AI 行业能自我监管吗？Stripe 欲收购 PayPal、中国追赶、纽约叫停数据中心

Jason Calacanis (00:00:00): Alright, everybody. Welcome back to the world's greatest podcast, the number one podcast, your favorite podcast, the all in podcast. I'm Jason Kallikanis, the world's greatest moderator. With me, of course, Shmoopalaihapativ. Great. Chamath Palihapitiya (00:00:13): Great. Great. Great. Great. Great. Great. Great grandchild, Jason was, of a hooker. Jason Calacanis (00:00:20): You saw that from France? Chamath Palihapitiya (00:00:22): And a purse snatcher. Jason Calacanis (00:00:25): Is this comes from, like, a history of France. Some history chemists said they let you out of this was a this was the deal in 1719, Saxe. If you're a prisoner in a in parish, 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 are taking the deal? Chamath Palihapitiya (00:00:47): It explains a certain of your proclivities, J. Cal. Jason Calacanis (00:00:52): I thought you were asking me to see if they would extend the rule for you. Chamath Palihapitiya (00:00:55): No. I'm saying that your great, great, great, great, great, great grandma. Jason Calacanis (00:00:58): I'm not he's David Friedberg (00:00:59): a hooker. Jason Calacanis (00:00:59): I'm Greek. Chamath Palihapitiya (00:01:00): That's what I'm saying. Very explicitly. She was I Jason Calacanis (00:01:02): think never we never spent time in a prison. Also, of course, David Freeburg is here. How you doing, brother? David Friedberg (00:01:09): Living the dream. Yeah. Good to be back. Missed you guys last week. How was Brad? How did he fill in? Jason Calacanis (00:01:14): Brad was great. David Friedberg (00:01:15): Yeah. Yeah. Jason Calacanis (00:01:16): He was great. David Friedberg (00:01:16): Count victory lap? Jason Calacanis (00:01:18): Yeah. A little victory lap. We played chariots of fire. And how was your special time at blank and your time next week at blank? David Friedberg (00:01:29): Thanks for thanks for having me on your show, Jago. Jason Calacanis (00:01:32): Alright. We got a full docket today. Lots of stories. Let's start with, DeepMind's Demis Hassabis just dropped an AI regulation proposal, and it's pretty popular with the boys. In an X article, Demis called for a US 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 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 slowdown in development if the situation demands it. I guess that would be if, there was a cyber risk, etcetera. Looks like, on the positive side, we have Elon who said it was thoughtful, Sam at OpenAI, Jack Clark at Anthropic, Sundar, Satya, Jack Dorsey from Block, the Carlson brothers. So Freiberg Freeburg, your thoughts on Oh, well, way to read it way to really, Chamath Palihapitiya (00:03:00): put in the effort today. Go ahead, Jason. Good. Good. Jason Calacanis (00:03:03): Just pass it to me, James. I'll take care of it. God. David Friedberg (00:03:05): Let me let What what do Jason Calacanis (00:03:06): want me do? Oh my god. What an incredible topic. Me the mic. Here. Let me do it. You want me to do it right? 3 two. David Friedberg (00:03:11): Us actually care about this topic. Let's go. Jason Calacanis (00:03:13): Okay. Yeah. You care about it. Okay. Here we go. 32. Here's a clip of me calling it on the All In podcast first. The whole industry is gonna 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 MPAA 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. Breibreich, would you like to congratulate me on nailing it again? Chamath Palihapitiya (00:04:00): Well, first of all first of all, I thought that Demis' 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 Jason Calacanis (00:04:10): totally I can't win, Sachs. Even when I nail it, I hit a half court shot. Tremont's like, move Chamath Palihapitiya (00:04:15): the net. Move the net. David Friedberg (00:04:18): 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. SROs 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 trading risk with one another. So the industry doesn't wanna have exposure, and they certainly don't wanna 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, 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 kind of rules and requirements actually map 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 FAA, 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 frigging 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, etcetera, etcetera, that independent body can get voted on, can get changed over time. David Friedberg (00:06:16): And because they actually have expertise in running software evals 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, Jay Kal, and 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 with it 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 gonna have oversight ultimately. Chamath Palihapitiya (00:06:49): Did Anthropic and OpenAI have a point of view? David Friedberg (00:06:51): 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. Jason Calacanis (00:06:59): Which means they're on board. Sachs, is this 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? David Sacks (00:07:16): Yeah. And I, you know, 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, would 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 the AI race. So I think an SRO approach would be infinitely better than that if it was done right. And I outlined for Demes five criteria or conditions that I thought were really important in order to make this work. And if I could, I'll just Yeah, run walk through. Through 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? Can't just Jason Calacanis (00:08:28): be The fix can't be in. Right. David Sacks (00:08:29): 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 reg capture. So for example, I think if you had Jensen, Elon, Zuck, and maybe Mira, because she just launched a very interesting Open weight platform that's based on David Friedberg (00:08:50): open Keeping machines, yeah. David Sacks (00:08:52): Yes, exactly. Then that I think would address the red capture problem to a large degree. So that's number one. Number 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 Chamath Palihapitiya (00:09:28): that's So they have where to be in maybe the Jason Calacanis (00:09:30): top 10 performers, top 20 performers on the benchmark test? David Sacks (00:09:33): No. I think when they benchmark on key dimensions of intelligence, they have to represent an increase above If where the current state of the art 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 risks only. And to my knowledge, those right now are cyber and CBRN, meaning it's, you know, chemical, biological, radiological, nuclear. So it should not be things, for example, like disinformation or microaggressions. This should not become a speech regulator, you know, 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 Demis 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 an 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 Demis said, I mean, he didn't put all these points in his blog post, 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 could 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. David Sacks (00:11:17): 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 wanna 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. What 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 I'm not even sure how major the changes need to be, it takes three to five years. So the Boeing seven thirty seven 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's not gonna 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. David Sacks (00:13:08): 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. David Friedberg (00:13:19): And your point, it can restrict open source. Yeah. Can't restrict open source. 