilled to be launching token spend management today. It's available to ramp in non-ramp customers. And he's exactly right over the last year, I looked at the stats this morning, token spend among ramp customers is run by 21 times. 21 times. 21 times. Not 21%, we're talking about 21 times. That's exactly right. So, being off by a few. pennies as a CFO actually might be quite nice at the rate it's going it might be several dollars and look like I think that for many CFOs they're often very surprised by the bill because what the AI companies have functionally set up is you have a tab you can spend as much as you want it's very hard for CFOs to see per actively what people are spending on and every time they're introducing new models the rates often go up and so there's very misaligned incentives so part of what we're trying to do is make it easy for CFOs to see the spend understand the spend and control it. Thanks. He's saying something so important there because if your engineers are going off randomly in an unguided system and then just ripping through million token at 56 bucks what he's talking about is the eventual downstream impact to earnings and that eventually a bunch of these public market CFOs are going to show up to Wall Street and they will have missed earnings because they're up at some point if things are 21x in every few months somebody is going to miss a quarter. I don't know who but somebody and it's not just going to be you know I was speculating it'll be a few pennies here or there which they'll have to say is because of token spend. He's saying it could be as much as dollars at this rate which also could be the case. I think the point that we're all trying to make is unless you get a control of this and you can directly say how much money you're making this is a bridge to know it. It is a money burning furnace. The good news is this is all creating a massive market opportunity. Sacks, bit tensor sub nets, GLM 5, 2 hosting, GROC 4.5. Now, in clink, in clink, mirror, maraudies, new maraudies, in clink, everybody's now saying hey wait a second, I can give you a better deal. You're paying a two bucks, I can get you one buck. This is no, no, people are paying between 26 and 56 bucks. They should be paying 50 cents. Exactly. Well, you know, and the inkling announcement was kind of interesting because I think the value prop there is, she's explicitly saying that look we're not frontier intelligence, we're just under that. But we're a platform for fine tuning these open models which are much, much cheaper and then you can achieve the result you want based on fine tuning. And so that's really interesting. Yeah. But you know these open models won't be around for very long if anthropic has its way. That's the reason they want to stop it. They have such a monopoly. Of course, you're selling most of the product for 50 cents per million tokens when they're selling theirs for 56 bucks. Of course, you don't want that to happen. Of course, you want to try to stop it. But that being said, they're still growing like crazy, just to be clear. I mean, yes, you know, you are seeing this explosion of interesting things happening with open models. Like you said, you know, the latest crock build is open, thinking machines open and so forth and so on. But still, you know, they're growing. They're still the industry leader in terms of revenue growth. So these things are happening side by side. And I would, I think that the interesting thing is Eric would not have released this ramp product unless CFOs were like, I can't control the spend. Yes. And then he's like, well, here, let me build it for you. And then if enough CFOs essentially turn that feature on and start to rate limit how it's spent because maybe they're not getting the ROI. And the engineer doesn't care about ROI. The engineer is like, I want to use the latest greatest model. Yeah. And they don't need it. Maybe mirrors right. And for 95% of the tasks, you should be at one level lower, especially when it costs one 100th of the cost. But the engineer will never make that trade off because they'll never want to think about it. And also, they're not tied to the money. The CFO is tied to the money. And the engineer wants to go on an exploration on using the latest greatest thing. And if you're booking if you're booking your, if you're booking your travel, you're like, you don't even see the price. You're like, yeah, just put me in business class, put me in a nice hotel. And like the travel department handles that. You're seeing something really interesting. What percentage of you at the gas of fabled five prompts are just average mischugana that should be running 98% 98% yeah. I was using it for stupid stuff that I could be using when for. I think this is my like micro prediction here, Mark Gurm, and who's like the most in the know guy when it comes to Apple. He says, and you know, we got this new CEO coming in for John furnace. Yeah. And he is a hardware engineer. M7 ultra because we're on M5 chips. Now you can get like, you know, 456, 512 gigs of RAM. He says M7 ultra is going to support as much as 1.5 terabytes. That's double what they're already supporting. So if you think about frontier models, like the last generation, this is like an opus level model running on your Mac studio. You guys all use Mac studios, your rich venture capital, whatever. You're like, yeah, I'll take a four or five thousand dollar computer. This is going to change everything. You're going to have employers go, oh, I can just run, you know, 90% of my workloads, 99% of the workloads on the local Mac studio. I think Apple is a screaming by right now. And I did not financial advice, but my lord, that company could just run the table on AI if they get