AI 杀死所有人，还是末日论心理战？OpenAI 的数学突破、耐克 2000 亿美元崩塌

Jason Calacanis (00:00:00): The canceled on us. Is that what happened? David Sacks (00:00:02): Yeah. The SIOP canceled. He couldn't take the smoke. Chamath Palihapitiya (00:00:04): He did not David Sacks (00:00:04): wanna be cross examined by David Sachs. I haven't used my legal degree in twenty Jason Calacanis (00:00:10): five years. I was up all night doing research on this. David Friedberg (00:00:15): We could still talk about it. Jason Calacanis (00:00:16): I'm so ready. Yeah. David Sacks (00:00:35): Facts. We have to talk about Anthropic. A researcher just quit over AI fears that he thinks could kill us all. Jacob Coxen worked as a researcher at OpenAI, then Anthropic over the past three years. Now he only started at Anthropic six weeks before resigning. After quitting, he posted the following to X. Quote, the people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. Quote, neither OpenAI or Anthrombo, ostensibly, is acting responsibly. They're not acting responsibly, Sachs. Quote, they are racing straight to self improving superintelligence and gambling. Gambling with our lives. This went insanely viral. I haven't seen a tweet go to a 150,000,000 views since Elon said he was gonna put the cocaine back in Coca Cola, which I think was the number one tweet of all time. Chamath Palihapitiya (00:01:33): But, Jason, can you actually explain to me how does somebody who doesn't have any followers or an account show up on a Monday and get a 110,000,000 views on a Tuesday? How does that algorithmically happen? David Sacks (00:01:45): That's a great question. We're gonna get into it. Evan Hubinger, who leads alignment science at Anthropic, responded to Jacob. Quote, Jacob is correct here. We really do earnestly believe AI could kill all humans. Exclination point. I personally think it is over ten percent within the next decade. We do not yet have a plan to solve alignment. These two posts, 200,000,000 combined, and it immediately jumped. As I mentioned last week, these things are now jumping from x and the AI community to the nightly news in under twenty four hours. Bernie Sanders, never the one to waste a crisis, said posts like this are the reason he's pro... Posing legislation to ban. BAN bans superintelligence and pause AI development. Governor JB Pritzker replied to this post saying, it's time to sound the alarm louder on reining in AI. Saxe Pooh, as our former czar of AI, do you share everyone's concern here that we're all going to die by 2030? Jason Calacanis (00:02:55): No. I don't. And look, there's nothing new here. This is the same doomer histrionics that we've been hearing from this crowd for a long time. And, you know, the media is calling him a whistleblower, but what evidence has he brought forward that we didn't have? This is all just vibes from him. Show us the data. Show us the reports. Show us the leaked information that the public didn't already have. Show us the facts. Show us the evidence. We don't have any of that. In fact, as Chamath was alluding to, this appears to be an op. How do we know that? Well, first of all, this is an account that had almost no activity, almost no followers, and no posts prior to this resignation tweet storm. If he did have prior posts, they were scrubbed. So this was a completely blank account and somehow within a day it finds this huge audience. Elon has said it never happened before. And we also know who amplified it in the first fifteen minutes. So there were basically three of these well organized, well funded doomer groups who amplified it. So Nathan Calvin, who's the general counsel at Encode AI, they're the group that basically pushed for SB 53 in California. They're pushing for all these state level AI laws. Peter Wildeford, who's head of policy at the AI Policy Network, which is pushing for, you know, all these federal regulations, having a federal department of AI. And then Daniel Cocotayo, who's head of the AI Futures Project, who just happened to drop a Rogan episode at the same time in which he used the exact same phraseology about how AI is gonna kill us all. And all three of these groups are funded by Jan Talen, who is one of the top few of these EA mega donor doomer types, who also happens to be a co lead of the Anthropic Series A. So this is a tight knit community that jumped on this tweet. So this was not some spontaneous act by an employee who said, oh, I'm just gonna post my resignation letter on Twitter. This was something that was orchestrated. And then just the final piece of evidence on this point is that someone looked at The Wall Street Journal story that covered the resignation letter, and somehow it was posted minutes before the tweet storm itself. So The Wall Street Journal David Sacks (00:05:18): was given embargo. That's what it means. The technical term is they were briefed under embargo, and they screwed up the Publishing Times. Jason Calacanis (00:05:25): Right. And this guy, Jacob Cox, and he reached out to you, Jacob, and said, hey. I wanna come on the pod. Yes. Did he not? And then he canceled this morning because maybe he figured out it would be a tough interview. If he had come on the pod, the questions I'd wanna ask are, who connected you with The Wall Street Journal? You know? This was a relatively low to mid level employee who had been there for... I've heard different estimates, six weeks to three months. Let's say three months. This is not something that'd be covered by The Wall Street Journal in this way. This is something that was teed up. He's clearly working