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. Jason Calacanis (00:13:34): Shammoth, any thoughts on this new self governing body? Chamath Palihapitiya (00:13:39): 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, 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 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's proposal makes a ton of sense and we should just get on with it. David Sacks (00:14:40): Well, 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. Even 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. It reports into the SEC. And so, you know, if we are gonna set this new SRO, where is it gonna report to in the government? There's gonna 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 Chamath Palihapitiya (00:15:19): regulator No, for think you're right. But those issues are important. But my point is, Hax, 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. David Sacks (00:15:37): For sure. And that's the crux of my argument is it's definitely the lesser of 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 and more. And frankly, this all goes back to anthropics, government Jason Calacanis (00:15:54): They poke relations the tiger. They poke the tiger. David Sacks (00:15:56): Yeah. Well, it's more than that. Chamath Palihapitiya (00:15:58): They're funding the need for the tiger. David Sacks (00:16:00): Yeah. I wanna give an update on that actually. Jason Calacanis (00:16:02): I would say poking the tiger of like the American public getting really freaked out and then the government settling Totally. David Sacks (00:16:08): And there's a couple of data points on that actually. I just wanna 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 take or 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 3,000,000,000,000 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 Chamath, 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 Anthropic 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 a line 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. And 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 Sharp ecosystem. David Sacks (00:18:09): Again, everyone went crazy at the time. I think now there's plenty of evidence showing that this is their agenda. And Jason Calacanis (00:18:16): And by the way, they're gonna win that because states have great sovereignty rights and, like, we're seeing what's self driving. The states are gonna decide. It's not gonna be a federal mandate. The states get to decide just the nature of the David Sacks (00:18:27): Well, look. The the reason why Jason Calacanis (00:18:28): They're gonna gonna win on that in a couple of states. Right, Sax? Just really They've won in a bunch David Sacks (00:18:32): of states. They already won 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. There's hardly anyone in government who will ever say, Oh, no, no, no, we're not qualified. Like, we don't Jason Calacanis (00:18:55): want We're for less have government. David Sacks (00:18:57): Yeah, there are very few people who are principled that way. And most people in the government will say, thank you very much. What else can we take? And this is the mistake that I think a lot of people in the tech industry are making is they think that they can just buy off politicians or 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, think these companies are gonna have to grow a spine and fight and decide where they're willing to draw a line. And if Demes' SRO is the line, if they're saying, okay, we think this is the right solution and we're gonna 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 kinda offering it up for free and all these companies are just gonna say, oh, yeah, regulates. 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. Jason Calacanis (00:19:58): Yeah. Alright. 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. Yes. I mean, I'm in a I'm in a couple of funds that have large positions. Like, go public, boys. They are bidding. Bidding. 53,000,000,000 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 a share, which is a small premium. Most people think it'll go for more like $70 a share. PayPal stock jumped on the news, obviously. And Chamath Palihapitiya (00:20:40): Were you able to get to the bottom of this that was it just Stripe and Advent? Because then somebody else reported that it was also Block. Jason Calacanis (00:20:48): Yes. Block is coming in as well. Chamath Palihapitiya (00:20:50): It's so confusing. Every other media source is like, they're all over the place on Jason Calacanis (00:20:55): this. Yeah. No. I think it's because it was a breaking story and maybe they were trying to keep it quiet. Chamath Palihapitiya (00:20:59): It's a huge deal though, if Block is a part of it versus if they're not, Jason Calacanis (00:21:03): I think. Yes. And Block formerly known as Square, is Jack Dorsey's payment company, one of the few entrepreneurs to ever create, to Decrekorns in our industry, and, they're contributing 17,000,000,000 in equity in the combined offer. How they, chop up what's inside of PayPal would be the big question. Obviously, they own, you know, a 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 SaiUSD, 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, Saxx. 439,000,000 consumer accounts. Chamath Palihapitiya (00:21:56): You did Jason Calacanis (00:21:57): something right there twenty five years ago. It's still the test of time. David Sacks (00:22:01): It's kind of amazing. It really is. Jason Calacanis (00:22:02): Isn't it amazing that it's still that strong? Yeah. It's weird when brands keep going for that long. David Sacks (00:22:07): 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, you know, it's grown It's 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 that because 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 different question. Kind of do a private equity play. Chamath Palihapitiya (00:22:35): The different question Jason Calacanis (00:22:37): What's the Chamath Palihapitiya (00:22:39): interesting question to ask is, what is the only kind of baby that Advent and Stripe and Block could have together? And I think there's one, which is you are creating a competitor to Visa and Mastercard because you now have upwards of 600 or 700,000,000 accounts. You have massive stablecoin infrastructure. You have all of the risk management infrastructure that Stripe has built over the last fifteen or twenty 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 it. So that now Stripe gets access to an ultra low cost set of payment rails, literally like to 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. Jason Calacanis (00:23:56): Brewer, 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 what are your thoughts here on the structure and capital market implications here? David Friedberg (00:24:17): I think there's gonna 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 overspending in in a a lot lot of of ways. Ways. And And when when you 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 buy, you know, in those cases, traditional services businesses