IPO 与 SPAC 回归、七巨头 AI 对决、扎克伯格全力押注、苹果失手、GENIUS 法案通过参议院

Jason Calacanis (00:00:00): Alright, everybody. Welcome back to the number one podcast in the world. I'm your host and executive producer for life. Is it not alright, Dave Freeberg? Nope. Jay Kal, Jason Kalik, and this Not David Friedberg (00:00:12): at all what you are. Make sure you tune in to this Jason Calacanis (00:00:14): in startups and apply to Founder University. You're David Friedberg (00:00:17): something very different. Jason Calacanis (00:00:18): Us again today, the sultan of science, David Friedberg. Can I just congratulate you on your fourth baby? If you double that number, you're gonna be able to catch up to Chamath and his five plus three illegitimate. How are you doing? Is our best. Oh my god. Speaker 3 (00:00:37): Let your winner ride. Jason Calacanis (00:00:52): How you feeling? You're tired and grumpy, aren't you? David Friedberg (00:00:54): You're a little tired. For me. I didn't have to do the work. Jason Calacanis (00:00:57): Are you tired and grumpy? And how's Allison? How's how's David Friedberg (00:01:00): the Everyone's wonderful. Chamath Palihapitiya (00:01:01): Thank you David Friedberg (00:01:01): for asking. Jason Calacanis (00:01:02): And a beautiful boy. Beautiful. Chamath Palihapitiya (00:01:04): More is crushing? David Friedberg (00:01:05): Nothing more amazing than seeing a child. Chamath Palihapitiya (00:01:08): How's Schmeckle? David Friedberg (00:01:10): Magnificent. Magnificent. Thank you for asking. Thank you for asking that. Yeah. Okay. Let's move on. Thank you. Jason Calacanis (00:01:16): Thank you for all the kind words. And just we sent over a gift basket, Chamath and I, longhorn, picanha steaks, a tenured membership for Chamath Palihapitiya (00:01:27): Oh, hey. Congrats to Olivia Landon, by the way, of Long Hill Wagyu. She had twins. Jason Calacanis (00:01:32): That means she's gonna have more people to work on the ranch and slaughter cattle to send us our picanha. Congratulations. Shout out. Chamath Palihapitiya (00:01:39): To Olivia Landon. Jason Calacanis (00:01:40): It's so funny because we love this we love these steaks so much. She doubled. We mentioned it on the pod, and you idiots started, like, searching for lunatics, and they ordered out all the stinks. So now Chamath and I are screwed. Thomas Laffont (00:01:52): No cool debts left. Chamath Palihapitiya (00:01:54): No. They ordered out everything. Everything was sold out. Everything was sold out. Jason Calacanis (00:01:58): So now we have to gatekeep with us again, your chairman dictator, Chamath Palihapitiya. He of two votes in our fine organization. How are doing, Chamath? Chamath Palihapitiya (00:02:08): I love voting control. Jason Calacanis (00:02:10): Oh. I'm doing great. He starts Thomas LaFonte with a tie, and then all of the gamesmanship happens between the team of rivals, me and Freiberg. With us again, Thomas LaFonte, a gentleman, a scholar, no idea why he's here. A true I don't know how he's doing. On this podcast. What a true gentleman, a true scholar, and host of East Meets West, an incredible conference that I attended this week with our bestie David Sacks, who, of course, is at the White House and can't join us. But, Thomas, what a great event. Thank you for including me. Thomas Laffont (00:02:47): No box lunches, by the way. We we took your feedback from a couple of years ago, so I hope that we met your standard. David Friedberg (00:02:54): You did upgrade highlights for you guys at your conference, Thomas? Thomas Laffont (00:02:58): I mean, I think for me, obviously, I think a lot of news in AI this week. So I think that was kind of the center piece of most of the panels pretty much up and down the stack from SaaS companies trying to transform into AI to, obviously, the big Zuck news on scale, and then potentially, I saw in the information today the the Nat Friedman news. So it feels like there's a lot going on in the industry, so it should be fun to talk about. Jason Calacanis (00:03:23): Yeah. And we're gonna talk about it all today. We got a a really full docket. Rick Caruso, the, mayor who would have saved Los Angeles from the fires. He was there, and you actually hosted at his incredible facility. What a Thomas Laffont (00:03:37): We did. We talked about the the state of LA, which J Cal, is that is that it looks like that's where you're at. Right? Jason Calacanis (00:03:43): Yes. I'm at my, LA home, which Thomas Laffont (00:03:46): AKA the compound. Jason Calacanis (00:03:48): Yeah. It's, it's available on Airbnb. So I'm, here in LA. But, yeah, Thomas Laffont (00:03:52): Rick Caruso, what a great speaker. Interestingly, Jake Al, today, a friend just sent me a chart showing the recovery of restaurants post COVID. And fifth, LA is 50% behind on the recovery per store location versus the national average. Jason Calacanis (00:04:09): What do you attribute that to, or what did they attribute it to? Thomas Laffont (00:04:13): I think I think there's kind of a couple different things. Right? I think one, the economy, which, you know, unlike the San Francisco economy being levered to to AI and on the upswing, is more levered to entertainment. And I think, you know, secular decline. I think, you know, someone mentioned at the conference that filmings in LA are down 50% from peak. So, I mean, that's just a a massive move down, losing share to other geos both in The US. I think Georgia, right, J. Cal, was mentioned. Jason Calacanis (00:04:45): Another has explained exactly how aggressive New York is being, The UK is being, Atlanta. I mean, so many different hubs for movies giving much better deals than Los Angeles is. Thomas Laffont (00:04:58): Yeah. So I think it's a it's a combination of, I think, you know, being levered to one industry that's kind of in secular decline. Chamath Palihapitiya (00:05:06): I can tell you from MrBeast that for beast games, we had a deal in Las Vegas and in Toronto. We got huge tax credits. And in the second season that we're doing for Amazon, we did an enormous deal with the Kingdom Of Saudi Arabia. And so we're filming a bunch of episodes there. We're building the sets there. We're actually gonna keep them there after it's all said and done. We would not film in Los Angeles unless we absolutely had to. We will stay as far away from California as possible. Jason Calacanis (00:05:35): And regulations are such a big part of this. Chamath Palihapitiya (00:05:38): Yeah. It's uneconomic. You can't make it work. Thomas Laffont (00:05:40): Yeah. 30% more expensive. I think it's is the kind of the official number on Jason Calacanis (00:05:45): shooting LA. Right, Thomas? Like, how quickly can you stand something up? How many how much paperwork do you have to file? James Beard Foundation, I'm seeing here from the research has found that all these independent restaurant owners said they just can't get staff here. So, in Los Angeles, it's just hard for people to live here. And it's hard to get through the regulations. And if you make it hard, there are other options for people. This idea that California has a lock on, anything other than incredible weather and beautiful people is farcical. There's a lot of beautiful people in other places with decent weather, and you can you can go to your projections there. So Another topic that came Thomas Laffont (00:06:20): up that a lot of people were talking about, something that I know you've talked a lot about, our our debt issue and the debt to GDP ratio. There was a lot of talk on the on the flip side on the GDP side. What if actually AI can increase productivity and regrow GDP faster than expectations? Right? And perhaps that's one of the reasons why, you know, interest rates might not be quite as high as you might expect given some of the trends that you guys have talked about. So I think a lot of a lot of discussions around AI productivity and what we could look at over the next, you know, five to ten years because of the the improvements we're seeing. David Friedberg (00:07:01): This is particularly beneficial to The US. Right? I mean, if you think about where AI is gonna accrue economic surplus first, it's likely gonna be in The US, not global GDP. So The US kind of does it compete away dollars or it increases overall productivity or both ahead of the rest of the world. If we do see advances from AI to accelerate GDP growth, is that because of all of the onshoring of manufacturing and industry that we outsource today? Like, do you think that that goes hand in hand with AI acceleration? Thomas Laffont (00:07:37): I think that's part of it. And I think the other part is just getting even out of the, you know, the knowledge worker workforce. Right? Just getting significant productivity improvements there. One of the things that we showed in our keynote is the adoption of these technologies and even taking doctors as an example. Right? An area you know well. You know, this new company, kinda coming in and and developing kind of a diagnosis kind of engine. Right? That's now used by a third of doctors. So, you know, I I think that, it's open evidence, by the way, is the name of the company. And already a third of US physicians are on the platform using it, 10 times a day to kind of help diagnose these. So in particular in oncology, as an example, it's seen significant traction. So you multiply that by the legal profession, coding, I think we're already seeing. You know, what if we just see kind of a an explosion of productivity gains across, you know, both the physical and the digital economy? David Friedberg (00:08:42): Yeah. The doctor one's a good example. If someone had the opportunity to go get more regular preventative checkups, They would, the problem is it's very expensive, it's hard to get an appointment, or insurance won't cover it. But if the cost to a doctor goes down, because they can leverage AI, the throughput goes up by 10x, they can see 10 times as many patients per day, then suddenly diagnostic care becomes more available. They can charge for that. They don't need to charge the same amount. The price will come down per checkup, but you'll, more people will be able to get a checkup per day. So that grows GDP in diagnostic care, that grows the size of that piece of the economy. It's a very good example. I'll give you by the way. Anything where AI provides leverage to a service provider where their throughput now goes up. Thomas Laffont (00:09:28): I'll give you another example of that, Dave. So there was an LA dentist that kind of hit got viral this week. I don't know if you guys saw this story, but basically he created an ad using VO3 about a skydiving gorilla David Friedberg (00:09:45): Yeah, saw that. Thomas Laffont (00:09:45): Who, you know, ultimately needs to get his teeth fixed because he was drinking while he was jumping out of the plane and, you know, it's a very kind of funny viral ad. He probably made it for a couple, you know, $100 and now his practice is totally full. He's been flooded with requests, right, for the new dental implants. So, you know, to your point about increasing productivity, boom. There's how how v o three can help a local dentist. Jason Calacanis (00:10:10): Alright, everybody. Welcome to the number one podcast in the world. We got a full docket. Full docket. But we're gonna rocket the docket because there's so much going on here. Zuck is tilted. Clearly, this has been the big discussion in Silicon Valley for the last ten days or so. According to reports, Zuck is super frustrated that Meta's falling behind in AI. So he is swinging for the fences. Sam Altman said Meta has offered top open AI employees a $100,000,000, wait for it, signing bonus. That's not comp. That's a signing bonus. Who knows if this is true or not? But he's also offering a 100,000,000 a year in annual comp. He's clearly cut out tens of billions of dollars for this effort, not dissimilar to when he did his VR efforts that didn't work out so well. Here's a thirty second clip of Sam Altman talking about this on his brother, Jack's podcast uncapped. Thomas Laffont (00:11:03): They started making these, like, giant offers to, you know, a lot of people on our team. Mhmm. You know, like, $100,000,000 signing bonuses, more than that comp per year. That's crazy. And I'm actually, it is crazy. I'm really happy that at least so far, none of our best people have decided to take them up on that. I think that people sort of look at the two paths and say, alright. OpenAI has got a really good shot, a much better shot at actually delivering on superintelligence, and also may eventually be the more valuable company. Jason Calacanis (00:11:31): Meta just also invested over 14,000,000,000. I'm using invested in quotes in Scale AI for 49% stake, And, this probably is better described as a shadow aqua hire to get around antitrust scrutiny. Remember Microsoft did that with inflection AI back in the day. Google did it with Character AI, and Amazon did it with the depth AI. I'm Not sure if this is necessary anymore, since Lena Khan's no longer in the position. Scale CEO, Alexander Wang, and others will be joining Meta to work on a new super intelligence team. They're saying that Scale's gonna remain an independent company and get a new CEO. I'm not sure if that's gonna happen. And if you don't know, Scale does data labeling. They get experts to help train language models. Two of their biggest customers are OpenAI and Google, and they both canceled their contracts. So Zuck is taking that chess piece off the board so he can get all that data into his LLMs. He's also reportedly in talks to hire former GitHub CEO, Nat Friedman and Daniel Gross to work on AI. They have a incubator investment fund for AI. Daniel Gross had a really cool startup incubator called Pioneer Labs. I had him on this week of startups a couple years ago. Really smart cat. Meta has 70,000,000,000 in cash. Thomas LaFonte, when you see Zuck doing this, what's your take? Not only on what Zuck's doing, but how big of an opportunity is this, you know, in terms of the prize of having the best large language model? What is he going for here? And what's your take on these really aggressive packages and 49% purchases? Thomas Laffont (00:13:06): I mean, look. I think, one, it it feels highly rational. Right? If you think about Meta's market cap is, rough math, 1,700,000,000,000.0. If you're the CEO and you ultimately believe that maybe 50% of your market cap is at risk because of AI, 850,000,000,000, why would you not spend maybe four or 5% of that if you think it increases the odds even slightly that you're gonna win the market? So to me, it it it kinda reminded me of a few few things. Number one, the scale and size of the opportunity. Right? Obviously, people think AI is massive. But frankly, Jake, I'm even wondering putting the regulatory scrutiny to the side if it was time. He just didn't wanna wait. And, obviously, doing it this way, I think Alex, literally, the next day, who's the CEO of scale, can show up to work at Meta. So I think it's it's urgency of a large opportunity. I'm curious to get Shamash's take because it reminded me a little bit of the pivot away from HTML five and also a a much smaller acquisition, but one that we really felt, which was of a company called Onavo. And for those that may not remember, Onavo was a small data service provider, but what it did is it had a panel of phones, and we as investors could see what people which apps people were using. And the data was incredibly valuable because it was the only service that gave you true engagement data. And so obviously as an investor, you felt, wow, this is an incredible tool. And eventually it sold to to Facebook and Facebook used it internally and didn't allow anybody else to