with these doomer groups. They're going for maximum amplification. And again, he's been called a whistleblower, but what have you blown the whistle on? You know, where's the evidence? Where's the data? We'd love to see what you saw inside of Anthropic if somehow there's a problem there, but you won't tell us what that is. And in most whistleblower cases, you get the company pushing back. They say, well, no. It's not true. Or, you know, they wanna refute what he's saying. In this case, they're amplifying it themselves. Well, I think you would... David Sacks (00:06:23): A functional company, Sax, would disavow. Wouldn't a functional company disavow this Sax immediately? Jason Calacanis (00:06:30): Here's the contradiction. Chamath Palihapitiya (00:06:31): It's very complicated. Jason Calacanis (00:06:33): He's actually amplifying their message, and you saw that when his boss or the person who's running this safety team is... He's saying that, yeah, we all agree with you. And he then put it on this greater than 10% chance of extinction, which when you put a number on something that frankly is just vibes, now it takes the the message to a whole another level. Chamath Palihapitiya (00:06:53): Two questions for you, Sachs, and then I have a bunch of comments and statements. I mean, this thing is crazy. Question number one is just let's steel man the other side. What is the game theory on the scion? How do you think it is supposed to go from here had it not been exposed? What do you think they thought would happen? Jason Calacanis (00:07:12): Well, I think they know exactly what's gonna happen. I mean, they are going for maximum unification. Look, given that this this guy was at the company for a maximum of three to four months, it's entirely possible to me that he joined knowing that he would put together this campaign and Yeah. Chamath Palihapitiya (00:07:28): Yeah. So what preimanded campaign? David Sacks (00:07:29): So what was his goal? And is he a role? Agent? Oh. Is he in role or is he in coordination? That's No. Jason Calacanis (00:07:35): These groups are interested in shaping the public perception of AI. This is what they do. I mean, these are groups... Well, they're creating a a very negative perception of AI to further their case for AI regulation. And the end goal here is to create a federal department of AI. They want an AI regulator. Some of them also want a pause. Some of them also want a ban on superintelligence, well, that's what Bernie Sanders' bill puts forward. But all of them want a new federal regulator for AI, and that is what Dario himself is called for. Again, is called FDA AI, which invariably they will control. And they will basically then be able to push their preferred frameworks for regulation through this new regulatory body. Chamath Palihapitiya (00:08:18): Okay. I have another question. So now you have this very complicated moment where you have internal employees validating an employee that just left, making claims, let's call them whistleblower claims, that create at a minimum product liability issues but at a maximum may create false representation issues. You have an active s one process underway. And so how are they to handle that? Like I'll give you a couple of historical examples. You guys remember when Google was going public? I mean, Friedberg, you probably lived it. But there was an interview that I think Sergey or Larry or both of them did with Playboy, but that was well before the IPO window. And then they published it in the middle of their quiet period. And there was all kinds of noise about how that could have derailed their IPO, that they would have had to refile. In a separate example, when Slack was going public, I was on the board and I was on TV with CNBC. And we were talking about Tesla and SpaceX and I made a couple of comments about Slack positive, but not saying anything that was crazy. Was just about the network effects of Slack. David Sacks (00:09:28): It wasn't super effusive. I Chamath Palihapitiya (00:09:29): remember it. But that almost stopped our IPO and we had to go and print it out and we had to put it back into the s one and we had to disclaim these things. This seems so beyond that because this is so beyond the pale of what these folks are claiming. What does it do to their IPO process? Now, Sachs, you jokingly said stop the IPO, but what is the SEC supposed to do? What are the Jason Calacanis (00:09:52): what are the lawyers who are Are David Sacks (00:09:53): you joking or are you serious in that tweet? Jason Calacanis (00:09:56): Well, I was I was tongue in cheek in that tweet and that's why I put the scare quotes around whistleblower is because this is not an ordinary whistleblower. Appears to be doing this with the full cooperation and support of many of the employees, including his own boss. I don't know if he's doing it with the senior leadership of the company, but again, this message is fully consistent with the doomerregulatory capture agenda of Anthropic. So again, he's not saying anything that is incompatible or detrimental to his boss and that's why he's getting support from within the company. But it does raise these these questions that Jamath is talking about. And I I do think that there's a tension here in Anthropic's position that I do think implicates their IPO process. And the tension is this. On the one hand, you're asking public market investors to underwrite your company to a value in the trillions. On the other hand, your own safety lead, not Jacob Cox and the boss who then sort of cosigned his his tweet, is saying