and AI f y them. I think this is part of a line of maybe looking at traditional digital businesses and AI ifying 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 gonna go hire some McKinsey consultant to do that work for you. It's gotta be the best of the best. It's gotta be the right players in the business. So I think Ryan Cohen has proved his mettle, obviously, with some of the things that he's done with Chewy and GameStop, and that's obviously debatable. I spent some time interviewing him to understand his Jason Calacanis (00:26:18): process. All in interview program. You can go to our channel and find it there. It's last month. David Friedberg (00:26:23): Thanks for the plug. And, obviously, when it comes to payments, who better than Stripe? And maybe Jack Dorsey plays a role here. And and by the way, I think because capital I mean, if you think about that $17,000,000,000 equity contribution, what that technically means is Stripe is selling and Block is selling $17,000,000,000 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 gonna operate PayPal post close. And my bet would be that they're gonna hand it over to the Stripe guys and say, Jason Calacanis (00:27:12): you guys go forward. Clear. Yeah. They because they are the most qualified, and they will have the biggest stake in it. You So I David Friedberg (00:27:17): think so I 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, you know, digital businesses. Have tremendous attention. Go ahead. That can be revived Jason Calacanis (00:27:32): Okay. David Friedberg (00:27:32): With the blue chew of capital and the right operator. Again, I think that there's probably a big a big wave of this to come. Chamath Palihapitiya (00:27:39): 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 and I will say that there is a certain individual that must look very closely at putting in a competitive bid. Jason Calacanis (00:27:58): Oh, a certain individual who may may have his fingerprints on the original PayPal who might also have 4 or $5,000,000,000,000 in market cap to play with who also made a $60,000,000,000 acquisition recently. We don't have inside information here. To your point, Freiberg Chamath Palihapitiya (00:28:18): Correct. Jason Calacanis (00:28:19): This is becoming a playbook. There's a company called Bending Spoons that just went public. They bought a bunch of nonfounder led assets. AOL for 1,400,000,000, Vimeo for 1,400,000,000, WeTransfer, Eventbrite, Brightcove, David Friedberg (00:28:33): time with him? Jason Calacanis (00:28:34): I was just DMing with him. David Friedberg (00:28:35): He's he's awesome. I've hung out with this guy. This guy is an absolute freaking operational killer. He In Italy. 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, how are they being over where are you overspending? Where are you underspending? What are doing wrong with the product? And what are you doing wrong with marketing? And he just fricking fixes it. And he's just a killer. And he's taken all of these, what were called web two point o businesses, and he's revitalized them, rolled them up, and printing cash out of them and And lower the cost Jason Calacanis (00:29:06): to run them. And lower the cost to use big things. He's putting young AIs. He's using young AI first executives from what I'm told. David Friedberg (00:29:12): Totally. It's a great call out, JKL. 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. Jason Calacanis (00:29:19): I will say, you know, the the high 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 Lina Khan. And then once Trump got elected, all the executives working in corporate development said, hey. Looks like m and a's 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 bought delivery hero today. That's gonna, like, jump their revenue by 20 yeah. And that's gonna jump their revenue by, like, they're getting diluted 10%. It's gonna jump their revenue 24% or something crazy like that. And this is gonna 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 and A, and we have four or five companies that got bought since Donald Trump was elected president. Thank you to my president, Donald j Trump, for putting M and A back on the menu, Saks. M and A back on the menu. Why didn't you make a bid, Saks, for PayPal? David Sacks (00:30:30): Been there, done that. Jason Calacanis (00:30:31): Been there, done it. Okay. David Sacks (00:30:33): No. But look. You have to have synergies. Chamath Palihapitiya (00:30:34): There was a moment. This was, like, fifteen years ago where they asked Sacks to go back and be the CEO. Jason Calacanis (00:30:40): That was right. I remember that at the poker game. Yeah. Chamath Palihapitiya (00:30:42): He and I immediately flew to Vegas and spent the weekend there to think about it. They're like, Jason Calacanis (00:30:48): you know what? I wasn't. No, they didn't ask David Sacks (00:30:50): me to, buy that. Didn't say you're 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. Meg Whitman had worked at Procter 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 as just a problem, just a bunch of like cowboys they couldn't control. They made no effort to retain them, 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 Jason Calacanis (00:31:57): They locked them out. They're like, these guys are too hard to manage. Change the keys. David Sacks (00:32:01): I've said for a long time, it's a misnomer to call it the PayPal mafia. It's really the PayPal diaspora. Probably. Our homeland was taken over and they burned our temple and then kicked everybody out. Yeah. And that's why the whole PayPal mafia got started with all those companies. Yeah. You're real victim. For for decades, I don't say anyone's a victim. Jason Calacanis (00:32:19): Joking, David Sacks (00:32:19): joking. Look, when you acquire a company, you get to decide what to do with that asset. Totally. So I mean, that was just the reality. But it's not like, you know, I don't think anyone was bitter about it. They were all like, okay, gives us the capital to go all do the next thing we wanna do. Jason Calacanis (00:32:34): Well, new CEO, by the way, Enrique, is really aces. I've met him before, and they're doing a great job, apparently, which is why they probably got these offers because they've been tightening that business up for the last couple of years. David Sacks (00:32:45): Well, no. The reason they got these offers is the market cap is down to, you know, was down in the, what, like, 30 something billion. I mean, is a company that was worth 200,000,000,000, wasn't it, roughly? Chamath Palihapitiya (00:32:55): $3.22, I think, was the peak. David Sacks (00:32:58): Mhmm. And before this offer, it was down to what, 30 to 40,000,000,000? Chamath Palihapitiya (00:33:01): Yep. David Sacks (00:33:02): 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? David Friedberg (00:33:10): Saks, to your comment about you've gotta have synergies, doesn't it seem to be the case that in this era, the 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, etcetera, etcetera, that simply Well, isn't obviously being well David Sacks (00:33:38): 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 twenty five years old. I mean, it's the same thing that we created back, you know, like twenty seven 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. Chamath Palihapitiya (00:34:24): I think they're buying the accounts. David Sacks (00:34:26): Yeah. Yeah. Yeah. 400,000,000 users. Yeah. What you're saying is interesting because with Stripe, I mean, 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 2,000,000,000,000 a year of annual transaction 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 400,000,000 active consumer accounts. So you're right, Shammoth, that if somehow you could combine the merchant relationships with all those consumer accounts, then bypass the credit card networks, because there'd be a lot, in theory, there could be a lot more on us transactions. Chamath Palihapitiya (00:35:16): Exactly. And where David Sacks (00:35:17): the value is. Chamath Palihapitiya (00:35:18): PayPal already owns Braintree, so now you have Stripe and Braintree that effectively were competitors that won't be. And then what Block gives you is an entire point of sale infrastructure, and you get the Cash App. So you put it all together, and I think it's a it's a shot across the bow for Visa and Mastercard. Jason Calacanis (00:35:36): Braintree is the other one that I think you just mentioned there, Tramath. That's important because that is a very strong business that you don't even know that PayPal Venmo is also that speaks to a lot of young people. So you're kinda getting two generations. You're getting Gen X and millennials. A lot of bang for your buck there. Chamath Palihapitiya (00:35:53): Yeah. What Sat said is true. They have enough of these things to go end to end on their own rails. That is a very David Sacks (00:36:01): The question is whether you 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. Chamath Palihapitiya (00:36:12): No, you don't do that. But what if the consumer David Sacks (00:36:14): doesn't want that? Chamath Palihapitiya (00:36:15): 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 3% or four or 5% discount. And they'll be like, okay. 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 4% in your pocket. Of course, they're gonna pick the new way. Jason Calacanis (00:36:40): Well, and this is the paradox of, like, modern M and A. You know, if you look at protecting the consumer, this will ultimately be great for the consumers. This is going to lower the prices on it. They're not buying Okay, this to Chamath Palihapitiya (00:36:51): 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. Mean, would not even get one step close to doing this deal two years ago. David Sacks (00:37:14): 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, you know, APIs for merchants, then J. Cali would be Stripe versus Braintree, and then the government would say, well, can't consult However, them in a if the real market is Visa and MasterCard, that's the ultimate duopoly. And if PayPal can add competition to that market, which is infinitely larger than APIs- Exactly. Then it's actually pro competitive. How you define the market determines whether it's David Friedberg (00:37:46): anti competitive or or pro competitive. Chamath Palihapitiya (00:37:47): And those guys are smart enough, and they've read enough books where they won't this one up. Jason Calacanis (00:37:51): Alright. Let's get to the next topic. Somebody else is suing OpenAI. This time, it's Apple. On July 10, Apple filed a 41 page lawsuit against OpenAI over alleged 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 Tan, 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. 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. Chamath, if you remember correctly, the default for iPhone AI was supposed to be ChatGPT. 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? Chamath Palihapitiya (00:39:50): I haven't really seen Apple act very litigiously in twenty five years in Silicon Valley. So that's obviously a 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. Jason Calacanis (00:40:10): Egregious, yeah. Chamath Palihapitiya (00:40:12): So I don't know, it's gonna take a court to sort this out. I don't really wanna 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. Jason Calacanis (00:40:27): Obvious. Chamath Palihapitiya (00:40:27): 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've 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 don't think that Sam or Sarah or anybody else there are trying to induce this to happen. I don't think so. Jason Calacanis (00:40:56): I doubt they induced it, but I do believe that it's true or Apple wouldn't have brought it. Sacks, when we look at this, maybe you could open the, aperture here if you want, or you can just go very detailed. But the nature of we have a free market. We don't have noncompetes in California. Generally speaking, you can just employ them at will, go where you want. But we have had instances, you know, Waymo famously, you know, 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. David Sacks (00:41:46): Well, like Jamal said, I have no idea what's going on here. I mean, these 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 is just when an employee leaves your 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. Jason Calacanis (00:42:11): Your memories. David Sacks (00:42:12): Your memories. That's fine. Whatever's in your head, you're allowed to take. But never leave with No anything Jason Calacanis (00:42:18): thumb drives. No CD drives. David Sacks (00:42:21): No documents. No nothing. Just Zip. In your head is okay? Jason Calacanis (00:42:26): Not bad. Freeberg, any thoughts here on just the number of lawsuits that seem to be piling up over at OpenAI? Bad luck? David Friedberg (00:42:41): Couple dots make a line, I guess. Jason Calacanis (00:42:43): K. There you go. Very well said. Couple of dots make a line. Okay. SpaceX had a data leak this week. They launched Grok Build in public beta at the end of May. The newest coding model, Grok 4.5, powers Grok build. I've been playing with it. It's extraordinary. It's a coding tool that works inside 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 Grok Build, the tool was sending their entire code base to SpaceX cloud servers without without alerting the users, Not just the files that were needed to do that specific coding test, just everything. Passwords, API keys could have got pulled up there, all the, change logs, etcetera. The privacy setting was supposed to stop this, but it didn't work. SpaceX quietly disabled the upload on July 13 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 sourced Rock build. That's their harness. So that's another open source win or win for the open source community and AI sovereignty. You got 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 All In podcast. Chamath Palihapitiya (00:44:10): I would actually connect this to my comments on CNBC earlier this week, which built on top of Alex Karp'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 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 trapdoors 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, that's very biased for me because it's in part what we do for large enterprises at eighty-ninety 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 trapdoors everywhere. David Sacks (00:45:53): And that's what Satya just said in a really interesting blog post. Did you guys see Yeah. Chamath Palihapitiya (00:45:58): I thought that was excellent. David Sacks (00:45:59): The reverse information paradox? Yeah. That's exactly the takeaway that he left with. He was building on Alex Karp's supposed crash out. You know, the point that Karp made