this right. All right. Apple. Yes. Because they just let it go. It's just like the iPhone. Everybody laughed at the iPhone. People overpay. When the first iPhone came out, many people laughed at that. That was it. That's right. He was the big one. I can still hear I'm laughing. No, if you think about how they make money off of hardware, off of their devices, they will put so much downward pressure on Claude and open AI by just putting local models and supporting them with this memory architecture. It's going to be wild when people have unlimited tokens on their desk. I don't know. I don't know if you guys saw this, but there's a very large solar company called Sunrun. They just announced this week that they're making distributed data center blocks that you can put in your house, another company that did it as company called Span that partnered with Nvidia. So to your point, Jason, you're seeing this fragmentation and distribution of edge compute, which I think is a theme. It's definitely a theme. Well, it's also chasing energy, right, Tremoth? Like if you've got some solar, if you've got excess battery power, hey, we power up your batteries that night, shapely. I think I told you this last week, we are so massively short electrons by 2050. The United States of America will be two and a half California's worth of energy in deficit, 2.5 California's the fourth largest economy in the world. We will be short 2.5 X of all of the energy consumed by California by 2050. This week, there was an auction by this huge utility called PGM, which serves Pennsylvania, New Jersey, Maryland, 13 states, and that auction is where they publish a forward curve and say, hey, listen, guys, here's my forecasted load and here's how much energy I need and people signed up to essentially get paid a guaranteed rate every day so that they have to fork over the energy in the future, kind of like a forward option. They needed like seven or eight gigawatts. They had 156 megawatts or something show up. We are in such a bad place right now on electrons and electricity prices. Did you see what our boy did this week? We need, we need, so this is behind the meter, which is different and he, Elon needed to do this by the way, just so you know, because there's an issue in Memphis where he was very clever about how he was able to get colossus off the ground. That regulatory, it's not. Well, when you try to power a data center, typically you have what's called grid power. So you go to the utility in the area and you say, hey, please run me a line off of that main transmission line and that's how you power your data center. When that runs out or is so backlogged, you have to do what's called behind the meter, which means on your own property that you own, you build something for yourself. Now there's a problem with that. You would think, well, that's smart. Yes, but like in everything in America, there's regulation on top of regulation on top of regulation. And one of the most complicated regulatory schemes that you have to overcome is clean air permitting. So even if you say you're going to do behind the meter, then you're like, well, what can I do? Solar, you can do, but it takes too much space from most places. Batteries you can do, but you need to generate the electricity in the first place. So people use that gas. So Elon cleverly bought a ton of 18 wheeler engines, basically. He bought me that, making sure of this and then just pin them to the ground and ran it. And those are personal use essentially. So they came under the clean air permitting requirements. But then when you act as a block, you could make the claim that it doesn't. Now there are new solutions like blue energy, which allows you to have huge installations and still fall under the personal use clean air permit. So for all of Elon's future capacity, he needed to have this in place so that he gets the clean air permits and he's able to have a clean run of sight to continue to build domestic data centers. Anyway, there's your little TED Talk on energy, but we are in a bad place, guys. And it's only getting worse. Speaking of data centers, sacks, everybody's favorite socialist governor Kathy Hochill in the great state of New York, my hometown. Powered by fossil fuels, they drive up our carbon footprint. They occupy massive amounts of land, potentially displacing agricultural space and open spaces. The bottom line is production arrives to higher utility bill, deleted water supply, or noise pollution. So we have no choice which would address these challenges created by these massive facilities. That is why they'll be signing the nation's first ever statewide moratorium on hyperscale data centers. Everything she's saying there is a false accusation on the data centers. Let's just go one by one. So she's saying that they eat up all of the power. Well, yeah, I mean, look, if you connect to the grid without producing more power and you force data centers to compete with residential rate payers, then yeah, you could drive up utility prices. However, if you do a charmasse and let them build behind the meter, then they bring their own power. And that's what the president has advocated for since the beginning of his administration is let the AI companies become power companies. So that is the way to solve the energy problem or the utility problem. Then she's talking about eating up land. The reality is these data centers are a model of land use efficiency. We have a fun of land in this country. Obviously, you can find places where there is enough open land to build a data center, the economic impact and value of a data center relative to the land use again is one of the best oral eyes there is the supposed noise pollution that's largely made up that can be