use it. And we lost one of our key abilities, right, in the mobile app revolution to tell who was winning and losing. So Jason Calacanis (00:14:48): And you're saying the scale acquisition is you know, parallels that in a bit. This is great service. A lot of people rely on it. He buys it, shuts it down for everybody else, gets the tool for himself, gets Chamath Palihapitiya (00:14:58): the data for himself. Correct. Thomas Laffont (00:15:00): So I definitely see parallels. Jason Calacanis (00:15:01): And I think given this you know, their market cap and the size of this opportunity, I think it makes a lot of sense. Shammoth, your thoughts on sucks action. Obviously, folks know you worked with him as you went from tens of millions of Facebook users to hundreds of millions, and you were there actually during the HTML wrapper app disaster that it I think maybe Chamath Palihapitiya (00:15:25): That was a debate at our executive team, at our m team, and I was on the side of apps. And, well, without embarrassing him, somebody else was on the side of HTML five. I thought it was fucking stupid. Jason Calacanis (00:15:36): Why? Why why was Chamath Palihapitiya (00:15:37): That but that decision, one, because, you know, all of my political capital at the time was also wrapped into native apps, our own phone, an entire verticalized integrated stack. And, I think I made the decision for them very hard because I was not a very play nice in the sandbox with others kind of executive. I was more of a scorched earth, get it done kind of person. Jason Calacanis (00:16:03): Okay. So no changes over the last fifteen years. That's good to know. Chamath Palihapitiya (00:16:06): They made they made an enormous mistake, but then they admitted it about a year after I left. They said this was the single success. Jason Calacanis (00:16:12): Explain in plain English why HTML five wrappers versus native apps. Chamath Palihapitiya (00:16:16): I can't because it's retarded. Okay. Great. I can explain it. So, like, native apps are was obvious in 02/2010. Obvious. Yes. The only the only reason to use HTML was as an end around for different carriers and for different ecosystems that were trying to charge us a toll. So in 02/2010, I went to Mobile World Congress, and I took a group of my most talented developers, and we built an entire replica of Facebook that we called Facebook zero, which was only available via URL. And we launched it at Mobile World Congress. And we did it, and I announced it there because if you went to India as an example, all of the folks there would try to charge us a tax. But if you could navigate through the browser, you wouldn't have to pay it. Right. So that was a good example of what to do in a developing market when people were toll taking. But the real solution was to build an extremely integrated app from the software all the way to the hardware. And the only way to do that was as a native application. And that has tremendous applications to today. But just to finish on yesterday, my proposition was full phone, full stack, full app, all of this other HTML stuff should only be as a side thing that we do in markets where they try to make it difficult for us. Instead, it became politicized, and it became a big bet on HTML five, which I thought was absolutely stupid and unjustifiable. And that was also when I said, okay. Well, this phone's not gonna happen, so let me leave. And a year later, I think Mark, to his credit, said this was really stupid and ripped all the HTML five stuff apart, went native, and the rest is history. So let's fast forward to today. Yeah. There it is. Biggest mistake was betting too much. It was it was an and that was, again, I'll just say it, people politicizing what should have been an obvious technical decision. Okay. Let's The other piece Jason Calacanis (00:18:09): to that, just to add to it, was it was also a religious decision then. People liked the open standards of HTML five. Was stupid. Certain developers who felt like, we have to support open standards. Chamath Palihapitiya (00:18:19): People thought that. Yes. Only stupid nontechnical people thought that. It was stupid. It was obvious. You'd have to be a fucking moron, and there were fucking morons at the executive team that advocated for this. Anyways, we were right. They were wrong, and he was fine. Okay. Fast forward to the where are Jason Calacanis (00:18:35): we today? Chamath Palihapitiya (00:18:36): It's the exact same story playing out. Now what do I mean? You have to look very carefully at Microsoft's deal with OpenAI. Why? Because what you see is the compounding of secrets. There are secrets in the training layer. There are secrets in the model layer. There are secrets in how these things are tightly coupled to infrastructure and compute. And what we have to remember is what OpenAI got from Microsoft was an extremely competent partner that built an enormous Azure compute infrastructure to train everything from ChatGPT all the way up to the o three model, DALL E, everything. Why is that important? Because you start to figure out these tricks. How do you really optimize these models to be extremely performant? Now if you look at all of the other models, they've also had some level of that advantage. So if you look at DeepSeq, what did they do? Well, we don't know, but what we have been told is that there's very tight coupling to hardware. If you look at what XAI is doing, I think what you can bet is that there's an extremely tight coupling to hardware and infrastructure and compute. If you look at what Facebook is doing, they generically train on NVIDIA and they launch it in the open source. So I think that what they need to do is more of the OpenAI, more of the Google playbook. Look at Google. Google's Gemini models are extremely tightly coupled to TPU. And it enables and unlocks an entire stack of secrets and capability that then get manifested in model quality. So I think the first thing that Mark has to do, if I were him, is start to chip away at all of the sets of secrets. So what secrets do you get from Alexander Wang and scale? It's what are the labeling techniques that allow these models to be more and more performant? What labeling techniques are used in the reasoning models? Chamath Palihapitiya (00:20:37): What labeling techniques are used in more traditional LLMs? It is clear that LAMA doesn't know this. Meta doesn't know this that well because their model quality is men. So now what you get is that set of secrets. So what do you get from Nat Freeman and Daniel Gross? You get what are the apps doing? How are they approaching writing agents? These agentic tips and tricks that make usability and value more obvious. But then what's missing? I think the thing that's missing is the infrastructure and compute set of secrets. I think it's insufficient to buy stuff off the shelf from NVIDIA and expect these models to fundamentally compete. So I think if I were a betting man, he's bought the training secrets. He's bought the app secrets, and now he has to buy some infrastructure and compute hardware secrets. You put it together, and he's got a pretty good strategy here. Jason Calacanis (00:21:24): And, also, just to add to that, Shammoth, Nat and Daniel have invested in a lot of AI companies, and those companies are have secrets of their own. Yeah. And those Chamath Palihapitiya (00:21:33): are Those are those. Jason Calacanis (00:21:34): And, actually, I think they have somewhere along the full stack. Friedberg, your thoughts on this strategy as described by Thomas and Shammoth and just the data we're seeing on the playing field, aggressive acquisition of talent and companies. David Friedberg (00:21:48): I don't know if I have much to add here. Thomas Laffont (00:21:51): Okay. One additional point, Shammoth, by the way, that you mentioned. If we look at the winners, right, in models of the past twelve months, anthropic the same. Right? They've been very, kind of deliberate and have explained how TPUs, right, they've been a big user of them, how it's helped define their training model. So I think you're a 100% right. If we look at the models that have really performed, it's ones that have that that, quote, secret, as you mentioned. Chamath Palihapitiya (00:22:14): When I first started $80.90 a year ago, one of the key bets I made, which was a mistake, and we unwound the bet. But the first bet that I made was, can we build a transpiler? Which is to say, can you take a CUDA workload and then can you redirect it away from NVIDIA to different hardware? And basically what I learned in that process are all of the attention mechanisms that are built into transformers that really differentiate how good the models are need to literally be hand tuned for every single target of silicon that you have. So when Amazon just kind of wakes up and says, here's this chip, it means nothing unless you can incentivize somebody to build to it. But the opposite is also true. If you have a model and you just run it generically, you're not gonna get the gains and it's not gonna be as special as if you have dedicated infrastructure and compute architecture and say, we're gonna tightly couple these. It's been clear that OpenAI has had that. Anthropic has had that. Google has had that. DeepSeek has had that. And I think Meta needs to do that. Otherwise, they're always going to be floundering on their back heel. Thomas Laffont (00:23:22): One quick misnomer. I think, you know, when people hear labeling, they kind of assume a photo of a dog and someone says this is a dog. Right? I mean, that's definitely how it started. If you look at scales Jason Calacanis (00:23:32): to the Thomas Laffont (00:23:32): business, it's completely more from that. So Yeah. You could actually label a problem. So for example, in in simple terms, two plus two equals four is actually, a reasoning dataset. Right? So you gotta think of labeling not just in the simple terms of, you know, this image, but of massive datasets of of outcomes, and that's what's kinda really used to true train these reasoning models. Yeah. That's perfect. Yeah. There's another story here, guys, in my opinion, and it's the performance of the max seven. Right? And I'm gonna have to check with my data science team, but I'm wondering if we're this is the year where we've seen the greatest divergence amongst the max seven. Right? So if you look at the max seven and if I just gave you, right, this performance, you can see, okay, so Meta's up 18, Google's down, NVIDIA's up eight, Tesla down 20, Apple down 21, Amazon down three, and Microsoft is plus 13. Right? So it's kind of interesting in a market that, you know, historically over the past few years where we feel the Max seven have been truly correlated, now the market is saying, wait, hold on. We might start to see diverging performance. What I read from that in one element is the market's starting to try and sort out who are gonna be the winners and losers, who's well positioned versus maybe falling behind. Right? So I think we're gonna start to see some divergent performance from the max seven. I think it's gonna reward not Chamath Palihapitiya (00:25:03): Can you put that back up there for a second? I mean, I think that's so interesting because if you look at the conditions on the field today, Google's down 8%. But, again, I would tell you, as a user, Gemini models are exceptional. Like, absolutely just bar none exceptional. I think Anthropic is incredible for cogen, incredible. What I see is every single company on this list that isn't NVIDIA baking and rolling their own silicon. Yet NVIDIA is up and the rest are down. I told you that I spent time last week at Tesla. I would not be sleeping on this business. I think that it is yet again back into the land of being misunderstood. The only one that I understand why it's down this much is Apple, because it's not clear that they're even baking something in private. There's nothing public. There's nothing private. It just seems like they're transitioning into being a cash cow and getting into sort of that cash harvesting mode. But it's almost weird that the price action is what it is because I would have thought that Google would be up. Meta would maybe be a little flattish to down. Nvidia is up, but maybe it could be down. Tesla's down, but it should probably be up. Amazon's basically breakeven, and Apple is down, and I think that kinda makes sense. That's sort of how I read this table. Jason Calacanis (00:26:25): Yeah. I mean, look what Thomas Laffont (00:26:26): I love, Chamath, by the way, on that is that, like, now there's debates. Right? Yeah. And and you can argue whether know, you agree with Chamath or whether you don't know, Chamath Palihapitiya (00:26:35): by way. 20,000,000,000 because he's because he's not afraid. Jason Calacanis (00:26:38): Correct. Yeah. I know. Let's pull the chart up again here. By the this is an interesting way to And by way, the Thomas Laffont (00:26:45): only reason Microsoft is not on this list is because of the limitation of the DOS era interface of the Bloomberg terminal where it will only allow you to compare six charts and not seven. Right. But we know that Microsoft is up 13. Chamath Palihapitiya (00:26:59): Cue perplexity. Thomas Laffont (00:27:00): Yeah. Jason Calacanis (00:27:01): So, you know, when you also, when you look at these, there are some extenuating circumstances here. Like, Tesla's car sales are down. All car sales are down, and I think that's the piece that maybe isn't being accounted for here, and they're in a transitional period. Apple, obviously, disrupt the odd yeah. David Friedberg (00:27:17): There's a lot of regulatory overhead. So Tesla losing solar and EV tax credits. Chamath Palihapitiya (00:27:23): Yes. David Friedberg (00:27:23): Apple Apple being told to onshore and stop buying from China, so their supply chain is being disrupted because of tariffs. Those two companies in particular are far more affected than the rest. And even Amazon, you know, there's been some conversation about tariff effect on Amazon, but, obviously, that's offset with some of the benefits they've been realizing and promoting as Jassy spoke in his letter this week, from AI. So I think that there's a variation here that's probably a little bit more, Thomas, kind of tuned to these conditions that aren't necessarily call it natural market forces, but are kind of influenced market forces associated with the the new administration and some of the policy choices that are being made. Jason Calacanis (00:28:05): If we were looking at those, number one and number two, which one do you think gets to AGI first? Thomas? Chamath Palihapitiya (00:28:11): Well, wait. Hold on. By the way, the other thing you should note, Jason, which I find really interesting is nobody talks about AGI anymore. If you listen to the language of all the companies, it's all superintelligence, which is a much more achievable goal because it's defined as being, multiples more intelligent than a human being. But I think you're I think if you actually did a search for the number of times AGI is being said today, it's meaningfully less because I think people have realized that that's not in the offing. Thomas Laffont (00:28:37): Yeah. By the way, another lens, Chamath, that I think about on these is who controls their own destiny of these seven companies in AI? Right? And I would argue Tesla does. I would argue Tesla does. Yeah. NVIDIA. And then it's kind of interesting. Right? Neither Amazon doesn't have its own foundation model. Right? They're kinda dependent on others. Right? Microsoft, 49% does, right, because of this kind of relationship they have with OpenAI. It's both you know, they they own a big share, but they don't control