about how enterprises who have technical ability want control over their compute, models, weights, data, and alpha. But he went further with that idea. I mean, he started with Karp's idea, but then he kind of provided a recipe, a roadmap, for how enterprises should operationalize that. And what he says is that enterprises, they 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 Karp 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 OpenAI wanna go, is they want you to be locked in 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. Chamath Palihapitiya (00:47:41): 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 the CEO of Ramp, was on Squawk Box, 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 Saks $56. A million from SOL is about $26, which is the same as Quad 4.8. A million input tokens from on Grok is about 1.5 ZUX is about 1.5 Elon's about $1 and the Chinese models are 50¢. David Sacks (00:48:30): Wow. Chamath Palihapitiya (00:48:31): So on top of the whole data sovereignty bleeding your alpha away, can you imagine that you're paying $56 as well per million input tokens for That that is insanity. Jason Calacanis (00:48:43): I'm using Perplexity Computer, and they started supporting Grok, and they already support GLM five two. So when you're, like, using Claude or OpenAI, you can only use their model. So I started effing with the different models, and I gave it all the same basically PRD. And I said, I wanna make a podcast player that deep links. So, like, if we were talking about, I don't know, mythos, it would play me all the mythos clips across all the different tech and business podcasts, but make it into one stream. I And 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 Grok. It was hilarious how cheap it was. And then adding to this, I don't know if you saw Chamath Palihapitiya (00:49:26): Sorry. Did you try to do it on Fable to see how much more expensive Jason Calacanis (00:49:30): it was? Didn't. I didn't because I was out of Fable credits on my $200 account. So, you know Chamath Palihapitiya (00:49:35): Well, look at this clip here. Nick, play the clip from, Eric Glenn. That's kind of interesting. Speaker 5 (00:49:39): We're thrilled to be launching token spend management today. It's available to ramp and non ramp customers. Smart. And he's exactly right. Over the last year, I looked at the stats this morning, token spend among ramp customers has grown by 21 times. Jason Calacanis (00:49:54): 21 times. 21 times. Not 21%, we're talking about 21 times. Speaker 5 (00:49:58): That's exactly right. So being off by a few pennies as a CFO actually might be quite nice. Right. At the rate it's going, it might be several dollars. And and and look, like, I 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 proactively 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. Chamath Palihapitiya (00:50:32): Thanks, Nick. He's saying something so important there because if your engineers are going off randomly in an unguided system and then just ripping through a million tokens at $56, 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 their OpEx, at some point, if things are 21x ing every few months, somebody's going to miss a quarter. I don't know who, but somebody. And it's not just gonna 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 nowhere. It is a money burning furnace. Jason Calacanis (00:51:28): The good news is this is all creating a massive market opportunity, Sax. BitTensor subnets, GLM five two hosting, Grok 4.5. Chamath Palihapitiya (00:51:39): Now Inkling. Inkling. Mira Moradi's new model. Jason Calacanis (00:51:43): Inkling. Everybody's now saying, hey. Wait a second. I can give you a better deal. You're paying, like, $2. I can get you $1. This is Chamath Palihapitiya (00:51:50): No. No. People are paying between 26 and $56. They should be paying 50¢. Jason Calacanis (00:51:54): Exactly. Well, you know, and David Sacks (00:51:57): 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. So that's really interesting. Jason Calacanis (00:52:20): Yeah. And But, it's David Sacks (00:52:21): you know, these open models won't be around for very long if Anthropic has its way. Jason Calacanis (00:52:26): I mean, the last question they wanna stop it, it's just they have such a monopoly. Chamath Palihapitiya (00:52:30): Of course, you're selling most of the product for 50¢ per million tokens when they're selling theirs for $56. Of course you don't want that to happen. Of course you want them, you wanna try to stop it. David Sacks (00:52:42): But that being said, they're still growing like crazy. Just to be clear. I Jason Calacanis (00:52:45): mean Yes. David Sacks (00:52:45): You know, you are seeing this explosion of interesting things happening with open models. Like you said, you know, the latest Grok build is open, Thinking Machines open, and so forth and so on. But still Chamath Palihapitiya (00:52:57): Neemo Trim. David Sacks (00:52:58): Mean, they're growing. They're still the industry leader in terms of revenue growth. So these things are happening side by side. Chamath Palihapitiya (00:53:04): 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. Jason Calacanis (00:53:12): Yes. Chamath Palihapitiya (00:53:13): 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's like, I want to use the latest, greatest model. Make me better. Maybe don't need it. Maybe Miro's right. And for 95 percent of the tasks, should be at one level lower, especially when it costs oneone 100 of the cost. But the engineer will never make that trade off because they'll never You're want to think about right. 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. Jason Calacanis (00:53:50): Yeah, booking things from a reckoning. Yeah, 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 the travel department handles that. Chamath Palihapitiya (00:54:00): You're saying something really interesting. What percentage, if you had to guess, of Fable five prompts are just average Michigan that should be running Jason Calacanis (00:54:08): 98 on percent. Chamath Palihapitiya (00:54:10): Yeah. 98%. Yeah. Jason Calacanis (00:54:11): I I I was using it for stupid stuff that I could be using Quen for. Yeah. I think this is my, like, micro prediction here. Mark Gurman, 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 Chamath Palihapitiya (00:54:28): John Furnace. Jason Calacanis (00:54:29): Yeah. And he is a hardware engineer. M seven Ultra, because m we're on m five chips now. You can get, like, you know, 456, 512 gigs of RAM. He says m seven Ultra is gonna 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. You're rich venture capitalists, whatever. You're like, yeah. I'll take a 4 or $5,000 computer. This is going to change everything. You're gonna have employers go, oh, I can just run, you know, 90% of my workloads, 99% of my workloads on the local Mac studio. I think Apple is a screaming buy right now. And I that's not financial advice, but my lord, that company could just run the table on AI if Chamath Palihapitiya (00:55:22): they get this right. Alright. Jason Calacanis (00:55:24): Apple? Yes. Because I they just make such fortune You gotta just let them take lot socks. It's just like the iPhone. Everybody laughed at the iPhone. People overpaid. They laughed. They did not really tell. When the first iPhone came out, many people laughed David Sacks (00:55:41): at that. Steve Paul review. That was it. That's true. Jason Calacanis (00:55:43): Steve Paul was the big one. You can I can still hear him 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 OpenAI 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 Chamath Palihapitiya (00:56:05): desktops. I'm David Friedberg (00:56:05): telling you. Jason Calacanis (00:56:06): I don't Chamath Palihapitiya (00:56:06): 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 is a 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, definitely a theme. Jason Calacanis (00:56:33): Well, it's also chasing energy, right, Shammoth? Like, you've got some solar, if you've got excess battery power, hey, we power up your batteries at night cheaply. Chamath Palihapitiya (00:56:41): 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. 