dealt with. You obviously don't want to put these things right next to a residential area, but create a little bit of distance and it's fine. The whole water consumption thing is largely a hoax so that the the modern data centers recirculate the water blows loop systems. Yeah, and I think there was a study that showed that a typical data center uses the same amount of water as 2.5 in and out burgers. So in and out burger chains. I mean, just go after the almonds if you're concerned about water people. Yeah, or golf courses. I mean, there's many, you know, there's many uses of water that are way more wasteful. So when you compare economic impact to all these different things data centers are like honestly, one of the best things we can be building as a nation, but and tax there's all these taxes and incremental revenues. Did you see the article where I think it was in North Dakota or something where like teachers were getting like 30 and 40 thousand dollar bonuses from all the tax revenue that was coming in. There's all these upsides. That's right. They generate a lot of tax revenue. They've created a blue collar construction boom. It's not true that there's no jobs once they're built that you do have ongoing jobs there. And then one final thing, just on the point that Hocal is making she said it created a lot of pollution. You natural gas, which is how most of these data centers are powered is one of the most clean burning sources of power that we have. 100%. These data centers become the scapegoat for all the angst that people have about AI and it's kind of become this very clumsy way of trying to throw a wrench in the gears of innovation and just kind of slow the whole thing down. Well, all I have to say is welcome to Texas. We got plenty of land here. And for now, so stupid about her proposal and her talk aside from the things she's got completely factually incorrect is New York State is like 80% underdeveloped. Drive up state folks. You're thinking of New York City. Yes, New York State is packed. You go up state. It's literally 70 to 80% of the land in New York state is undeveloped. There's so much land. It's ridiculous. New York is giant. It's giant on this topic this week. I just want to give a shout out to Senator Dave McCormick. He had a defense and innovation summit in Carlisle, Pennsylvania at the Army War College. Which a bunch of us went to. Potus came, gave a speech, had a CEO round table, a lot of defense company CEOs, et cetera. But Chris Wright was there. Sachs. And my guy, he's great. And Chris mentioned this in in same story. He said, you know, there is a lot of common funding because Dina Powell asked this question on stage. And he said, there's a lot of common funding patterns of these people that are protesting the data centers. And he said, you can actually trace it back to the same people that in a different era were protesting fracking. And so he was saying like, these are all just hobby horses that they use to raise money. Have a job. They're like professionally paid protesters. They kind of just show up out of nowhere. I didn't realize that there was such a commonality. But they're the same people. The thing that I just can't understand for the life of me is why andthropic is still funding these groups that want to put the Kabash on new data center construction. There's one called public first where Dario just gave his first seven figure contribution. And then a bunch of other employees at andthropic gave it. And you know, all these groups are trying to slow down AI developed with new regulations and making it harder to build new data centers. And at a certain point, you just have to wonder, I mean, is this regulatory capture or they just kind of lost the plot? Because the number one thing slowing down the growth of anthropics revenue, it's not demand. I think it's the availability of compute in data centers. And so you're just kind of wondering like, what is the point of all of this? It's true. I was talking to someone in politics about this. And the theory that they had is, well, the Democrats aren't going to pause the data centers forever. They're going to pause them until they feel like they're in enough control that they can dictate all of the rules. And so in other words, they're calling this a moratorium. And I think it does mean that the data centers are going to stop. But eventually, they're going to be in a position to say, okay, here are our terms if you want to turn these things back on, right? You want to lift the moratorium. And then that's when we get this, you know, big government Democrat defined AI regime. And you know that it's going to consist of a new regulatory agency and you speech controls, a whole trust and safety agenda from social media will be ported over. That's this was this one person I was talking to. This is what he was speculating is a real agenda is that eventually once Trump is no longer president or in some future Democratic administration, they will eventually lift the moratorium, but on their terms. Now, I think that's a really dangerous thing to do because, you know, Trump is president for another two years. And then no one knows what's going to happen after that. And even if you lift the moratorium in, say, two and a half or three years, it's going to take a couple of years for those projects to even ramp back up. So when you start talking about a moratorium on data centers, it's not like us a few months pause. It's probably a good five years, at least before, you know, you can get another data center switched on in the state of New York. Just so you know how bad it's gotten. There's a curve that you can use to price data center assets. And I think you guys know this, but I have this portfolio of these assets