it. So there's kind of interesting. And then maybe six months ago, we would have said, well, Meta absolutely does. Maybe Zuck's turned in to question that a little bit. And, you know, it's it's fun, in my opinion, to kind of bring different lenses to this list. Right? There's the regulatory one that Yeah. Friedberg was just talking about. I kind of think about if I was the CEO, do I control my own destiny in this market? Right? And I expect these companies are not gonna wanna be dependent on others and are gonna at least want to say, no. I'm gonna control my own destiny whether I win or lose. Jason Calacanis (00:29:38): Who's your number one? Who's your number two if you had to could only bet on two here to achieve superintelligence AGI? Let's just say, win the AI re win the AI, big prize, the big prize, superintelligence AGI, you know, in the midterm, five years. Five years from now, we're sitting here. Thomas, give me your number one. Give me your number two. Thomas Laffont (00:29:58): Look. I I think to me, number one, I I still think NVIDIA. Right? I don't see the GPU kinda getting displaced. I see additional don't architectures kinda coming on board, right, and growing the market. But, at the end of the day, all roads still lead to the GPU for all of these models. So I would kinda still put, kind of, NVIDIA on that. My number two, more of a dark horse, but I I would pick Tesla. I do think it has the most potential for vertical integration, right, from all the way the silicon to the model to actually the hardware, right, that might become super important not just in cars but in optimus. So NVIDIA one, Tesla is my dark horse. Jason Calacanis (00:30:38): Wow. Stunning. Chamath, who's your number one and number two in the midterm? Five years from now, we're sitting here on All In episode 700. Chamath Palihapitiya (00:30:46): Tesla's one and Google's two. And the reason is because they are the closest to having that vertically integrated stack that I spoke about. I think that Tesla has the best vision models. Now with x AI, they'll have one of the best LLMs and reasoning models, and they'll be able to eventually stick that on Dojo. And then all of that will be in all of the physical AI that you will interact with in your daily life, whether it's a robot or whether it's a car or whether it's a robotaxi. So that's number one. And then number two, for many of the same reasons, I think Google, Because you'll have the Gemini family of models, which just absolutely kick ass. Like v o three, which we haven't really spoke about, is gonna destroy Hollywood, like in the next year. Like Hollywood is done, I think. But they're landing model after model. They have the TPU, and the next generation TPU, I think, is exceptional. They're baking quantum, and then they have an entire funnel of billions of people that they can direct experiences to. So Tesla one, Google two. Thomas Laffont (00:31:55): Chamath, quick follow-up on that. I'm curious on Google. This is the because I I oscillate a lot on this particular name. Can Google win if search declines? Chamath Palihapitiya (00:32:05): Yes. And I think that what probably has to happen is, bear with me when I say this, but if you had to boil down Google's economic North Star metric, right, not the value North Star the economic North Star metric would be price per click. And I do think that Google is extremely well positioned to pivot that to price per token. And I think that they have some emergent classes of physical AI, but they have the largest pool of people where they can generate a price per token value framework through YouTube, through Gmail, through Workspace. I think through search, but probably it's a different kind of model. It just requires them to rip the Band Aid off at some point. But, yeah, I think Google can do it. Jason Calacanis (00:32:51): I'm gonna go with you, Chamath. I'm one. My one and two are either Google, or Elon. And I'll I'll just say Elon because I, like you, I spent a day up at, x AI, and I saw what a magnet for talent he is. I got to sit in some meetings and just he was interviewing people, and he was working with that talent. 08:00 at night, there's a lot of people there on a Saturday grinding it out. It was nuts. Chamath Palihapitiya (00:33:15): I first went to XAI. In the fifteen minutes that I was in the parking lot finishing a call, the kinds of people that were walking in and out of there, you could tell they were big brains. Yeah. I don't know how you know what I mean? Like, from every walk of life, they all just looked much smarter than the rest of us. Yeah. And some of them were like chain smoking, cigarettes, and just, like, stressed out. It was crazy. Jason Calacanis (00:33:36): I hit a couple of zins. I'll be totally honest. But the reason I say Elon versus Google is I think Elon's in a unique position. I don't have any insider information here, and and I haven't talked about this. I'm not backchanneling from Elon, lest anybody aggregate this. I think what Colossus has done and what Tesla has done, both of these things, Tesla with their own stack of hardware, to your point, Shamath, hardware plus software plus the user application of FSD and Optimus. Then you put that together with the data, the real time data of X, formerly known as Twitter, plus, you know, what he's building with XAI. And, obviously, those two companies merged. I think Tesla board, XAI board have to get together, put those two companies together. Yeah. Worth a trillion, one's worth a 100,000,000,000. Agree. Put them and just have all that brainpower going in one direction as opposed to Elon Musk switching between the two. You do that, I think he wins number one. You don't do that, I think he either gets one or two. And then I think Google is going to have a better search product, Thomas. I think it's a really important point. Do they lose search share? Does it matter? What I think matters is, are their ads more effective? Is their ad network more effective? And I think based on what they know on you from your chat searches and your discussions and what they analyze in your email, just analyzing your Gmail and your surfing behavior and Chrome if they get to keep it, your Android phone if you use it, your YouTube list, and what you how when you drop off all in and when you start listening to another podcast, whatever it is, all that data all that data is gonna lead to an ad network that performs so much better that even if they lose search share, their ad network is gonna continue to grow, and I think it will increase in velocity. So those are the my top two. Freiburg, I'm curious from your position, which one do you think is number one and number two? I saved you for last because you know what we do here? Jason Calacanis (00:35:21): We save the best for last, Freiburg. Go ahead. David Friedberg (00:35:23): I think there's a difference in how I would kind of lump them. I I think that Tesla probably has the it is the best place to invest if you want to have a shot at a massive new industry. So they've got a baseline business in in, obviously, the automobiles. But I think this humanoid robot opportunity is absolutely mind blowingly ginormous. And I don't think that there's a better company on earth positioned to execute against this humanoid robotics opportunity than Tesla. So, you know, it's sort of like, I would call it a low probability, high upside sort of call option embedded within that business. And obviously, you're paying a premium for that because it is still a very healthy premium you pay for that business. I think NVIDIA, to Thomas's point, I think the common thesis is it is the most protected. The durability of the business is there. But I would argue that there's actually a low probability, but very high severity risk to NVIDIA in China. There was just a demonstration last month of a one nanometer semiconductor manufacturing process out of China. I think the more that we continue to try and isolate China from a policy perspective, the more we are emboldening investment in China, meaning from the government, from private industry into China to create alternatives to the chip stack, where The United States companies, particularly NVIDIA, have a moat today. So I do think that there's going to be an emergent competitive threat coming out of China to Nvidia. And just like we were knocked over by DeepSeek, I think we will be knocked over by some semiconductor manufacturing processes coming out of China in the near term. But the overall kind of Thomas Laffont (00:37:08): By the way, Dave, just on that point, I think Sax's work on the diffusion rule, just generally, I don't think has kinda gotten enough attention in the resending of the diffusion rule, which essentially handicapped our ability to even arm our allies, right, with our semi duct with our semiconductor technology. My opinion, was kind of a milestone and very important moment to to try and offset exactly what you were just describing. David Friedberg (00:37:37): Exactly right. I mean, there there there was a report a few months ago, and I mentioned it on the show, or maybe I didn't, or maybe I sent it to Saks and we talked about it offline. I I can't remember, but it was about a $40,000,000,000 investment being made in developing competitive semiconductor manufacturing full stack solutions out of China. So I do think that the lithography IP moat is being crossed in China. I do think that China is developing actually new technology for DUV and EUV systems. I do think that there's a risk to NVIDIA's core. Now look, NVIDIA is such a durable business. There's great modes, great advantages, but we're creating every incentive for an alternative to Nvidia to emerge from China. And then my third kind of categorization would be what's the portfolio solution. I think that's Google. I think that there's a diversification of high beta bets inside of Google of any one of which could have, call it a trillion dollar market cap outcome ranging from Waymo to quantum computing to the biologics work that Demis is working on out of isomorphic. There's a number of things that do not get a lot of attention at Google. So yes, there's a there's a core business that that may be at risk, Thomas. But I think that there's a portfolio of options you get at Google, and you just need any one of them to hit to kind of make up for the loss. But I do think also Sundar, in my interview with him, which we put out a couple of weeks ago, is very thoughtful about where search evolves to. And he is being, I think, reasonably aggressive in in trying to evolve the search product architecture to meet the market, to meet the consumer. Do give him credit for that. So Google would be in a good place for me as an overall kind of pick in that set of options. Jason Calacanis (00:39:20): So just to be clear, NVIDIA one Google two or NVIDIA Tesla? David Friedberg (00:39:23): Like I said, I think in terms of, like, having the right Sharpe ratio is how I would think about it. The alpha and the beta adjusted returns, I would put Google number one. I would probably put Tesla. Tesla's valuation, I think, already has a premium associated with those options. Speaker 3 (00:39:38): Don't know. David Friedberg (00:39:39): Yeah. So I don't know if I would really pay that premium. I think Well, Jason Calacanis (00:39:42): aside from the valuations, let's take valuations out of it. Just the the game here is who wins the AI prize five years. Thomas Laffont (00:39:49): That's how I understood it as well. Yep. So valuation irrelevant. Valuation irrelevant. Jason Calacanis (00:39:54): Who wins the AI prize? One, you're saying Google. Two, you're saying Tesla. David Friedberg (00:39:58): I think Google's in such a position. I I mean, look. Demis Demis, I think, has been fairly coy about where they are. They obviously promote Gemini 2.5, but there's a lot still coming. And as Chamath pointed out, it's not just LLMs, there's a pretty sizable family of models, including a lot of these graph based models that are being used in really novel applications that no one else is even close to, no one's spending time on. I mean, of the weather forecasting, it might seem small and trivial, but it's a demonstration of Google's competency in core model development that shows an understanding and a depth of research and work that goes well beyond LLMs. So I'm pretty bullish on the depth of talent, the full stack. Jason Calacanis (00:40:43): And whatever they learn there could apply to Gmail, apply to search, could apply to ads, could apply to YouTube algorithm, right? It just goes up and down. David Friedberg (00:40:50): Yeah. From a product perspective, I do think you see this kind of multi model emergence that we're now seeing that no one talks about the single model that sits behind the application. There are multiple models that work together and obviously this agentic architecture unlocks another layer of not just kind of solutions to complexity. Sure. And so there's there's quite a lot, I think, that's emergent here, that Google will start to kind of benefit from, in the year ahead. Thomas Laffont (00:41:20): I mean, for those of us, you know, who love tech, right, if we if we step back for a minute, I really feel like to use the analogy of this podcast, like, we are now at the WSL World Series of Poker. Right? We got seven companies around the table. The stacks are trillion in size. Right? And all of us are gonna get a front row seat to see what happens over the next five years. I mean and on top of that, we're gonna get to analyze, bet ourselves on who we think is gonna win. We know there's some other companies that are pushing to get at that table, right, with some sharp elbows. I mean, what a time to be doing what we're doing. David Friedberg (00:41:55): I don't know if I love the analogy because I don't think first of all, it's a zero sum game where there's this x number of chips and someone ends up with all the chips. I do think you could see as an example, just talking about the scenarios we just described, Tesla developing an extraordinary humanoid robot business that's worth a trillion dollars. Google building, you know, to Chamath's point, a media empire based on generative AI in in media. And then, you know, NVIDIA building an entirely new chip stack that everyone's participating in. So all of them in an ecosystem based way could could be major winners here. Thomas Laffont (00:42:26): You're right. I I didn't mean it in the zero sum nature of it. I meant it more in the in the stakes. Right? And Jason Calacanis (00:42:33): and And there's a lot of hands to be I like the analogy because there's a lot of hands to be played, and there is a price pool. Right? And you and you could have three or four people at that table. One thing I just wanna point out here is just speaking of regime change. What is going on at Apple? Like, they Siri was just the early idea of an AI agent. It's just totally. It's disgusting. It doesn't work. It's embarrassing. And then their biggest developer conference, they're redoing the UI. Like, this happening. For regime change at at at Apple? Chamath Palihapitiya (00:43:03): No. This has happened many, many, many times in many industries before, which is that companies that were stalwart organizations transitioned themselves from being a growth business to being a cash cow. And these are well documented transitions, and it requires an extremely brutal reset if you wanna shake that up. Yes. I think that the same thing that I think you have to respect Apple for, which is stability, the duration of some of their best longest serving executives are there for twenty and thirty years. On the scale of innovation, it's a horrible thing. And the reason is that we all just get old, our