2.5x of all of the energy consumed by California by 2050. This week, there was an auction by this huge utility called PJM, 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 sign 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. Jason Calacanis (00:57:42): Did you see what our boy did this week? Chamath Palihapitiya (00:57:45): We need, we need. So this is behind the meter, which is different. And 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. Regulatory Explain this. It's not David Friedberg (00:58:00): Explain this, When Chamath Palihapitiya (00:58:02): 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 for most places. Batteries, you can do, but you need to generate the electricity in the first place. So people use nat gas. So Elon cleverly bought a ton of 18 wheeler engines, basically. Jason Calacanis (00:59:07): He bought the company that makes all this and Mobile provides turbines. Chamath Palihapitiya (00:59:11): And then just pinned them to the ground and ran it. And those are personal use essentially. And 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 Bloom Energy, which allows you to have huge installations and still fall under the personal use clean air permit. And 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 site to continue to build domestic data centers. Speaking. There's your little TED talk on energy, but, we are in a bad place, guys, and it's only getting worse. Jason Calacanis (00:59:53): Speaking of, data center sacks, everybody's favorite socialist governor, Kathy Hoechel in, the great state of New York, my hometown. Speaker 6 (01:00:05): 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 projects shouldn't arise from higher utility bill, deleted water supply, or noise pollution. So we have no choice but to address these challenges created by these massive facilities. That is why they all be signing the nation's first ever statewide moratorium on hyperscale data centers. David Sacks (01:00:37): Everything she's saying there is a false accusation on the data center. So let's just go one by one. She's Please. Saying Yeah. 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, you know, residential ratepayers, then yeah, you could drive up utility prices. However, if you do what Chamath said 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, you know, eating up land. The reality is these data centers are a model of land use efficiency. We have a ton 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 ROIs there is. The supposed noise pollution, that's largely made up. That can be dealt with. You obviously don't wanna put these things right next to a residential area, but create a little bit of distance and that's fine. The whole water consumption thing is largely a hoax. Totally. The modern data centers recirculate the water. Jason Calacanis (01:01:52): Closed loop systems. David Sacks (01:01:54): Yeah, and I think there was a study that showed that a typical data center uses the same amount of water as two and a half In N Out burgers. So In N Out burger chains. Jason Calacanis (01:02:03): I mean, just go after the almonds if you're concerned about water, people. David Sacks (01:02:06): There's 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 could be building as a nation. Chamath Palihapitiya (01:02:22): And SACS, 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 $40,000 bonuses from all the tax revenue that was coming in? There's all these upsides. David Sacks (01:02:38): 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. You do have ongoing jobs there. And then, oh, one final thing just on the point that Hockel was making. She said it created a lot of pollution. 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. Chamath Palihapitiya (01:03:00): A 100%. David Sacks (01:03:01): These data centers have become the scapegoat for all of 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. Jason Calacanis (01:03:14): All I have to say is welcome to Texas. We got plenty of land here. David Sacks (01:03:19): For now. Jason Calacanis (01:03:19): What's so stupid about her proposal and her talk aside from the things she got completely factually incorrect is New York State is, like, 80% underdeveloped. Drive upstate, folks. You're thinking of New York City. Yes. New York City's packed. You go upstate. 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. Chamath Palihapitiya (01:03:50): On this topic, this week, I just wanna 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 roundtable, a lot of defense companies, CEOs, etcetera. But Chris Wright was there at Saks. My guy. He's great. And Chris mentioned this insane 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, these are all just hobby horses that they use to raise money, have a job. They're 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. David Sacks (01:04:52): The thing that I just can't understand for the life of me is why Anthropic is still funding these groups that wanna put the kibosh on new data center construction. There's one called Public First where Dario just gave his first 7 figure contribution and then a bunch of other employees at Anthropic gave it. And, you know, all these groups are trying to slow down AI development 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? Chamath Palihapitiya (01:05:37): It's so true. David Sacks (01:05:37): I was talking to someone in politics about this and the theory that they had is, well, the Democrats aren't gonna pause the data centers forever. They're gonna 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 gonna stop. But eventually they're gonna be in a position to say, okay, here are our terms if you wanna turn these things back on, right? You wanna 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 gonna consist of a new regulatory agency and new speech controls, a whole trust and safety agenda from social media will be ported over. 