that myself and my partner, Anita, have accumulated. And what's so interesting is when we talk to all of the hyperscalers about giving us a price, because we're trying to figure out whether we should keep it or build it or just sell it, the most incredible thing is how extreme the price is at the front end of the curve when you have verifiable, energizable power today. And the reason is exactly everything that you're saying, Sachs, which is that when you look out into the future, you know, we've said this before, but it's about 40% of all these projects are getting mothballed and stopped. And so it's creating this massive deficit of available energy to actually drive the use of AI. So to the extent that you actually want, you know, drug discovery or you want cancer diagnoses or you want better health care or better legal advice, we may actually not be able to service it based on all of the demand that exists because the power isn't there, the energy isn't there and the reason why that's not there is because folks are just kind of reflexively protesting something that they don't completely understand, clearly. So I think it's a really big problem. I mean, we're going to have GPUs chasing energy, like where's their energy and just drive the GPUs there is what's going to happen, right? Let me add one layer to it, which is they're normally trying to stop data centers from being built in the U.S. They're trying to stop data centers from being built internationally in our friends, allies and partner countries. And the way they're doing that is the same political forces that are stopping data centers are also behind all these new export controls on chips. So they want to make it harder and harder to export chips to more and more countries, including our friends and allies. And so there's not going to be data centers here. There's not going to be data centers in our allies. I mean, where are we going to put these things? Yeah, I mean, all those allies have unlimited energy, Middle East. If you want some data centers. Well, what's funny, Jason, is we did a bunch of Middle East data centers stuff. And then it's kind of stopped. Meaning like there wasn't this growth that I thought would happen because it's a very conveniently placed geography. It's the Middle East for a reason. And so, you know, you can serve four billion people very quickly and under 200 milliseconds from there. Instead, what happened was there was this explosion in Asia, specifically in Australia, which kind of surprised me because I would have thought that those folks are a little bit even further out on the DSA, you know, far left. I thought these things would not have happened, but they were able to get big deals done. So in this weird way, you have all of these other countries kind of running to try to embrace this stuff quickly. They've done a decent job. They're doing stuff to sort of like, displace some of the energy that that is needed in the U.S. But the problem is we need to have enough surplus here because this is where most of the commerce is gonna get created that really, that I think she's over. - These are luxury regulations. Like you can afford if you're New York state or California to be like, "You know what, we don't need this. "It's a luxury for us to have an extra day." But Australia, you might really need the money. If you're Texas, you might really want the money. - So this is what's amazing. - Like virtue signaling only goes so far until your debt to GDP is high enough and/or your productivity is low enough and/or your foreign direct investment is low enough where you're like, "Yeah." "All right, you know what, screw all that. "We're just gonna build the data center." But the other thing is, if you saw what happened this week, the UAE now is able to import the best in class leading chips. And so to your point, Jason, I think it restarts this cycle where you have to look very carefully at the Middle East 'cause it's a very attractive place to build these things. - And by the way, how do you solve the? - Even if you just, if you think about fiber and the milliseconds as you're talking about, yeah, she can get to the foreboding people. But I don't know if you saw the giant starlink versions now. They make like a really big version. I think it's actually got like one of the enterprise versions, but there's like an even bigger enterprise version. And they can bundle them together and you're starting to get to like 10 gig, 20 gig setups. So that means you can start putting these things almost anywhere. - Yeah. - Which gets also like, - Can I, can we see your clip, the thing that you were mentioning before? This is not, to your point, as prevalent in the Middle East where you have monarchies and governments that aren't ruled by democracy, but in democracies we see this anti-data center movement taking hold. This chart is something that, for me always kind of played a role in my understanding of where the incredible anti-GMO sentiment came about in the United States. - That was great. - Russia today, this Russian media outlet, launched in the US in 2010. They were kicked out of the US by Biden in 2022. And you can see that prior to Russia today existing in the US, there was no anti-GMO sentiment. GMOs were around since 1996. That's when they first had their big commercial launch in the US and were pretty prevalent for 14 plus years before everyone started to think GMOs are bad. We got to get rid of GMOs and you could ask people a hundred different ways, very pointedly and specifically about the facts on the matter and the science of GMOs and all this sort of stuff. But everyone always had a reason why they didn't want them similar to what we're hearing now with AI and data centers. And it turns