skill sets become rusty, and we don't have the energy or the capacity to think about what the future actually looks like because we are not living it. And then what happens is you task those decisions to people that you try to hire. But you saw it in the clip with Sam. Even in all of that crazy recruiting chaos that's happening right now for these brilliant machine learning and AI people, maybe that's a fight between OpenAI, Meta, and maybe Google. But what you don't hear is Apple. So who's Apple getting? I have to think that Apple is not getting any of those people. So by the time you end up at Apple, it's just a different caliber of person. Thomas Laffont (00:44:30): That is true. Chamath Palihapitiya (00:44:31): And they're living inside of a cash cow organization that's going to optimize for don't make mistakes. Jason Calacanis (00:44:38): Right. Chamath Palihapitiya (00:44:39): But that's hap it's happened to HP. It's happened to Lotus. It's happened to Intel. It's happened to General Electric. It's happened to umpteen companies. Jason Calacanis (00:44:49): It's just shocking. Chamath Palihapitiya (00:44:50): And it's happening to Apple, so we should just not sweat it and move on. Jason Calacanis (00:44:54): I don't know. Thomas, what are your thoughts? I mean, it's kind of shocking with all that cash, and they don't acquire anything. They had project Titan, $10,000,000,000 to build their own car, and they just shut it down. Imagine if they kept going with that. You think regime change time? Maybe Tim Cook retires and put somebody who's a product person in charge of it, or maybe they should merge with Tesla and put Elon in charge of it all. There just seems to be no new products coming out of there. Like, it's absolutely confounding that they're optimizing for share buybacks and earnings per share instead of having some amount of that money go towards innovation and acquiring companies. Biggest acquisition is Beats? Give me a break. Thomas Laffont (00:45:33): I mean, it's interesting. Right? For me and I've studied Apple basically my whole career, and it's kind of interesting. Right? Because if you think about the their defining competitive advantage, right, was the integration of hardware and software that led to the beautiful MacBook that we're all using. It led to the iPhone and, right, the fact that they were so coupled between hardware and software, the user interface, you know, etcetera. And I think it directly led to them winning, let's call the the mobile era. Right? But I think back to Chamath's point, and I think the analogy holds, in AI, they're the opposite. Right? They don't control, I don't you know, the silicon. They don't control the underlying models. And so now they're back to maybe, you know, using a historical analogy, the PC makers who didn't control the OS. Chamath Palihapitiya (00:46:20): That's right. Thomas Laffont (00:46:20): So I I think the good news for them is, look. They still have a monopoly on users. They have 3,000,000,000,000 of market cap to kinda play with. So I think it's way too early to count them out. But I think, you know, the market let let's posit. What's the most extreme thing that they could do, right, just for just for intellectual sake? Right? Buy OpenAI for 500,000,000,000. I'm just gonna put a crazy thing out there. Right? So you think, okay. That's the most extreme. Well, is it even that extreme? And what would Apple stock do that day? Chamath Palihapitiya (00:46:52): Go up. Thomas Laffont (00:46:53): That's my view too. Right? I actually think it would go up, not down, even if they did something like that. So I do think they need to be kind of aggressive. I do think to your point, I think, Freeburg, it is important that, you know, all seven of these companies could actually win and do well. Right? That that is a absolute possibility. But I I would love to see them be a little bit more aggressive. I mean, you guys remember when Steve Jobs bought Fingerworks. Right? It was this tiny acquisition. They made this little trackpad that you could use your fingers on. No one figured out why they did this and then in turn into multi touch and scrolling. Right? So I think it's it's gonna be fascinating to see what they do. Jason Calacanis (00:47:31): Thomas, that was a great question I was about to ask. If Apple could do one thing, they could do one internal project or buy one external company, maybe we could do both around the horn. What would we advise them to do? My number one is build a humanoid robot. Like, how does Apple not have a humanoid robot? That seems like that's obviously the next giant consumer market is having Optimus or Figure in your house. Freebert, I'm gonna go to you first since I went to you last last time. Is there a product that they could do, that they could build, that they would be uniquely suited to that would turn this all around? If you could pick it on their road map, what would it be? David Friedberg (00:48:06): I do think there is. I do think they're doing it, and I do think they have a shot at winning, which is this kind of ambient AI assistant. I don't know about you guys. I must own 30 friggin Apple devices. I have many Apple computers I use in different offices. I have phones. I have many AirPods. I got everything, watches, everything. I'm ubiquitous on the Apple platform. So I'm an easy transition into this if it works. So as everyone races to build kind of the agentic AI assistant that is sort of in my ear all the time or available where I don't have to stare at my frigging phone like this, It is a great unlock for humanity. It's a great unlock as a consumer. It's feasible technically. And I'm sure Apple of everyone that we've referenced today is best suited to both access consumer design and engineer the solution in a way that can be truly transformative. I think it references a little bit what Johnny Ive and Sam Altman have been talking about doing, but I do think that this is exactly the direction Apple is headed. And I do think that they've got a very great shot at at winning at it. I don't think they need to own the full stack to be successful here. Jason Calacanis (00:49:16): Got it. Okay. So we got Optimus. We got the device you're talking about, this Ambient Assistant is part Siri and part maybe a pendant that records your behavior in the world and gives you feedback to it. And that's what they're calling a puck perhaps that Johnny Ive has made or these pendants that record everything. Thomas, what's your thought on the one product they could create? Thomas Laffont (00:49:36): To that point, it's interesting to think that the AirPod business at Apple is three x OpenAI's revenue base today. That's right. That's the AirPod business. David Friedberg (00:49:46): And by the way, let me let me just say one thing about this. We all think about devices in the context of a single device being an assistant. I think if there are more devices integrated into our lives, and the assistant is ethereal and ubiquitous amongst the devices, it's almost like the Next Generation, you walk in, you say, Hey, computer, and there's always a device available that's doing things. There's always a device observing. There's always a device able to take care of things for you, whether it's in your ear, whether it's your phone, whether it's your watch. But basically these devices all, instead of acting independently, they all know what you've been asking or talking about with the other devices. And so you could get in your car and you could pick up, you know, the conversation you were having, you know, while you were sitting in your office in front of your computer to do work. And so the agent effectively is almost like this ethereal ambient assistant. Everywhere you go, the agent is there. Jason Calacanis (00:50:38): They could even be in a candle lit bath with you. Freyberg could be in there. They could David Friedberg (00:50:43): well, I mean, by the way, think about also, you know, it it it having identity, so it knows who you are. But I could be in your in your home, JKL, not that I would ever get invited to your home. But let's say I was there. Yeah. You know, I could walk into the the living room and there's your puck and it start talking to me because it knows Jason Calacanis (00:50:58): It's you. David Friedberg (00:50:59): Who I am and yeah. It's like it it knows me. Yeah. So there's Jason Calacanis (00:51:01): You and I, I have a bath for two. You and I could be a candlelit bath for two and Chamath Palihapitiya (00:51:04): be And it David Friedberg (00:51:05): would know the when when each of us are fighting over what music we wanna play, the assistant will, you know, hear out the debate Jason Calacanis (00:51:11): and make sense. Shabbat, do you have a a device before we go on to IPOs here? Do you have a device or an angle for Apple to go after if they were truly ambitious? Or maybe they are, and it's just in stealth. What do think? Do think it's the goggles, the glasses? You think it's a glasses? You think it's a pendant? You think it's optimist? What do you think? Chamath Palihapitiya (00:51:26): I don't think they have any chance of anything. Thomas Laffont (00:51:29): Great. Love it. Chamath Palihapitiya (00:51:30): I would take the exact opposite of what Friedrich says. Look at this chart, and I'll tell you why. K. Jason Calacanis (00:51:35): Here we go. Chamath Palihapitiya (00:51:36): This chart is not this chart is not a strategy. So this is a chart of Apple's revenue. And what you see is iPhone has completely stalled out. And so to Thomas's point, where do you make money? You make money in other hardware. This is not a strategy of success. This is a strategy of inefficiency. I lost my AirPods. I need to buy a new pair. Oh, the cables changed. I need to buy a bunch of those. This and that. And a this and that strategy is not a strategy. It's a tactical play for revenue optimization in the short term. A company that focuses on this kind of revenue growth is not capable of creating something that's exceptionally unexpected. That will come from a new company who has no ties to the past, has no nostalgia on the fact that we're gonna swap out the connector type and, you know, book another billion dollars. What Thomas said is an indictment actually about their ability to do it. When your AirPods business is two or three times bigger than OpenAI, what there is internally when you try to have a strategy meeting about what to do is derision about OpenAI because you're like, that's small. And even our AirPods business is three times big. That's what some smart ass MBA will say in that meeting, and it'll shut the meeting down. So how do you expect that culture to then all of a sudden get their act together? I think it's exceptionally hard. David Friedberg (00:52:58): It's a good the clip on cue. Play the clip, Nick. It's a great point. Here's the clip. I'm Apple nostalgic. Jason Calacanis (00:53:05): Me too. Bring Steve Jobs back. Watch this lunacy. Speaker 6 (00:53:08): You probably saw that Johnny Ive is linked up with OpenAI to create some sort of future AI device. Speaker 7 (00:53:14): Yeah. I don't know what that is. Jason Calacanis (00:53:15): Don't either. Yeah. Speaker 6 (00:53:16): Is this a space that Apple's looking at? Is this a space that goes beyond what you have in the current lineup of devices? Something that is more personal, maybe you wear it, glasses? Speaker 7 (00:53:27): I I think, I mean, I think we have some extremely personal wearable devices. If you want something that's aware of your environment with with audio, I think you're you're wearing one right now on on your wrist. If you want something that you can capture the environment with and see and also receive visual content, you might just have one in your pocket right now. Are there other form factors that can make sense to AI? Sure. But pretty hard to beat something that's with you all the time and glanceable or, you know, provides nice screen that you can interact with. So, yeah, I I don't know what they're working on. Jason Calacanis (00:54:06): What do you think, Charmouth? Chamath Palihapitiya (00:54:08): Again, I think I wanna be very clear about what I'm saying. That is a very competent Craig Federici, very, very competent executive. And whoever the person beside him is, that guy's, I'm gonna assume, competent as well. They're competent at making money the way that they've made money for the last seventeen years with no meaningful disturbance. And I think it's just something to appreciate that after seventeen years of unmitigated linear success, it's very difficult to retool yourself. It's like asking Michael Jordan to go and all of a sudden become an all star baseball. It doesn't work. And so I think and I think it's okay, though. This is my point. It's okay, guys, to have creative destruction of companies. Like, there was probably a version of us blathering on about HP and being nostalgic about the transistor radio that they made and the, you know, HP 12 b calculator that they made. And, my god, why can't they figure their shit out? And where are we today? HP doesn't even exist. It's okay. Jason Calacanis (00:55:15): I mean, just, Thomas, the fact that they launched Siri, they bought that company, and Siri can't do anything other than, like, an alarm, can barely play a song, it barely can do directions. I I I mean, literally, we're in year, like, 27 of Siri, and it can't do anything. And then I have the the Google and Grok voice. And when I turn that on, it does whatever I want. It will load on my Pixel. It loads other applications, fires it off, the specific tasks in it. It's absolutely disgratiate. Your what? Chamath Palihapitiya (00:55:46): On your Pixel? Jason Calacanis (00:55:47): I have a Pixel. When I when I flip open my Pixel. Chamath, I'm learning to you. I have the Pixel nine, Chamath. It's the Anaconda of smartphones. Pixel nine foldable. Got it. It's the greatest assistant ever. It's what Siri it's what Steve Jobs showed Siri. I had you at nine? Chamath Palihapitiya (00:56:04): He had me at Anaconda. Yeah. Jason Calacanis (00:56:05): I had you at nine inches? Yeah. We can all aspire. Maybe get Roman. Thomas. Get extra inch. Thomas, go ahead. Thomas Laffont (00:56:11): Chamath, I would argue to you that I think this management team has done it once, and it's in the transition of their gross profit base, which doesn't show in the chart that you just highlighted, but was something that I kind of lived as an analyst covering the stock for a long time where if you remember over a decade ago, 90 plus percent of their gross profit was a onetime hardware sale on the iPhone. And no one thought that they would ever be able to get away from the drug of selling that one iPhone unit. Right? And cut to, you know, over a decade later, it's 40%. Right? And I don't think they get enough credit for actually transitioning from hardware to a recurring gross profit base. But look, you you might argue that that was an easier pivot and challenge than what they're gonna face, and so let's see whether they can do it. The other thing, guys, I wonder about, let's I know we wanna talk about IPOs, but I do wonder whether Zuck buying scale for 15,000,000,000 gives air cover for other companies to really start being aggressive. Right? And and to me, as we think about Circle and CoreWeave, two companies that have gone IPO recently, it's it's kind of amazing kind of numerically that the charts are almost identical even, you know, on a dollar basis, on a share price. Right? Because to me, what it says, we were talking about the dispersion of the max seven before. Right? Which are gonna do well, which are not. I expect we're gonna have a lot of opinions on this over the next few years. And frankly, they