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 gonna happen after that. And even if you lift the moratorium in, say, two and a half or three years, it's gonna 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 a few month 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. Chamath Palihapitiya (01:07:09): 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, Saks, which is that when you look out into the future, 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 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. Jason Calacanis (01:08:28): I mean, we're gonna have GPUs chasing energy. Like, where's their energy and just drive the GPUs there is what's gonna happen, right? David Sacks (01:08:34): Let me add one layer to it, which is they're not only trying to stop data centers from being built in The US, 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 wanna make it harder and harder to export chips to more and more countries, including our friends and allies. And so there's not gonna be data centers here. There's not gonna be data centers in our allies. I mean, where are we gonna put these things? Jason Calacanis (01:09:05): Yeah. Mean, those allies have unlimited energy, Middle East. Like, if you want some data centers Chamath Palihapitiya (01:09:11): Well, what's funny, Jason, is, you know, we did a bunch of Middle East data center 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. So you can serve 4,000,000,000 people very quickly in under two hundred milliseconds from there. Instead, what happened was there was this explosion in Asia, and specifically in Australia, which surprised me because I would have thought that those folks are a little bit even further out on the DSA far left. And 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 running to try to embrace this stuff quickly. They've done a decent job. They're doing stuff to displace some of the energy that is needed in The US. 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 should Jason Calacanis (01:10:10): power. Luxury These regulations. Like, you can afford if you're in New York State or California, you'd be like, know what? We don't Chamath Palihapitiya (01:10:16): need this. Jason Calacanis (01:10:16): This is a it's a luxury for us to have an extra day zone. Chamath Palihapitiya (01:10:19): But in Australia, Jason Calacanis (01:10:20): you might really need the money. If you're Texas, you might really want the money in Nebraska. This is what's crazy. Chamath Palihapitiya (01:10:25): 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, all right, you know what? Screw all that. We're just going to build a 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 the cycle where you have to look very carefully at The Middle East because it's a very attractive place to build these things. Jason Calacanis (01:10:52): By the way, Chamath Palihapitiya (01:10:52): had a vanity the Jason Calacanis (01:10:54): the you know, even if you just if you think about fiber and the milliseconds as you're talking about, yes, you can get to the 4,000,000,000 people. But I don't know if you saw the 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, 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 could start putting these things almost anywhere Yeah. Which gets also, like, adds another rainbow. Chamath Palihapitiya (01:11:21): Can we see your clip, the thing that you were mentioning before? David Friedberg (01:11:25): 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. So 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, you know, 14 before everyone started to think GMOs are bad. We gotta get rid of GMOs. And you could ask people a 100 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 as 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. You know, 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 wanna get rid of them. David Friedberg (01:14:01): 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 ask 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. Know, people have these, well, I hate the rich. I hate tech. I hate AI. I don't want any of this stuff. I don't want any of this 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? Influence. I I don't love the word influence because everyone kind of everyone captures it up, but there is some degree Yeah. Of David Sacks (01:15:00): Well, I would David Friedberg (01:15:01): say there's there's foreign interest. Let's call it that. David Sacks (01:15:04): I think it's more than that. Just one month ago, just one month ago, OpenAI published a blog post called PRC Linked 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. Chamath Palihapitiya (01:15:31): It makes sense. It makes a lot of David Sacks (01:15:33): sense that there's trying congressional do investigation of this. It does make sense because it is in their interest, right? Yeah. If they can stop us from building this necessary infrastructure, then that's a way for China to win the AI race. Chamath Palihapitiya (01:15:45): They can convales market, 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¢ 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. David Sacks (01:16:18): Right. Chamath Palihapitiya (01:16:19): That's just the math. The math Jason Calacanis (01:16:20): You ain't David Sacks (01:16:22): know, Satya made the point that these enterprises are not just paying for AI with money. They're paying again by feeding those frontier models their proprietary knowledge, right, and all their alpha. So it's like a double whammy. Like it's more expensive you're potentially mortgaging your future. Chamath Palihapitiya (01:16:41): 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 and they will not think from first principles. David Sacks (01:17:08): 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. You know, even the cyber risk that everyone's been talking about. David Friedberg (01:17:24): Job loss. David Sacks (01:17:25): Or job loss. David Friedberg (01:17:25): Job loss. David Sacks (01:17:26): 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 mean, think about how far the Overton 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 stockbrokers 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 That David Friedberg (01:18:09): was a big one. Here we Okay. David Sacks (01:18:12): 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 stockbrokers creating new rules that all these AI companies are not going have to abide by. Jason Calacanis (01:18:27): I think David Sacks (01:18:27): it's fair Jason Calacanis (01:18:28): going We David Sacks (01:18:29): to 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. Jason Calacanis (01:18:48): 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's 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 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 any more license moratorium on license for now. It's worth watching mythos and if it could hack your system. Palo Alto Networks checking it out. Other people checking it. It's all worth monitoring, but, yes, it there's no disaster here today because of AI. Nothing's jumping out of your chat GPT window. You know? The worst case scenario is you blow out some tokens. You know? Okay. Great. That that's that's the biggest David Sacks (01:19:32): 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 Jason Calacanis (01:19:39): of a good job. David Sacks (01:19:40): Yeah. They're doing a good stop that. I'm just questioning whether we need some vast regulatory apparatus now to start doing Jason Calacanis (01:19:47): all this real premature, and we did this because of science fiction and Dario saying all jobs are going away. I mean, that that that was the most ridiculous thing. When he said it's like he's panicked that it's gonna be 80 or 90% jobs in 2026, what was his claim? Nick, get the exact claim. I think he said 50% of job site. David Sacks (01:20:05): 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. Jason Calacanis (01:20:12): So It's a little ridiculous. Yeah. I mean, it's David Sacks (01:20:15): But he's been in since state of GPT two. Jason Calacanis (01:20:21): Yes. Yes. David Sacks (01:20:22): I remember. They wanted they wanted to have regulatory approval for models that use 10 to the twenty fifth FLOPS, right? And every single AI model is like well past that threshold now. Jason Calacanis (01:20:34): And David Sacks (01:20:35): we haven't seen any of the harm look, they thought that 10 to the twenty fifth FLOPS would be enough compute to create, you know, the Terminator, you know, to create Skynet. Jason Calacanis (01:20:47): No offense, Friedberg. But one guy's panic attacks, one guy's anxiety condition might have shaped the whole course of history here. Like, Dario 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, Dario. Invite's open. Come hang out. David Friedberg (01:21:05): I'm sure he'd love to come on the pod after you just accused him of having a panic attack. Attack. Jason Calacanis (01:21:11): I mean, he seems like he's in a perpetual one. David Sacks (01:21:14): 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, ban unsafe AI. Three, profit. Jason Calacanis (01:21:30): Yeah. There you go. David Sacks (01:21:31): That's the strategy. Kind of brilliant. Jason Calacanis (01:21:33): All right, everybody. Go to allin.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 Friedberg. David Friedberg (01:21:49): Before we get into the Science Corner, I'm gonna give a shout out to Ronnie, dog for adoption. I love Family Dog Rescue in Sonoma. Check out his Instagram link Jason Calacanis (01:21:58): God. Here he goes. David Friedberg (01:21:58): In the description. This dog needs a home. He was fostered, he lost the foster home. Someone come and grab him. He's awesome. Alright. Let's get into science. David Sacks (01:22:06): We're doing next Jason Calacanis (01:22:07): on your side? This is what we're doing. Just try to try to get more cue points. Chamath Palihapitiya (01:22:11): That dog looks delicious. David Friedberg (01:22:14): What? Gross. Jason Calacanis (01:22:15): Tucker, fuck you. David Sacks (01:22:17): You don't live in Sri Lanka anymore, Chamath. Jason Calacanis (01:22:19): No. Seriously. Sri Lanka taking his tray. Oh my god. How do you marinate that dog in Sri Lanka? Do what you David Friedberg (01:22:27): gotta do in Sri Lanka. Chamath Palihapitiya (01:22:28): Is it just salt and pepper, Freeburg, or do you like something else? You know, just a little salt and pepper? Jason Calacanis (01:22:34): Marinade. Do you use beau drole, nouveau? Chamath Palihapitiya (01:22:36): Oh, do you do you like do you like a little yogurt and garam masala? Maybe do a little tikka dog? Spicy. Do David Friedberg (01:22:42): you wanna talk about reversing aging? David Sacks (01:22:44): Yes. I wanna talk about, but I gotta drop. Alright, guys. Jason Calacanis (01:22:46): I gotta go the Apple Tower, Paul. Oh, come on, audiences. Around. David Friedberg (01:22:52): Science Quarter. Alright. So, Jamat, you can drop two if you want. I'll cover Science Corner solo. So 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. And 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 kind of, you know, age reversal startup that's super secretive that they're not allowed to talk about in partnership with a group called Revel Pharma. And what they focused on was what's called the extracellular matrix, the parts outside of the cell that age. And and 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 and they don't get cleaned off. And 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, makes Is it harder for our Chamath Palihapitiya (01:24:01): that what visceral fat is? David Friedberg (01:24:02): No. It's called glycation. And so it's the binding of sugar and fat to the proteins that sit in that extracellular In between the cells. Chamath Palihapitiya (01:24:12): Yeah. David Friedberg (01:24:12): In between the cells. Exactly. And so it's that whole gunky area in between the cells that when you're young works well, everything's smooth, the proteins get replaced if they break down. And as you get older, sugars and fats kind of 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. So things like collagen that are far apart stick together, and that causes things like wrinkles and that causes immobility. And 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. And so 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. So these scientists set out to try and create an enzyme. An enzyme is a protein that breaks something down, that can break down CML. And remember, a protein is just a series of amino acids, and those amino acids are programmed by DNA. So you can put three letters of DNA to make an amino acid. So you can literally just print DNA and then put it in a bacteria to print proteins and then test those proteins to see what they do. That's the the modern kind of era of kind of protein synthesis and protein testing. And so these guys kinda 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 AlphaFold, and they used AlphaFold to find a protein that could bind to CML and activate an enzymatic or process that would break it down. And then they took that protein from alpha fold that comes out of a bacteria. David Friedberg (01:26:02): 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, you know, 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'd kinda 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, casine, collagen, retinal proteins, which are in your eye, hemoglobin, and they were able to get rid of 52 to 97% of the CML, just degraded away. And then they, 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. And 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, lights a great path forward for these novel therapies that we're developing. It's fucking awesome. I mean, dude, like, you know, all my I got all these joint pains in my hip and my shoulder now. David Friedberg (01:28:05): Like, everything you could feel yourself getting older. Chamath Palihapitiya (01:28:07): Well, that's all. I will tell you this right now. That will not be the first market. The first market will be cosmetic and David Friedberg (01:28:12): Cosmetic skin. Yeah. Chamath Palihapitiya (01:28:14): It will be a trillion dollar market. You can create a queen. David Friedberg (01:28:18): I mean, you could put this enzyme literally on your skin and have it absorb it Chamath Palihapitiya (01:28:22): in your cream? Yeah. David Friedberg (01:28:23): Game over. Chamath Palihapitiya (01:28:23): It's a it's a that that alone is $2,000,000,000,000. David Friedberg (01:28:27): But, I mean, dude, AI, let's just talk about applications of AI, why it's actually awesome that everyone should be able to agree on and you can't be convinced by some foreign psyop. This is fucking awesome. I mean, this was alpha full It's amazing. Used to discover this thing and evolve it and drive this outcome. Everyone can benefit from it. It's just so profound that we have this pool at our disposal in this day and age. I think it's pretty awesome. Anyway, thanks for sticking around for Science Corner. Chamath Palihapitiya (01:28:51): Sky's a lot more. Alright, David Friedberg (01:28:53): bro. Love you too. Jason Calacanis (01:28:55): We'll let your winners ride. Rain man David Sacks. And it said We open sourced it to the fans, and they've just gone crazy with it. We should all just get a room and just have this one big huge orgy because they're all just useless. It's like it's like sexual tension that they just need to release somehow. Wet