out that if you track back all of the media that had all this anti-GMO sentiment that ultimately got picked up by the mom bloggers that ultimately got put into social media feeds that ultimately everyone just accepted as truth. A lot of it originated in this Russian media push that happened around this era. And you can actually see this on the Google trend data that shows GMO and it's kind of right up. And then it's Russia today started to get cut by different media outlets and people stopped retweeting them and stopped reflecting them and stopped writing articles that followed Russia today, the anti-GMO sentiment declined in the US. And I think you can see this going back decades. There's this effort that the KGB kind of designed during the Cold War called directed measures which was really meant to try and create an influence campaign through affecting media. So putting this kind of propaganda out through foreign media, particularly targeted Western democracies. And you know, you could argue that maybe you could trace back what happened in Germany with nuclear energy as being kind of similarly originated. But there have been a series of these pushes that seem nonsensical if you're fairly rational and can have an actually objective debate about the scientific merit, the economic merit, the benefits of these technologies. But for some reason, what we call the activist community become heightened to them, say that we've got to get rid of them and everyone's got these different, unfounded, scientifically unfounded reasons why they want to get rid of them. And you're like, wait a second, how did we end up in this place that we're literally handicapping ourselves? And I think we're seeing something similar happening with data centers in the US today. The funding of the NGOs as they're being called, the media that's supporting this, the retweeting of the media. And then you asked people, there was a poll that came out today, something north of 50% of Americans believe that data centers increase the cost of water and electricity. Even if the data center is fully recycling the water and they're producing their own electricity, there's still this kind of repugnant reaction to the data center. And so there has been this like deeply sewn psychological shift that's happened in the United States. And you know, people have these, well, I hate the rich, I hate tech, I hate AI, I don't want any of the stuff, I don't want any of the stuff. But where does it all come from? I do worry that there's some degree of kind of call it foreign, you know, influence. I don't love the word influence because everyone kind of, everyone captures it up, but there is some degree of this like. - Well, I just, there's foreign interests. Let's call it that. - No, I think it's more than that. - There's just one month ago, just one month ago, open AI published a blog post called PRC Link to Influence Operations are targeting AI debates in the US. And Politico covered this and a lot of other sites covered this. Basically, what they are saying, and in fact, many people are saying, is that China is behind a lot of these influence campaigns to shape US attitudes on AI data centers. - It makes sense, it makes a lot of sense. - Yeah, and there's kind of a congressional investigation of this. It does make sense 'cause it is in their interest, right? If they can stop us from building this necessary infrastructure, then that's a way for China to win the AI race. - If they can, can I just understand that? - Can I just understand that? If they can incentivize anthropic to, you know, pull the ladder up, if they can kill open source in the United States and constrain demand or the optionality and choice of lower cheaper models, think about that for a second. At $56 per million input tokens, I mean, versus 50 cents for the rest of the world, all of a sudden it doesn't take a company that's much, much worse than you to beat you when your cost is 50 to 100x more. - Right. - That's just the math. - The math thing? - The math thing. - You know, it's, Sasha made the point that these enterprises are not just paying for AI with money. They're paying again by feeding those frontier models of proprietary knowledge, right? And all they're, they're alpha. So it's like a double whammy. It's like it's more expensive and you're potentially mortgaging your future. - Look, let's be honest, it is obvious where foreign governments have an enormous incentive to try to manipulate and influence the comings and goings in America. I think we should just acknowledge that. The idea that that doesn't happen is very naive. Now the question is we have to be able to call it out and put our finger on it because otherwise, what is clearly happening is that there's a lot of Americans that will just fall for this (beep) and they will not think from first principles. - We have a huge moral panic going on with respect to AI. Look, when you talk about catastrophes that could result from AI, what are we talking about? We're talking about things that might happen in the future. Nothing resembling this has happened yet. Even the cyber risk that everyone's been talking about. - Job loss. - Or job loss. - Job loss. - It's like, none of it's turned out to be true. We haven't seen any of it so far. But we're on the threshold, I think, of destroying the crown jewel of our economy, which is the system of free market innovation that we have, this culture of rapid iteration of anyone with a good idea can go raise brisk capital and start their idea, start their company. And we're on the verge, you know, now we're talking, I think about how far the over-to-window has moved, where we're actually saying that creating a finra for our industry might be better than all the