may change. We, you know, we may think Apple one way today. It may change in a month. Right? But I do think the market is starting to realize that there is dispersion that AI might create some all winners or some winners and then some losers. Is starting to think about, okay, how do I want to be positioned for the next five years? What are big open ended growth opportunities? And here comes two companies, one levered to crypto, right, and the other levered to AI. So I don't think it's a surprise. To me, these things are intertwined. Chamath Palihapitiya (00:58:11): You're a 100% on because here's the thing. The average profit margin of the S and P four ninety three is, drum roll please, 12%. The average growth of the S and P four ninety three is, drum roll please, single digits. So to your point, why would you be long any of these 493 companies that may turn around and one day just get decapitated by something you don't even know that's getting cooked up by a couple kids in a garage using OpenAI or Grok or what have you? It just makes a lot more sense when you find investable companies in the big themes of the future to at a minimum hedge. Right? Be less long the past and frankly make some bets about the future. And I think that that's where you're seeing these IPOs just absolutely rip. What is a better comparison in my opinion are the companies that are truly levered to the future themes of AI and crypto versus any of these IPOs that have happened of companies that are not. And I think what you see is there's a dispersion there as well. And they are being treated almost as similarly, Jason, as the S and P four ninety three. Mhmm. It's like, yeah. It's good. Yeah. It's fine. They get some reasonable gains. But if you're levered to any of those two two trends, you're off to the races because it's just so disruptive. People don't wanna be bag holding these old legacy companies. Jason Calacanis (00:59:37): We're already into our next topic, which is IPOs and M and A. Lina Khan is no longer in the building, and M and A is back on the menu as our IPOs. As Thomas pointed out, three IPOs, March 28, June 5, and June 12, CoreWeave, Circle, and Chime. Obviously, CoreWeave up four x after going public. $81,000,000,000 market cap. Absolutely stunning. Circle, 25 x oversubscribed, six x from its opening price, $48,000,000,000 market cap. Chime, that's a neobank like NewBank, which is already public. That was up 40%, in its IPO price, but then it went down 20%, $12,000,000,000 market cap. On the other side of the ledge, we have a ton of m and a this year. So when you look at what's happening under the Trump administration, look at what's actually happening. The game on the field is three major IPOs, and then massive amounts of billion dollar acquisitions. Obviously, we talked about Google acquiring Wiz for 32,000,000,000. SoftBank bought Ampere. I don't know what they do, 6,500,000,000.0. OpenAI bought two companies, one for 3,000,000,000, one for 6,500,000,000.0. Developer Copilot, Windsurf, 3,000,000,000. Johnny Ives IO, making some sort of a puck or hardware device. Databricks brought Neon for a billion. Salesforce did an $8,000,000,000 acquisition. And then interesting, DoorDash bought two companies. Uber made two smaller acquisitions. There is a ton of activity here. What does it say about the market, David Friedberg, that we're seeing so much M and A and these amazing IPOs coming out all within the last three, four months? David Friedberg (01:01:08): Okay. So let me just follow-up to a comment Chamath made and ask Thomas his view. I have a a theory, and I haven't looked empirically to see if it makes sense. For most of the S and P 500, the fundamental profit growth is pretty anemic with the exception obviously of a couple of the big tech outliers, the MAG seven and a few others. But for for the majority of the S and P, this is a pretty kind of anemic environment relative to the transitions that are underway in the world fundamentally with AI and ancillary technology. So are the institutional fund managers hungry for access to some of these new, you know, high growth offerings And they have been held off because just to kind of go back, think it was around 2008 or so public institutional fund managers started to do crossover investing into private equities. And that scaled up and scaled up and it entered obviously a stage where it was a heavy flurry, a lot of activity and a lot of crossover late stage investing, you know, right until 2021 when things started to pop 2022. And because they were overexposed with their private equity portfolios relative to their public equities, they came out of 2122 with the market declining, and they now had a higher concentration of private equities than they were supposed to have. And so they have been kept out of the market for the last three or so years of the private market. And now is there kind of this pent up hunger or pent up demand for new issuances for high growth tech issuances? Is that what we're seeing? Is there kind of this pent up demand because they've had to stay out of the private market for three years? And if there is, obviously, it bodes well for late stage growth startups that are looking to go public because the demand will be there. And I think the reports were that the Chime IPO was, like, 18 x oversubscribed. Thomas Laffont (01:02:59): I think you're right in in something that, you know, I've talked about with you guys and, was a was a big conversation at our at the All In Summit last year was the health of the, private ecosystem. Right? And we talked about the concept of, look, if you put a dollar in, you need to get a dollar out. Right? And so I do think that we're starting to see a healthier market where we know a lot of dollars have gone in, but now we're starting to see some dollars coming out. So I think that's both in M and A, by the way, and it's also in IPOs. So I think that's one element. But I also think the second element, which is we're the tailwind of the mobile and SaaS era. Right? And even if you look at the SaaS companies, we kind of put this together in our deck when we were preparing it for our conference, this week. Chamath, I think you'll find this interesting. Right? If you look at SaaS, in 2021, the median growth rate for SaaS companies was 17%, and a quarter of those were growing over 25%. Mhmm. Okay? If you look at SaaS today, the growth rate has been cut in half, 17% to 9%, and only 5% of that cohort is now growing above 25%. So I think Dave, what's clearly happening, right, is other sectors which were predominantly seen to be growth are now slowing down, right? So that's kind of one piece. So the market can no longer just rely on saying, oh, I'm just going to own the best summer SaaS index, right, for the next decade and I'll do great because those companies have really slowed down. And I think it's starting to look forward and think, okay, now over the next five to ten years, what are the companies that can compound at maybe 25% per year over that time frame? And I think companies like CoreWeave and Circle and Chime, by the way, and others are gonna kinda fill that gap. Chamath Palihapitiya (01:04:46): I, I really like this chart. If I had to guess about what has changed from 2021 to 2025 is that most companies have realized that buying yet another vertical software solution is not gonna help their business, that it typically adds bloat, it adds cost, and it adds people. And I think starting in 2023, what people started to guess is at some point in the near future, you're going to have some AI way of rewriting all of this vertical software. And I think that's why it stopped growing. I don't think this SaaS market ever had the return on equity that it was supposed to. And I think so many companies have woken up from this hangover saying, there's gotta be a better way. It can't always be yet another tool, yet another program, yet another multiyear delay, yet another price escalator. And I think that that the jig is totally up for software. Jason Calacanis (01:05:56): You're referring to the Salesforce and the SaaS category, Chamath, and what you're doing at $80.90 specifically. Yeah. Chamath Palihapitiya (01:06:03): Well, it's it's not just us, but, like, if you look at anybody that's rebuilding software, it is so much easier to rebuild software from scratch today. Like, my team of 30 people can transact hundreds of millions of dollars of work, not because we are so prolifically amazing, but frankly because, well, I think the team is good, but honestly because the underlying tool chain gives you a level of leverage. And so if you rebuild the software development life cycle using these tools, you can't help it but become much more efficient. And you can't help it but deliver custom solutions that are meaningfully cheaper. And I think, Jason, if you look at the entirety of the software that runs the world, we're gonna rebuild it. Soup to nuts. All of that Jason Calacanis (01:06:51): And the tool you're referring to just for the audience is the AI copilots that are making that are contributing 40% to code bases at Microsoft and Chamath Palihapitiya (01:07:00): Not Google. Less specifically that because those are those are good for individual people, but the software development life cycle is more the horizontal end to end of making things. Got it. So what we do internally at eighty ninety is we have an entire process that starts from the PRD all the way out to the functioning code, and we use different techniques at each step. But what you get is a fifty, sixty, 70% increase at each step, which then compounds. Yes. And so you have the ability of a team that would otherwise be able to service tens of millions of dollars, be a team that can service hundreds of millions, and then a team that would otherwise service hundreds can service billions. David Friedberg (01:07:37): Let me ask you guys your response to this theory. If there is gonna be this kind of accelerated, call it custom software rebuild of business models and you take the S and P four ninety three, do you think that we enter an era where there is a similar dispersion as we're talking about seeing in the MAG seven with the S and P four ninety three, where there are going to be probably the biggest money making opportunities for investors that we've seen in decades between those that do adopt and do rebuild using AI and those that don't Nailed it. Are lagging. Chamath Palihapitiya (01:08:15): 100%. No. Thomas Laffont (01:08:16): Absolutely. Chamath Palihapitiya (01:08:17): I had a call yesterday with one of the largest private equity funds in the world. Hundreds of billions of dollars under management, and we're doing something with them at eighty, ninety with one of their most important assets. And when you're an owner of a business and you can direct very specific change and you can rip out hundreds of millions of dollars of software licenses and replace it with tens of millions of dollars of highly customized software. It's an enormous lift to OpEx and business model quality. So why doesn't it happen more? The reason it doesn't happen right now for this S and P four ninety three is that the IT organizations inside all companies essentially speak a different language than the CEO, the CFO, and the board. So if the CEO, CFO, and the board of directors of the S and P four ninety three speak English, the IT organization speaks Mandarin Chinese, and you get away with saying all kinds of bull I'll give you an example. I went to a CIO conference. One person that I met, an $18,000,000,000 a year IT budget. What the fuck does that actually even mean to spend $18,000,000,000 a year on IT? I'm not saying that this is a mag seven company, guys. And when you take that example and you multiply it by 50 and a hundred and four hundred and ninety three examples of people spending money, there's an entire cartel of influence that's been built in software that's gonna get undone because you're not gonna be able to justify it, Friedberg. Jason Calacanis (01:09:58): Absolutely correct, Shabath. And the response from the SaaS industry is changing from the per seat model as the number of employees at these companies continues to get lowered. Obviously, Microsoft, a lot of layoffs. Andy, Jesse, talking about layoffs. They're moving from the per seat model. They're not taking this laying down. They know that people are gonna make custom software. So what they're doing is they're moving to a consumption model. So you're seeing people charge per call, per customer support call, etcetera. Chamath Palihapitiya (01:10:26): I know, but that's work. Well, it's I'll tell you why it doesn't work combination. David Friedberg (01:10:30): Hold on. Hold on. Jason Calacanis (01:10:31): Let me finish. The other thing they're doing is they're dramatically lowering the number of people and the developers they have on their team. And then a lot of what's happening in the background is the third piece they're doing is they're starting to do roll ups, and people are starting to talk about how can we take, you know, 20 of these SaaS companies, lower them just like you're doing to compete. Shmuthi, you're the No. Was just gonna say playbook. Chamath Palihapitiya (01:10:53): Well, I just wanted to comment on this, like, consumption based pricing. It doesn't work. And what I mean is you can have some adoption in the short term. The best example is Snowflake, but in the long term, it destroys your business. And the reason is because you don't know which data is valuable, and you're not gonna put up with a variable business model that increases more and more cost because you need to trap everything. And so what happens is all of these other companies develop around you. People go back to Postpress. People go to Supabase. They find all of these ways of saying Snowflake makes no sense. And the reason is because in this world, nobody's gonna pay consumption because you're like, how do you expect me to, you know, hold and store and pay for terabytes and terabytes potentially a day of data? It's not sustainable. Jason Calacanis (01:11:39): We'll see if Intercom, Salesforce, HubSpot, and we see if all of those people start Slack start losing their customer base or if they lower their pricing to make it just too easy to keep those systems in. Thomas, your thoughts? Thomas Laffont (01:11:51): Yeah. So two quick thoughts. Number one, Chamath, to put a kind of a mathematical frame on this. Right? We know that Anthropic is kind of the level zero of cogeneration. They're they're doing incredibly well at powering companies like Cursor. Right? I think, and this is order of magnitude correct, that Anthropic in Q1 added 70% of the net new ARR in the SaaS industry, right, defined by public SaaS companies. Right? So let's just think that the company in AI that is most powering the disruption of SaaS added three quarters of the net new of the entire industry. Right? So that's kind of point number one. I think Friedberg, point number two, I think what we're seeing in the max seven, right, where we're starting to have debates about who's well positioned and who isn't, who's going to win and who isn't, right, is actually as it was in the past five years, going to be a broader lens into the S and P four ninety three. I think inside of boardrooms, inside of every investment committee, you're going to see the exact same conversations that we've been having about the max seven. Right? Who who's well positioned? Who can win? What are the management teams maybe like Zuck that are aggressive and bold and capturing the opportunity, and which are the ones that are not. So for me as a stock picker, right, I think over the next five years, I couldn't think of the more interesting