alternatives. Finra is a bunch of stock brokers writing rules. And when's the last time there was ever any innovation in that sector? I mean, I guess Robinhood made trading free. That was it, right? - Yeah, that was a big one. - Yeah. - That was a flow. - Okay, but that's not real innovation. Okay, that's like an innovation with respect to a pricing model. And we're actually saying that that might be the least bad alternative is having the equivalent of a bunch of stock brokers creating new rules that all these AI companies are not gonna have to buy by. - It's crazy, we're gonna throw away the lead that we have in this, and by the way, Kimi K3 just came out and people are saying it's not right up there. It's very, very close to the frontier. We may have months on China if that. And we're gonna create all these crazy rules and new regulatory bodies for risks that have not manifested yet. - It's worth monitoring the situation, but it's not worth panicking. Like you should monitor the situation with self-driving cars and job loss, China is certainly doing that. They just stopped giving out permits for self-driving cars as an example because it's going so well, and they're losing jobs, and there are people who are getting, there's a little civil unrest, so they just said we're gonna make self-driving cars licensed, and so they're not giving out anymore license, work-tourium on license for now. It's worth watching mythos, and if it could hack your system, pedal off the networks, checking it out, other people checking it. It's all worth monitoring, but yes, there's no disaster here at A because of AI. Nothing's jumping out of your chat GPT window. You know, the worst case scenarios, you blow out some tokens, you know? Okay, great. That's the biggest. - There's only a handful of companies that are even at the frontier, and they all have safety testing and red teaming and all the rest are doing a good job. - Yeah. I'm not saying stop that. I'm just questioning whether we need some vast regulatory apparatus now to start doing all this room. - It's certainly premature, and we did this because of science fiction and Dario saying all jobs are going away. I mean, that was the most ridiculous thing. when he said it's like he's panic that it's going to be 80 or 90% jobs in 20. He said with it, he said 50% of entry-level knowledge worker jobs are going away within one to five years. That was one year ago. So it's a little ridiculous, yeah, I mean, it's, he's been in a state of panic since GPT-2. Yes. Yes. I remember they wanted to have regulatory approval for models that use 10 to the 25th flops, right? And every single AI model is like, well, passed that threshold now. And we haven't seen any of the, the, the harm. Look, they thought that 10 to the 25th flops would be enough compute to create, you know, the terminator, you know, to create sky net. No offense, freeberg. But one guy's panic attacks, one guy's anxiety condition might have shaped the whole course of history here. Like, Darryl, have like, I'm not making light of it, but does he have an anxiety issue where he's like overly concerned about this stuff? Or is it just delusions of grandeur? Come on the pod, Darryl, invite's open. Come hang out. I'm sure you'd love to come on the pod after you just accused him of having a panic attack. But I mean, he seems like he's in a perpetual one. No, let me tell you, listen, I, it could be psychological, but I actually think that there's a strategy that makes a lot of sense and it's a very simple, straightforward strategy. Number one, brand yourself as a safe AI company. Number two, and unsafe AI. Three profit. Yeah. There you go. That's a strategy. Kind of brilliant. All right, everybody. Go to awlin.com/events and sign up for the all in summit in September, scholarships are open. Let's do a quick, amazing, deep, robust science corner with our boy, David Freedberg. Before we get into the science corner, I'm going to give a shout out to Ronnie Dogg for adoption. I love family dog rescue in Sonoma. Check out his Instagram link. God, here he goes. In the description, this dog needs a home. He was fostered and he lost the foster home. Someone come and grab him. He's awesome. All right. Let's get into science corner. This is what we've been trying to, try to get more cue points. That dog looks delicious. Talk her. Talk her. Talk her. You don't live in Sri Lanka any more, Chema. Yeah. Oh. We can do it. We can take it as great. How do you baronate that dog in Sri Lanka? Do you like a little yogurt and garam masala? Maybe do. Do you want to talk about reversing aging? Yeah. I want to talk about that. I got to drop. All right, guys. I got to go to the apple tower. All right, so, Chema, you can drop, too, if you want. I'll cover science corner solo. In the past, we've talked about Yamanaka factors, which are these proteins that can go into cells and reverse the aging of the cell and the cell starts to act young again. Pretty amazing. There's a lot of advancement happening on that front, but this paper that came out just this week that everyone's kind of going crazy about was put out jointly by Calico, which is Google's age reversal startup, that's super secretive, that they're not a lot of talk about in partnership with a group called Rebel Pharma. What they focused on was what's called the extracellular matrix, the parts outside of the cell that age. What does aging actually look like outside of the cell? Well, over time, sugars and fats bind to proteins in the area between our cells, and they accumulate. They don't get cleaned off. As they accumulate and they don't get cleaned off, they make it harder for your body to clean out that area, to maintain that area. It causes stickiness. It causes binding, and that reduces mobility and ultimately leads to things like wrinkles in our skin. Is that part of our joints? Is that what visual patterns? No, it's called glycation, and so it's the binding of sugar and fat to the proteins that sit in that extracellular matrix in between the cells, exactly. It's that whole gunky area in between the cells that when you're young, works well, everything smooth. The proteins get replaced if they break down. As you get older, sugars and fats stick to these proteins, block them up, and as they get blocked up, your body can't repair them, it can't clean them, and more importantly, it changes the structure and the shape of those proteins. Things like collagen that are far apart stick together, and that causes things like wrinkles, and that causes immobility. It also causes inflammation, because then those proteins kind of look different than they're supposed to, and your body starts to attack them, and that activates inflammation, and that's why we get one of the reasons why we get more and more inflammation as we get older. One of the key, what are called advanced glycation end products, that's the term for these things is called CML. CML is kind of the predominant molecule that gets formed in this extracellular matrix that's driving aging, and nothing breaks it down. These scientists set out to try and create an enzyme, and enzyme is a protein that breaks something down that can break down CML. Remember, a protein is just a series of amino acids, and those amino acids are programmed by DNA. You can put three letters of DNA to make an amino acid, so you can literally just print DNA, and then put it in the bacteria to print proteins, and then test those proteins to see what they do. That's the modern era of protein synthesis and protein testing. These guys kind of went out and they took the target, which is CML, and tried to figure out, okay, how do we actually degrade CML, clear that extracellular matrix and reverse aging? And they started with alpha-fold, and they used alpha-fold to find a protein that could bind to CML and activate an enzymatic process that would break it down, and then they took that protein from alpha-fold that comes out of a bacteria, they produced it, they started to test it, and then they started to find some of the binders or the parts of that protein that they could make better, and they used DNA programming to change it. And they made hundreds and then thousands of variants of it to measure activity, which is how good is it at breaking down the CML? And they did this recursively, five different cycles, and then eventually they tested it. Once they kind of gotten it breaking down the CML really well in a test tube, they started to test it on the proteins that we would find in our body, Cassine, collagen, retinal proteins, which are in your eye, hemoglobin, and they were able to get rid of 52% to 97% of the CML, just degrade it away. Then they found several sites where they were able to degrade over 90%, and then they took actual human skin from elderly patients that had donated their skin, and they put this enzyme onto that skin, and they were able to eliminate 55% of the CML on the skin, which basically reversed the skin's age down to the age of a 31-year-old. This is from greater than 70-year-old patients, just by putting this enzyme on the skin. And so it's kind of a groundbreaking demonstration of combination of alpha-fold, what's called directed evolution, where you change the order of the DNA that changes the structure of the protein to test different proteins, do high throughput screening, and ultimately make a novel protein that doesn't exist in nature today that can do something pretty profound for human health. Now the next set of questions is, okay, well great, this enzyme is awesome, how are we going to get it into our bodies, how are we going to get it into that extracellular matrix? Is it going to be a cream, is it going to be a shot, a supplement? Could we eventually take an RNA shot that makes the protein inside of our body and starts to do the degradation from within a lot of questions kind of still to be answered? But it really, I think, likes a great path forward for these novel therapies that we're developing. It's fucking awesome. You know, all my, I got all these joint pains in my hip and my shoulder now, like everything you can feel yourself getting older. Well, that's, I will tell you this right now, that will not be the first market. The first market will be cosmetic and cosmetic skin. It will be a trillion dollar market. You can create a queen. I mean, if you could put this enzyme literally on your skin and have it absorbed in. On your face as a cream. Yeah, came over. It's a, it's a, that alone is two trillion dollars. I mean, dude, AI, let's just talk about the applications of AI, why it's actually awesome, that everyone should be able to agree on it. You can't be convinced by some foreign siaop. This is fucking awesome. I mean, this was alpha-full. It's amazing. It's amazing. It's amazing. It's amazing. It's amazing. It's amazing. I mean, dude, AI, let's just talk about the applications of AI, why it's actually awesome. That everyone should be able to agree on it. And you can't be convinced by some foreign siaop. It's amazing. It's amazing. You've to discover this thing and evolve it and drive this outcome. Everyone can benefit from it. I love you too. We should all just get a room and just have one big huge or two because they're all just stuff. It's like this like sexual tension that we just need to release that out. What? You're the beef. What? You're a beef. What? You're a beef. What? You're a beef. You're a beef. What? You're a beef. You're a beef. What? You're a beef. [BLANK_AUDIO]