time where we're actually gonna see dispersion between winners and losers. Chamath Palihapitiya (01:13:12): And do you think that these roll David Friedberg (01:13:13): up models make sense? So you've probably heard, and I don't know if you guys have considered this, but obviously, fund managers are putting together pools of capital to go out and buy businesses that they can then apply their know how. They're bringing smart people in AI to then create a category killer and go after that market. And are you guys participating in that? And how do you kind of view that opportunity? Are all the public companies basically too mature, or are some of them gonna kind of go after this type this model as well? Chamath Palihapitiya (01:13:45): It goes back to whether you can attract the talent to go and do these things. My advice to this large private equity firm is you can probably try to stand up your own AI org, but I suspect you're gonna get the person that didn't get an OpenAI offer, didn't get a Meta offer, didn't get a Google offer, didn't get an $80.90 offer, then didn't get an Apple offer, and then that's the person you'll hire. How good that person will be? Who the hell knows? I think the problem is that even if you take some of these kind of meh industries and roll them all up, you ultimately have to find a buyer who wants to own that business after you. So the question is, like, if you were to buy a bunch of accounting firms or law firms or IT services firms and you do an incredible job, Who wants to buy that in seven years? Meaning, if you talk to like, if you went to the OpenAI demo day, there was this really interesting chart where Andre Karpathy talked about integrating Google login into one of his apps. I think it was his MenuGen app. And the comment he made, profoundly hit me, is like, why am I doing any of this? Why isn't this just one click behind the scenes? And you could take that generalization and apply it to all of IT services. Why does any of that exist? Why isn't it all one click? And eventually, if these agents become smart enough, the fear that I have is that there is no terminal buyer for many of these companies. David Friedberg (01:15:16): But they could still be public, Chamath. I mean, could trade at some multiple of cash flow and you're basically arbitraging the cash flow. But I'm not talking about the private equity trade. I'm actually talking about the public equity trade. If you look at the April companies Chamath Palihapitiya (01:15:31): Those are better positioned. Think, like, instead of an IT roll up, I think what you could do is probably sort like, here's what I would do. I would take the four ninety three, and the filter that I would apply is what offline assets do they have? What online assets do they have? What percentage of those assets are defensible and unique and exist in a post AI world? And what percentage of those assets disappear in a post AI world? And I think where I would end up is I'd, like, own a specialty chemicals company or something. You know? Like, you're still gonna need lubricants and stuff, and you can find some way to make it. But if you're, like, a David Friedberg (01:16:07): We know you need lubricants. Sorry. Go ahead. Chamath Palihapitiya (01:16:09): You know, I love the lubricants. Jason Calacanis (01:16:12): But No ditty. No ditty. Chamath Palihapitiya (01:16:14): But baby oil making, you know, like, just David Friedberg (01:16:17): Five by the crate? Jamal, do you wanna talk about your SPAC tweet? Uh-oh. You know the market's back, Chamath Palihapitiya (01:16:22): we see this much M and David Friedberg (01:16:24): A. Play the siren? Can you play the siren? What? Chamath Palihapitiya (01:16:27): Well, as with all my David Friedberg (01:16:29): tweets combo. Like a combo of each party. Yeah. Chamath Palihapitiya (01:16:33): As with all my tweets, it starts when look. Here here's X is an incredible platform. I use it for David Friedberg (01:16:39): Pull up the tweet. Pull up the tweet. Chamath Palihapitiya (01:16:40): I use it for a lot of things. Jason Calacanis (01:16:42): You're in your filling phase right now, man. You're full supervillain. It's so great. Chamath Palihapitiya (01:16:46): I love it. The retweet is more important. Yeah. I love retweet. Jason Calacanis (01:16:50): Here we go. Here's the tweet. Chamath says, incredible that almost 58,000 people voted in his tweet if he should launch a new SPAC. So, give the people what they want, Chamath, or what? Chamath Palihapitiya (01:17:01): Well, I first I first started this because I when I use x sometimes to to just to, like, sound off because it de stresses me during the day. Okay. And, like, I'll troll people or whatever. And then I just did this, and I was so impressed that 58,000 people voted. But really what happened was I had a lot of very smart money people on Wall Street and some crypto folks call me that I respect. And and, basically, what they said is, like, it would be really good if you did it. So I don't know if I'm gonna do it, but I'm heavily leaning towards doing it. Jason Calacanis (01:17:31): Well, the argument to do it is you learned a lot since last time. There's a lot of inventory there. You've got a lot of access to premarket companies. I think what people need to understand is when you're doing SPACs and and correct me if I'm wrong. Chamath Palihapitiya (01:17:42): Here's what here's what I'll say, Jason. This poll and this community note will be in every single document I do. Nobody that is listening to this should participate in this. Okay. This is going to be for me and a handful of, you know, advanced large pools of money. You should stay as far away as possible. K. So there's a disclaimer. I do next. Jason Calacanis (01:18:04): Don't participate, and show up next back. That's that's the rule here. Chamath Palihapitiya (01:18:07): Stay on the sideline. Do something else. Jason Calacanis (01:18:10): Don't come in the arena because we're trying things. David Friedberg (01:18:12): Tomav, don't you have enough going on? Like, why would you spend why would you do this when you have Jason Calacanis (01:18:16): because fate loves irony. Fate loves irony. Chamath Palihapitiya (01:18:18): Irony, bro. Fate loves irony. Jason Calacanis (01:18:19): It'll be hilarious. It'll be the greatest IPO of all time. The poll is back. If the Chamath Palihapitiya (01:18:24): poll was yes, I'd be like, oh, This is the last thing I need. Jason Calacanis (01:18:27): In SPAC. Let's go. David Friedberg (01:18:29): Thomas, commentary? Thomas, you're gonna buy the Jason Calacanis (01:18:32): all in SPAC. What's going on? Chamath Palihapitiya (01:18:34): Is the SPAC market coming SPAC or Thomas Laffont (01:18:36): I'm open to all great companies coming to the public market. Jason Calacanis (01:18:39): Love it. Love it. I mean but Chamath Palihapitiya (01:18:41): Actually, Thomas, can I ask you a question? Like, tell us about the state of liquidity and actually about IPOs and SPACs in general. Like, where's your where's your temperature on it? Just give us a read on what you think. Thomas Laffont (01:18:51): I mean, look. I I think we're getting real world data, Tramath, right, like, in real time, not just from kind of higher visibility companies like Circle and CoreWeave, but Chime also did really well. Keras, company, you know, more in Dave's wheelhouse, right, also just coming out. So and then wait till we see the flurry of s ones that have already been filed. Right? Figma is a is a generational potential company, right, that's gonna be coming. So I think we're gonna see fantastic assets coming out. And I think the market is saying we're open for business. The the max seven is controversial. To Dave's point, the the S and P four ninety three, there's gonna be lots of winners and losers. It's maybe not as obvious. There's gonna be some dispersion. So bring on the new cohort. David Friedberg (01:19:41): I think it's the first time you could probably argue that you could go short the S and P Yeah. And pick a couple of winners. It's it might be the first time that I would feel in the last twenty years because I I'm pretty negative on people being able to kinda pick stocks. But I do think that this is such a transformative moment that if you really have a sense for what's possible, you could start to see category killers emerge out of the S and P, and it's an opportunity to short Jason Calacanis (01:20:03): the S and David Friedberg (01:20:04): P and pick a couple winners. Chamath Palihapitiya (01:20:05): Totally. Do you Thomas, but do you do you care about how these companies go public? Like, do you care about SPAC versus direct listing versus IPO? Thomas Laffont (01:20:14): Like, I don't. I I only care about the quality of the underlying asset and what I think it can be worth five years from now. Now, obviously, I do care about the liquidity that I'm getting in the IPO, Chamath. So am I getting a million, or a 100,000,000 or a billion as the float? Right? That's number one. And obviously, I also do care about, the percentage that is floating and I do care about the lockup. Right? So those those three elements are really important in terms of a company going public and how we think about participating. Chamath Palihapitiya (01:20:43): Give the listeners the guidance there. So for the first thing, bigger is better than smaller. Thomas Laffont (01:20:49): Correct. So it's number one, can I even buy it? Right? If if the IPO is so small, and, you know, we can't get in a large enough position, it doesn't really make sense for us. Right? So that would be kind of point number one. Right? Point number two is how much of the company is publicly floating. Right? Chamath Palihapitiya (01:21:08): Bigger is better there as well? Thomas Laffont (01:21:10): Correct. We you kinda get a truer price. Right? When a higher percentage of the company floats, it's also most likely gonna be less volatile and less susceptible, Chamath, to, you know, pricing, predatory pricing and and manipulation and things like that. Jason Calacanis (01:21:27): What's the percentage float that Thomas Laffont (01:21:29): matters? 20% is, in in my opinion, kind of a minimum. Some have gone out. You know? I think I remember correct, Tremoth, you may know this. I think LinkedIn went out of, like, 10% or something. I I remember it being really small. Yeah. And a lot of us thinking, like, wow. That is that is a Chamath Palihapitiya (01:21:45): controlled float. Yeah. Thomas Laffont (01:21:46): Yeah. Which ended up, by the way, being very volatile. So so number two, the float, and then number three, the lockup. Right? First, is there one? In a direct listing, there may not be one. Right? So you may you may get in that scenario to a truer price faster. Chamath Palihapitiya (01:22:03): Thomas, why do you think there's been no direct listings? Like, why has that totally fallen away after I mean, Spotify did one. We did one at Slack. And then where where are they? Like, why why don't people pursue those? David Friedberg (01:22:17): So in this Here's Thomas Laffont (01:22:18): a statistic. I actually had to double check this because I couldn't believe it. Right? If you look at the cohort of companies that went IPO in 2021. Right? And, and I'm actually not including SPACs in this particular analysis. Right? If you look at that cohort, t plus one year, the cohort was down about 40% on average. Right? Okay. Fine. Maybe they went up too high. 2021 was a peak. They didn't do well in one year. T plus five years, it's down 50%. Right? Which which really kinda shocked me. Right? So I think there's kinda scar tissue on both sides of the table, on the buy side about, wait. Hold on. What am I really buying? And how do I make sure that, it's kind of a sustainable kind of company? But frankly, probably also from boards, right, who are taking their best assets public and may just wanna pursue a more conventional approach in the beginning stages. Right? I can tell you for us, direct listing versus IPO makes makes no functional difference. You know? I think each has a benefit and I think in some, depending on how how concentrated your ownership base is, how understandable your business model is, and things like that. But we just want these companies to come. Chamath Palihapitiya (01:23:33): There's a market behavior, by the way, in direct listings. And I've I've mentioned this once, but I've been in two transactions with direct listings. The first was Slack. And in the execution of it, we miss executed. We, meaning me. Because I had a huge ownership of Slack, but I didn't know what to do with it. And I ended up distributing portions along the way, and it then went through all kinds of turbulence, and then it it got acquired slightly above the IPO price. And what I learned in retrospect was the best trade is actually the first day trade on a direct listing. So then when it came back around and I got a distribution the day before of Coinbase, and I and I mentioned this to Brian, this was not a judgment on the company. I said, if this direct listing process is gonna map to what I've experienced at Slack, the right thing to do is to sell. And I sold that on day one at $335 a share. And it's just it's I think, Jason, it's still not at the IPO price? Jason Calacanis (01:24:35): I think it might be getting close, but no. It's not back. Chamath Palihapitiya (01:24:38): So these yeah. So these direct listings are not Thomas Laffont (01:24:40): what they're Chamath Palihapitiya (01:24:40): attracted to be either. Yeah. Jason Calacanis (01:24:42): Yeah. We look back on SPACs, I think SoFi is above the price. I and that might have been one of yours for a month. Joby getting close. These were venture investments. These were late stage venture investments in your mind, Thomas. And then retail tried to become venture capitalists, and they didn't have the $5.10 year horizon that we as venture capitalists have. Is that your assessment of it? And are there any great ones that came out of the SPAC movement? Thomas Laffont (01:25:05): Well, I mean, the the direct listing era, as an example, let's talk about Spotify, right, which basically has 7x, right, over that period. So, again, I it's hard to talk about, right, causation versus correlation. That's why, like, I think ultimately for me as an ultimate kind of long term owner of these businesses, I really just care about the quality of the business. And whether you chose to go SPAC or direct listing or IPO is a mechanical decision. To me, the output is quality of business and, you know, that's ultimately what wins out. Jason Calacanis (01:25:40): Okay. I wanna end on this. You just shared a chart of AppLovin and the massive revenue per employee. This is just astounding, Thomas. AppLovin, as we can see here, had 3,600,000.0 revenue per employee in '21, now up to 7,600,000.0. They peaked at a thousand employees now down to seven fifty ish, it looks like. In related news, obviously, Microsoft, we talked about the other week, let go of 3%. They are planning on massive cuts again for sales. These are organizations that are at record cash, record revenue in an industry where we had a tradition of not firing the gray beards, and people had been at the company for more than ten years. Andy Jassy didn't come up as, like, one of the companies we think is gonna win at AI, but it might be the company most impacted by deploying AI inside their enterprise. He launched a missive. Here it is. I suggest everybody read it. When you send a missive like this to your employees, you're trying to communicate something to them and to the public market. So he published it on his website. He talks about dozens of AI projects, AI tools for advertisers, obviously, Genii for sellers, you know, their