Podcast Summary

Key Points:

  1. Demis Hassabis of DeepMind proposes a self-regulatory organization (SRO) for AI, modeled after FINRA, to oversee frontier AI models for risks like cybersecurity, biological threats, and weapons development.
  2. The SRO would be industry-run, voluntary initially, with independent experts assessing models, and would report to government bodies like Congress for oversight—avoiding government overreach.
  3. Key conditions include broad industry representation (startups, open-source), only reviewing frontier models, focusing on catastrophic risks (cyber, CBRN), starting voluntary, and acting as a substitute, not an addition, to government regulation.
  4. Critics, including Dario Amodei of Anthropic, warn the proposal may be a stepping stone to broader government control and regulatory capture, especially if dominated by large tech firms.
  5. Anthropic is accused of a "regulatory capture" strategy, pushing states to impose stricter AI rules, creating a patchwork of regulations that harm innovation.
  6. A major private equity deal is forming between Stripe, Advent, and Block to acquire PayPal, leveraging combined infrastructure (payment rails, stablecoins, consumer accounts) to challenge Visa and MasterCard.
  7. The deal highlights the growing trend of "AI-native" capital firms reviving legacy businesses through operational improvements and AI integration.
  8. Apple has filed a lawsuit against OpenAI alleging theft of trade secrets, involving former Apple engineers now at OpenAI.
  9. SpaceX’s GROC build tool was found to secretly transmit users’ full codebases, exposing critical privacy flaws in AI tools despite claims of “zero data retention.”
  10. The industry is responding with a push for third-party, independent AI orchestration to prevent data leakage and maintain control over data, models, and costs.
  11. Token pricing disparities reveal that some open models (e.g., GROC, Chinese models) cost just 50 cents per million tokens, while others (e.g., Fable) charge up to $56—highlighting cost inefficiencies and financial risks for enterprises.
  12. A growing ecosystem of open-source AI platforms is emerging, enabling cost-effective, flexible, and privacy-conscious alternatives to closed AI stacks.

Summary:

The podcast explores key developments in AI regulation, corporate strategy, and innovation. DeepMind’s Demis Hassabis proposes a self-regulatory organization (SRO) for AI, modeled on financial oversight bodies like FINRA, to independently assess high-risk frontier models. The SRO would be industry-led, voluntary, and focused on catastrophic risks like cyber or biological threats, avoiding government overreach.

Critics caution it may be a front for deeper regulatory capture, particularly by powerful firms like Anthropic, which is allegedly pushing for state-by-state AI restrictions to create a fragmented regulatory environment. Meanwhile, a major private equity deal between Stripe, Advent, and Block to acquire PayPal is underway, combining their payment networks, consumer bases, and stablecoin infrastructure to create a direct challenge to Visa and MasterCard. The deal underscores a broader trend where capital firms are reviving legacy tech businesses using AI for efficiency and cost reduction.

On the AI ethics front, Apple sues OpenAI over alleged theft of trade secrets, while SpaceX’s GROC tool is exposed for secretly sending user code to servers, revealing severe privacy vulnerabilities. This incident highlights the fragility of AI trust and fuels demand for independent, third-party AI orchestration to manage data exposure. The podcast concludes that open, cost-effective AI models are emerging as viable alternatives to closed systems, with token pricing disparities showing drastic cost differences—some models costing as little as 50 cents per million tokens.

This shift is driving a new ecosystem of AI tools and platforms, enabling enterprises to regain control over their data, models, and spending, and positioning open-source AI as a critical force for innovation and financial sustainability.

FAQs

Demis Hassabis proposes a self-regulatory organization (SRO) modeled after FINRA to oversee AI development. Industry leaders would voluntarily submit their models 30 days before release, with assessments for risks to cybersecurity, national security, and biological threats. The body would be independently run by tech experts, with federal oversight but no direct control, allowing faster adaptation than government regulation.

The industry has better expertise in AI technology and can adjust rules faster than government agencies. A self-regulatory body avoids delays, reduces regulatory capture, and allows innovation without stifling progress, especially given the rapid pace of AI development and the government's limited understanding of current models.

The SRO must have broad industry representation (including startups and open-source), only review true frontier models (not incremental ones), focus solely on catastrophic risks (like cyber or biological threats), start as voluntary before becoming mandatory, and act as a substitute—not an addition—to existing regulations.

Concerns include potential regulatory capture, especially if large players like Anthropic dominate the body. There's also fear that the SRO could be a stepping stone for further government overreach, and that political pressure could influence decisions, undermining independence and transparency.

Anthropic is pursuing a strategy of state-by-state regulation, making rules increasingly strict in each location to create a patchwork of regulations. This is seen as a form of regulatory capture, aiming to pressure the market and limit competition, especially in open-source and AI innovation.

The 'FAA for AI' would require lengthy certification processes (like 5–9 years), delaying AI development and potentially giving China a competitive advantage. In contrast, the SRO approach enables faster, industry-led development and avoids the risk of a government-mandated, slow AI race.

Chat with AI

Loading...

Pro features

Go deeper with this episode

Unlock creator-grade tools that turn any transcript into show notes and subtitle files.