product detail page. He's talking about Alexa coming back with a brand new version, shopping assistance, everything. But then he started talking about the work for size. He says in this manifesto, in the next few years, we expect this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company. So my question to you, Thomas, is when you hear public CEOs talking about lowering the number of employees while they're growing 20% per year. This is obviously awesome for earnings, the share price, but there's gonna be a massive job displacement. Any thoughts on the job displacement, job replacement, and society navigating that? And just as well, Andy Jassy specifically, and what you think of Amazon as a business and them being a player in AI and AI being a player in their business. Thomas Laffont (01:27:38): You know, I think it's a it's an important question, and I'll defer to what Jensen answered on this topic because in my view, it's still the most credible and cohesive answer I've kinda heard. Right? And Jensen is known, the CEO of NVIDIA, an an incredibly long term thinker. And in his view, as he looks at a population that's getting older, and he wonders who are gonna be all the young people that are gonna take care of all the old people, whether it's nurses or doctors or other things like that. And in his view, we better get a lot more productive, right, to deal with our inverted demographic table. So I ultimately think this is gonna enable more young people to take care of more old people. Right? And it's just gonna create I think knowledge workers are incredibly flexible. They can take their tools from, you know, one particular skill set to another. So I think this is gonna unleash incredible opportunities for the economy. I think it is gonna make us more productive and wealthier. So I'm definitely on the more optimistic side of the scenario. Jason Calacanis (01:28:37): Jamath, any thoughts on Amazon? They didn't come up, but, obviously, AWS crushing it, and they're a major player. And they have their own silicon they're making. You mentioned that being an important part of the stack. And then you have optimists and robots figure that are gonna be in their factories. That's a lot of jobs, delivery robots. They're doing drones like zipline. They have their own version of it, obviously, and they're doing ZUCs. So if you just look at their behavior and you look at their investments, they're massively, massively investing in robotics, self driving, and chips. So they're pretty hardware focused. Yeah. Chamath Palihapitiya (01:29:09): For physical AI, they're a kingmaker in parts because they're a a sink for demand. So they'll just generate so much demand for robots. So if Figr lands the BMW or the UPS robot successfully, Amazon will buy a gajillion of them. If Optimus lands a successful robot that they tune inside the Tesla factory and then are ready to sell, Amazon will buy a gajillion of them. If there are drones that are delivering things, Amazon will buy a gajillion of them. So on the one side, there's a lot of typical OpEx lift that Amazon will get. I think the problem is more with AWS, which is that their success is actually their biggest bottleneck. The success is that they are not necessarily king making. They're about being a purveyor of many, many, many different things that you can find inside of AWS Marketplace. And so, you know, the thing that they'll have to embrace is, well, do I differentiate my own hardware from NVIDIA's at some point? Do I actually make a real bet on models and try to frankly buy Anthropic, which is probably their only solution, and tightly couple it in and say that, you know, if you wanna have next generation cogen experiences, they need to run inside of AWS. These are the difficult decisions that I think that Andy will have to face, and he's gonna have to spend hundreds of billions of dollars. But, yeah, the the Amazon retail side is gonna be a kingmaker for all of these physical AI things. Jason Calacanis (01:30:39): Friedberg, any thoughts on Amazon just as a company broadly? Chabot saying, hey, they're a kingmaker. That seems like a really interesting insight. You have any insights there on Amazon and they're playing a part here in the future of AI? I don't. Thomas, any closing thoughts here the sort of old old guard, Microsoft, Amazon, and their employee count and the cuts we're seeing there, and what these companies will look like in the future in terms of revenue per employee. They're not hiring young people. They're getting rid of the old folks. They're just advancing, it seems, at a at a they're adopting AI pretty, severely at these companies. David Friedberg (01:31:19): What are your thoughts there? Thomas Laffont (01:31:19): I'm gonna play I'm gonna play the role of J. Cal, and I'm gonna ask a question to all three of you guys. David Friedberg (01:31:24): Oh, here we go. Thomas Laffont (01:31:26): So Microsoft's employee count peaked at about 250,000, you know, call it about a year ago. Who here believes that in five years, Microsoft will have more employees than it does today? Chamath Palihapitiya (01:31:40): More. I'm gonna say the same. Jason Calacanis (01:31:43): I think they'll have just about two fifty plus or minus 10%. I don't think if I if I could pick push as the answer, would pick push, which is they're gonna get 10% better every year with AI, 20% more efficient. Therefore, they don't need to add people, but I also don't think they atrophy much more. So maybe they have two twenty five, two fifty. Thomas Laffont (01:32:02): Why why'd you say more so quickly? I'm curious. Chamath Palihapitiya (01:32:04): Oh, so this chart, which I think is like a very dangerous vanity metric, is why. So what Microsoft touts is what percentage of code is generated by AI without answering the more important question, which is, is that code useful and good? And if you ask that second layer, Nick, I sent you this tweet from Yan Lakun, and I'll tell you that this is my lived experience as well, is most code generated by AI is crap. And most of the tools that we use, you know, the reason we call these tools app crappers is because most of the code that it generates is crap. So it's great in a single player mode, but transitioning from single player mode to a complex enterprise environment is not possible today. So I think that Microsoft puts these metrics out because they wanna seem that they're on the front line of it. But I suspect that this is just like, you know how you used to hire McKinsey consultants to fire people because it was good air cover? It's probably just air cover to fire a bunch of folks that they probably wanted to get rid of anyways, but it's not related to that chart. And the reason is that Jan Lecun's tweet is true. When you allow these models to run over complicated tasks over long periods of time, the error rates compound to such a degree that the that the resulting output is not worthwhile. And so until that problem is fixed, which I'm sure it will be, and I and I and I'm gonna bet that it will be, the idea that all of a sudden it's because of coding agents that people are getting laid off, I think is a fallacy. So I suspect that Microsoft business on the margin grows. Back to Dave's point, some of the $4.93 shrink and go away. It'll be cheaper for Microsoft to bundle together a bunch of other products that are point features today. And so they'll have more people. They'll indeed more. The people will be different. They'll have different skill sets, but I suspect Microsoft's employee base growth. Thomas Laffont (01:33:58): Mhmm. Friedberg, what say you? David Friedberg (01:34:01): I think shrink. Wow. Thomas Laffont (01:34:04): So, by way, pretty interesting to think about. We have one decisively more, one median about the same a push and a and a less. David Friedberg (01:34:12): I only say that because I do think that there's a real probability of revenue decline in the next five years. So if you look at the enterprise install base, I think that cloud gets competed away. I do think, like, on this on the application software layer, they're gonna have a really hard time in this new world because the old school customers that buy Microsoft are gonna die. They're more likely to die in their marketplace compared to the folks that are gonna build native software, native workflows. And I'm not really where Chamath is. I think you may be right about where AI written code is today. I I don't think that that's true three years from now, four years from now, given the pace of improvement. And so in a world where you have software written workflows built for you through agentic tools, I think that Microsoft's core business for the is gonna decline. The the losers are their biggest customers, and the winners are not gonna use them. So I I you know, that that would be Jason Calacanis (01:35:06): Where are you at, Thomas? Maybe you're the tiebreaker. Thomas Laffont (01:35:10): I I'm in Chamoskamp, where I actually think the Microsoft business will be bigger, if anything, on on kind of Azure alone. And that at the end of the day, we'll just need more people to support it. I just think they'll be they'll be more relevant. They'll have more productive employees, but they'll still be more of them. Jason Calacanis (01:35:29): I'm predicting incredible growth and the same number of employees. So you guys are predicting incredible growth and employee growth. Chamath Palihapitiya (01:35:36): I think that David Friedberg (01:35:36): That's interesting. So so sorry. Let me Mass revenue, Jason Calacanis (01:35:38): less employees. Interesting. David Friedberg (01:35:40): So the thesis as as year grows, is basically where the the application dollars go effectively is one way to think about this. Right? So application dollars go there, and that more than makes up for the decline in in that business over time. Yep. Right? And there's multiple clouds. By the way, I went to the Google Next event last year, and so I I ended up going to these, like, special dinners or whatever, a couple of cocktail dinner thing because I spoke there, and I'm I saw they put me with a bunch of these people and I CIOs of, you know, whatever, Fortune 50 companies. And all of them said that they're multi cloud, like they're not, no one's going to standardize on one cloud. So everyone has to be on Microsoft and Google. And I had never really recognized this or thought about this as being a fact that it's not necessarily the best or the lowest price. At the end of the day, these guys are gonna distribute their exposure. And so I think that maybe supports your case. Very easily con I'm very easily able to see other arguments today. I'm very convinced. Jason Calacanis (01:36:39): Here's the revenue. What a spectacular revenue run. Just wow. Thomas Laffont (01:36:44): I think all four of us would agree that if we could synthetically own AWS, Azure, and GCP, if I could somehow automagically create an index of all three of those businesses, right, Chamath Palihapitiya (01:36:56): over the next five Thomas Laffont (01:36:57): years Yeah. Yeah. You wouldn't need to own anything else. Chamath Palihapitiya (01:36:59): 100%. Thomas Laffont (01:37:00): Need to own anything else. Jason Calacanis (01:37:01): Yeah. 100%. I wish Elon would take it. David Friedberg (01:37:03): So why don't you put up with the shitty part of the rest of their businesses and just own all three, and that's it. Call it a day. Because you've got to assume that if one of them wins over the other two or accelerates ahead of the other two, it's gonna more than make up for the losses that the other two might experience in their other businesses. The multiples aren't crazy on those three companies, by the way. Thomas Laffont (01:37:20): Correct. Jason Calacanis (01:37:20): Quite reasonable. Yeah. I think if Elon took what he did with Colossus and he had an AWS competitor, he would be a serious competitor in this space. David Friedberg (01:37:27): But this is like, this this Jason Calacanis (01:37:28): is at which he can build out data centers is extraordinary. David Friedberg (01:37:32): This is where Elon does better because he can actually get a better, like, fundraising in the private market with x AI then what do you have to deal with? Chamath Palihapitiya (01:37:42): He's really he's really struggling with that. David Friedberg (01:37:44): That's what I'm saying. Yeah. No. No. I'm saying it's better for him. Jason Calacanis (01:37:47): Right? Hey, guys. Look who's here. Couldn't stay away. David Sachs. Look at here. You can't get away from it. 11:00 happens on a Thursday, and you start jonesing for your besties. Welcome to the czar, David Sachs. David Sacks (01:38:00): Good to good to be back. Jake, how are you? In LA? Jason Calacanis (01:38:03): Mhmm. I'm in LA. This is David Sacks (01:38:05): You're at someone's guesthouse? Jason Calacanis (01:38:06): Yeah. Actually, this is one of your guesthouse. David Sacks (01:38:08): You you just kinda track them. I still Thomas Laffont (01:38:10): have the Jason Calacanis (01:38:11): key code. It's j cal Callan. J cal Callan is at your guesthouse. David Friedberg (01:38:16): Jato Callan. Jato Callan. Here. I'm here. Come down the hill. David Sacks (01:38:20): Still get that reference? It's getting kinda dated now. Jason Calacanis (01:38:23): Oh god. Kato Callan is ride or die. I mean, he would jump on a event day or a grande for you for sure. Let's talk a little bit here since they got you sacks. Would you be willing to talk a little bit about the genius act, which is past the senate? I think you have your fingerprints on this. Is that true? Yeah. Tell us everything. David Sacks (01:38:40): Well, it's definitely something we supported, and this is, I think, a huge milestone. I mean, just, you know, what basically happened is we had this genius act, which is the stablecoin bill passed the senate with 68 votes, got 18 Democrats, they came on board. We had to hit that key threshold of 60 votes in the Senate. That's the threshold you need in the Senate unless, you know, it's a narrow exception for reconciliation. So it's very, very hard to pass any bill out of the Senate and you need a significant amount of bipartisan support, and we got that. Now, when you consider where we were a year ago, you know, you realize what huge progress this is for the crypto industry. A year ago, you had crypto companies being prosecuted. You had this whole regulation through prosecution approach where Gary Gensler was the chair of the SEC then. He wouldn't tell startups what the rules were, but they would just announce prosecutions, and this was driving all the crypto innovation offshore. And I think we were basically poised to lose the crypto industry in The United States. What happened then is president Trump adopted this cause. He announced that he wanted to make, United States the crypto capital of the planet. He really campaigned on this. And as part of his administration, he in the very first week signed a new executive order making it clear that his administration supported crypto. We've been rooting out all the buy and war on crypto rules and regulations at the agency level, and now we have this first major legislative win. And I would expect the house will act in the next few weeks on this, and then the president will have a bill he can sign. Jason Calacanis (01:40:15): This is, great work, and it's really important because to your point, Gary Gensler's concept was, hey. There's an existing playbook. There's existing rules. Just follow those. But none of these things actually match the existing rules perfectly, so you need some new rules. They need to evolve. David Sacks (01:40:32): It was much worse than that because he would say things like, well, just come into the SEC and talk to us. You So in other words, you gotta come in and talk to us and get our approval. But then when startups would go in there and talk to them, there'd be enforcement people there writing down everything they said. And the next day they get a Wells notice and they would get Honeypotted. Yeah, they were honeypotted basically. Chamath Palihapitiya (01:40:51): Yep. David Sacks (01:40:52): And so the the response to the industry was, okay, we're just gonna leave The United States. And that that was what was in the process of happening until president Trump won the election and then changed the tone in Washington. I think there was one other really significant thing that that happened because, you know, obviously, president Trump has gotten Republicans on board with this cause, but the question is why are Democrats on board with it? During the Biden administration, Elizabeth Warren really called the shots on crypto, and it was well reported that Gensler was was sort of her ally in her pick. I've kinda joked that Warren controlled the Biden auto pen on on crypto because she really did exert that kind of influence. So the question is, well, what changed? And I think one of the big things is that in this last election, Sherrod Brown, who was the chair of the banking committee for the Democrats in the Senate, lost his seat in a close election against Bernie Moreno. And I think there were many reasons for him to lose that seat. He was far to the left of voters in Ohio. Nonetheless, he had been a successful politician there for a long time, and one of the reasons why he lost is because the crypto industry really got behind Bernie Moreno because Sherra Brown was just a a total blocker to any crypto legislation in the mold of Elizabeth Warren. And I think that a lot of smart Democrats looked at that and said, why are we dying on this hill again? You know? Yeah. And I think she Well, Jason Calacanis (01:42:16): it's also extraordinarily popular, Sax, with consumers and businesses. So there is a demand here, and Korea David Sacks (01:42:23): Well, you've got you've got something like 50,000,000 wallet holders in The US, and they're they're they're voters. Jason Calacanis (01:42:28): So that's one out of five Americans. David Sacks (01:42:30): Adult Americans. So I think a lot of Democrats said, well, wait a second. Why are we just blindly following Elizabeth Warren on this? What exactly is so harmful about this? Particularly when what we're talking about here is creating a regulatory regime. You know, it shouldn't be hard to sell Democrats on new regulations. But in this case, the reason why there's broad bipartisan support is because the crypto industry itself is calling for those regulations because having regulatory certainty is better for them than the possibility of the return of a Gary Gensler like figure who just prosecutes them without telling them what the rules are. This is why I think you're getting some significant bipartisan support. Jason Calacanis (01:43:09): And as you said, bringing this onshore is such a great portion of it. There are tons of actors who some people might describe as bad or gray or dark. Tether comes to mind with a lot of regulation against it. And now those folks who are running away with the industry, Thomas, now they have to compete with people like Jeremy O'Learn Circle, which are totally buttoned up here in The United States, and it levels the playing field. So it's an example of actually good regulation bringing this opportunity back onshore and taking it out of the gray area. David Sacks (01:43:42): Just on the whole offshore versus onshore. So it is true that the number one stablecoin issuer on the planet right now is an offshore company, and that is partly because there has not been a regulatory framework in The US and there's been hostility towards the crypto space. And so the logical reaction to that is to either not get involved in the crypto space, which is what the banks have done until now, or you go offshore. Neither one is good. And, you know, you can see in the wake of this genius act, the stablecoin bill, that the banks have now talked about getting into stablecoins. They're gonna issue one. And then also, Tether will under this act will have three years to come onshore, but the bottom line is they will have to operate in The United States. And that's a good thing for consumers. It's a good thing Jason Calacanis (01:44:32): for US. Three years to get compliance? David Sacks (01:44:34): They have three years, but they have to move onshore. Now all stablecoin issuers under this bill will have to be audited quarterly. Jason Calacanis (01:44:42): By a real audit, not just attestation nonsense. Like real audits by American David Sacks (01:44:47): Real audits. And it will verify that every stablecoin that's been issued is backed or fully reserved on a one to one basis With? With real dollars in American bank accounts that are in US T bills or money market accounts. And so it what it does is by the way, I'm not saying there's anything wrong with Tether, but this does provide additional certainty and confidence because you know that all the companies are onshore and they've been fully audited, and we know that they're fully reserved so that when you wanna redeem and cash out your stablecoin tokens, there's a real dollar waiting there to cash out. Chamath Palihapitiya (01:45:26): You prevent the undercollateralization issue. Jason Calacanis (01:45:30): Yeah. And and and by the way, David Sacks (01:45:31): I'm not saying that there is Chamath Palihapitiya (01:45:32): saying that. David Sacks (01:45:33): But but what I'm saying is now we create total certainty and confidence, which is good for the market. Chamath Palihapitiya (01:45:37): What happens if a stablecoin issuer does not like, can you issue US dollar stablecoins and not be governed under this system? Or no. You're saying because the US dollar is a US government instrument, then no matter where you are or no matter where you issue from? David Sacks (01:45:53): Yeah, all the issuers will be governed by this. And if you're a legacy offshore issuer, you're given this time period to bring yourself into conformity. But yeah, Chamath Palihapitiya (01:46:01): I'd hear Otherwise, what happens if if they don't? David Sacks (01:46:04): Well, it's a good question. I mean, I guess the exchanges won't be able to carry their their tokens, and they won't be able to set foot in The US. They'll be in violation of US laws. It's not a good place to be. Jason Calacanis (01:46:15): Yeah. I mean, you don't have to guess. There have been dozens of actions and accusations, like legitimate ones, against Tether. New York's attorney general did a major settlement with him in 2021. They've been banned from many jurisdictions and, and senate hearings. Chamath Palihapitiya (01:46:31): Tethr should just Tethr should just go public in America and be done with it. Jason Calacanis (01:46:35): Oh, well and the issue was there was deep concerns that they didn't have the deposits, and now they're they're really trumpeting the fact that they're massively profitable, obviously. So there's been tons of, you can just search Tether and allegations, and you'll find all that stuff in order to get you guys should hear. Chamath Palihapitiya (01:46:51): Tether founders a ton. Jason Calacanis (01:46:52): Sachs, I gotta give you a lot of credit. We knew that you would bring an efficiency level and some expertise to this administration. But I got to give you your flowers. We're five months into this administration, could disagree about many things. One thing we can't disagree about is that this piece of legislation is here, and we're only five months in. So maybe you could speak to the velocity at which things are getting done, and then, any other closing closing thoughts. I know you gotta get back to your day job. David Sacks (01:47:19): Jay Kal, a lot of people deserve credit for this. I just wanna give out a couple of shout outs. So, senator Bill Hagerty from Tennessee was the principal author of legislation. He did an amazing job getting Democrat votes and also bringing the Senate bill into greater alignment with the House bill, so hopefully this can pass the House very quickly. Chairman Tim Scott, who's the chairman of the banking committee, was also incredible. The majority leader, John Thune. And then we had a few cosponsors of the legislation, Cynthia Lemus from Wyoming. And then two Democrats actually were really important, Kirsten Gillibrand from New York and Angela Alsabrooks from Maryland. All of them did a great job. And we've got great leaders on the House side as well. French Hill, who's the chairman of the House Financial Services Committee, Tom Emmer, who's the whip, and Mike Johnson, who's the speaker. So kudos to all of them because I think that it really is a pretty incredible achievement that they've been able to get this bill through. Again, just a huge sea change from where we were a year ago where crypto was basically under attack. It was being driven offshore, and now we have it as one of the first major piece of legislation by this new congress. And, again, that's all because of president Trump's leadership and prioritization of this issue. So thank you to all of them for making this happen. Jason Calacanis (01:48:27): Congratulations to you, David. Hey. One, tactical question I forgot to ask you. The float on these, this is like how Tethr is making billions of dollars a year, and this is how people anticipate they're gonna make billions of dollars a year. Are they able to split that with consumers yet? Because I I remember reading an early legislation that you weren't allowed to pass on the interest made from a stablecoin to, like, the consumers, I guess. So you wouldn't it couldn't be an interest bearing account. If you buy Stablecoins, you can't get interest on it, but the issuer like Circle, that's their main business model. David Sacks (01:48:55): So Right. Jason Calacanis (01:48:56): Did that make it into the final? And and maybe you can give us some background on that. No. Chamath Palihapitiya (01:49:01): No. It did not. David Sacks (01:49:02): The way the framework works is that the Stablecoin issuers cannot pass on interest Why? To the token holders. Jason Calacanis (01:49:08): Why is that? David Sacks (01:49:09): Look, I mean, I don't know if there's a great principled reason this was a compromise that was necessary to get the support of the banking industry, quite frankly. Jason Calacanis (01:49:16): Ah, they see it as competition, I'm betting. David Sacks (01:49:18): Well, there was a lot of concern from community banks that if stablecoins were paying 5% interest, it would put them out of business. Personally, I think that that concern, although understandable from them, I don't think that that's what would've happened, but these are the types of compromises, quite frankly, that you need in order to pass legislation. I hope that at some point in the future, we'll revisit that and allow stablecoin issuers to kinda just do what they wanna do. Alright. And that'll be easier once the banks get into the act and they're participating in this industry. Chamath Palihapitiya (01:49:48): Got it. David Sacks (01:49:49): But right now, they're total outsiders, and you can understand the fear factor. Jason Calacanis (01:49:52): Alright. Sacks, let me drop you off, man. I wish we could have you on for the full show, but you're you're busy. You got a lot of things to do. Chamath Palihapitiya (01:49:58): Love you, dude. Jason Calacanis (01:49:58): Shed a little tear, and I'll miss my bestie. See you soon. David Sacks (01:50:01): Thanks, guys. Alright. Bye, gotcha. Jason Calacanis (01:50:03): We got two hours of classic all in. In part two of the show, we're gonna do an hour and a half on the Israeli conflict with Iran. We've got 90 David Friedberg (01:50:12): coming up you. Jason Calacanis (01:50:13): And we've got Ukraine Ukraine Ukraine, Meersheimer, and Jeffrey Sachs joining us in the second in the third and fourth hour of the all in podcast. How's the all in summit going, Friedberg? How's all in summit? You know, we might get Chamath Palihapitiya (01:50:27): Wait, Jason. Can I just Jason Calacanis (01:50:28): try? Wants to come from Alibaba. Who's in touch with him? I am. You? Thanks to Philippe. Chamath Palihapitiya (01:50:34): I just wanna do one quick shout out to our friend and fellow bestie Vinny Lingam. David Friedberg (01:50:39): Oh, yes. Chamath Palihapitiya (01:50:40): He is movie's coming out. A friend of ours did a documentary on It's great. Freiburg, you're gonna love this, on only David Friedberg (01:50:47): I denounce I denounce. I love Vinny. I denounce it so great. Jason Calacanis (01:50:50): This film is amazing. Chamath Palihapitiya (01:50:53): Anyways, it's called animal. Jason Calacanis (01:50:55): Oh, it's a great doc. David Friedberg (01:50:57): Perfect. Can't wait. Chamath Palihapitiya (01:50:59): Where can where can people watch it? Jason Calacanis (01:51:01): I think he's got a couple of deals that's coming local slaughterhouse David Friedberg (01:51:04): and put it on your phone and watch it at the slaughterhouse while you're there. Jason Calacanis (01:51:07): The idea. You're gonna consume a certain number of cal calories from us. Us humans were designed to eat meat. That's the number one thing we should be doing as a species is eating meat. Chamath Palihapitiya (01:51:16): Nick, can you put the trailer in the show notes so that we can get a little Jason Calacanis (01:51:19): Play actually, us out with the trailer. You can play us out with the trailer on the show. Chamath Palihapitiya (01:51:23): We'll do them ourselves. I gotta go eat. I have a photoshoot in two hours. I Thomas Laffont (01:51:26): love Oh, you gotta Jason Calacanis (01:51:27): photoshoot? Is it gonna be What's that for? You showing the legs or just the top this time? What are you showing? David Friedberg (01:51:31): What are you shooting? Chamath Palihapitiya (01:51:31): I'm gonna do Jason Calacanis (01:51:32): Blur out the anaconda. You should do Thomas Laffont (01:51:33): pixelate the anaconda. I hope it's Italian vogue. Jason Calacanis (01:51:37): What are you shooting? Chamath Palihapitiya (01:51:38): Thomas is in the general neighborhood. I I can't comment. But Oh, just tell us to bleep it out. Nice. Jason Calacanis (01:51:44): Tell us to bleep it out. David Friedberg (01:51:45): Jamal, give me a call. I gotta talk to about this weekend. Chamath Palihapitiya (01:51:47): Okay. Love you guys. Talk David Friedberg (01:51:48): to guys. Thomas Laffont (01:51:49): I'll see Jason Calacanis (01:51:49): you at four. Thomas Laffont (01:51:50): Are you guys still doing the tequila launch? David Friedberg (01:51:52): Yes. Saturday Jason Calacanis (01:51:52): night. We'll see you Saturday night. Thomas Laffont (01:51:54): Absolutely. See you there. Jason Calacanis (01:51:55): Go to allin.com slash yada yada yada to sign up for the All In Summit. Apply there for Thomas LaFonte, Shamaf Palihopatia, Dave Freeburg, and the czar. David Sachs, I am the world's greatest executive producer. We'll see you next time. Jason@allin.com. Thomas Laffont (01:52:11): Bye. Jason Calacanis (01:52:12): Play the trailer. Speaker 3 (01:52:13): We're too good of hunters. We came out of the trees not to eat the grass, but to eat the grass eaters. Meat is the most nutrient dense food that human beings can eat. Thomas Laffont (01:52:28): We're carnivores, but we're not living as carnivores. We are just better designed and more efficient at getting nutrition from meat. Speaker 3 (01:52:35): Gotta remember where we came from and what our food should be. It will change your life.