that your core product is unsolved and potentially civilization ending. I mean, at a minimum, that is the mother of all product liability lawsuits. Is that the type of liability you can just wave away with a little disclosure in the s one? David Sacks (00:11:19): Sachs, it's it's a very important point to to... For us to pause on. If they are saying this thing is incredibly dangerous and they continue to update it and release it, they're saying if something goes wrong in your enterprise, in your life, if it does a major hack, if somehow it figures out how to hack Bitcoin or something and compromises the miners, they're liable for some giant hack that occurs. That's an incredibly important point for us to, like, meditate on here. Jason Calacanis (00:11:45): Look. I think this is a time for choosing for Anthropic. I think that these games have to end. I think that they have to choose between either renouncing this quote whistleblower as a doomer op. He's basically an entry level know nothing who's engaging in hyperbole and science fiction. It's all vibes. In other words, there's not facts and evidence behind this. Right? So they can say that Or they can agree with him, you know, in which case Bernie Sanders may be right that further development should be frozen, in which case I don't see how they can IPO now in the trillions because, I mean, that is where these doomer arguments lead, is directly to Bernie Sanders. That's the reason Bernie Sanders quote tweeted this guy. That's why Bernie Sanders introduced a bill to stop further development, to ban artificial superintelligence. But if that is where Anthropic says it's going and they agree with Bernie Sanders as dangerous, how can they be allowed to IPO at this point in time? Why would any public market investor want to invest in that? So it's fundamentally a contradiction in its intention. And I think that historically, the way that Anthropic has solved this tension is they've basically said, yeah, in anybody else's hands, frontier AI is too dangerous to be developed, but in our virtuous and wise hands, it's safe. We will make it safe. We're the only ones you can trust. And everybody else in the world can see that that is the most ludicrous, self serving argument. We're not buying into it. We're not gonna grant you a monopoly on frontier AI or a duopoly through this red capture. So you've gotta give up on that game. It's patently ridiculous. I think, again, that's sort of their way out. But if that's not... If if that's not gonna be sustainable, I think they now have to choose between, look, you're either on the Bernie Sanders side of this thing, in which case why are you IPO ing? Jason Calacanis (00:13:30): It's time to stop. Or you renounce the argument that Jacob Coxen is making that it is hyperbolic, Chamath Palihapitiya (00:13:38): What there's no basis for you saw yesterday showed that they're not in a position to do that, even if they want to. I think that there are very rational, people that work at Anthropic, building a great company. The problem is is that that is in conflict with a philosophy held by enough of a group of people inside that business that they can't disavow him, Sachs, because then this entire cohort of people will go absolutely bonkers and get up in arms. David Sacks (00:14:02): This is such a good point, Shama. Yeah. Chamath Palihapitiya (00:14:05): There's all kinds of people right now quote tweeting this guy, essentially saying from the inside of both closed frontier companies that this is happening. Yes. And so I think it is a complete hornet's nest that they have kind of like kicked to the ground because on the one hand, have rational people who wanna build a business for which you need enormous amounts of capital that is only available in the public markets. But the process of doing that requires you to underwrite risk, absorb liability, disclose that properly, and then allow people to know what they're buying. But what we have is this weird version now where it's almost like a... An example of, like, Philip Morris where it's like, we know that the cigarettes are bad for you. We know that the cigarettes will kill you, and we're gonna say it, but we're not gonna disclose it. And we're gonna take the company public and allow you to own the stock, and then we're gonna just figure it all out later. This is not a tenable position, Francois. They do, as Sack said, have to choose. David Sacks (00:14:59): Let me get Freiburg involved in here. This is a very good analogy you bring up. Nick, find the video where the executives at the tobacco companies are asked at a congressional hearing if they believe that nicotine is addictive. And one after the other, Chamath, they say they do not think it's addictive. Here... And that happened, like, ten or twenty years after they had the research and hit it. Chamath Palihapitiya (00:15:24): This is the movie, David Sacks (00:15:25): the insider. You're a 100% correct. You now have legions of people inside of OpenAI and Anthropic, Freeberg, agreeing that we're all going to die in 2030. They're not just saying everything's gonna be hacked anymore. They're saying ten percent chance of everybody dying and then other people are saying, yes. That's probably pretty accurate. Freeberg, I give you the floor. David Friedberg (00:15:47): I'll give you some other times when we've heard similar things. Al Gore published a movie called Inconvenient Truth and he used these IPCC forecasts that as of now have been disproven and many of the assumptions in those forecasts were not correct. A guy named Fauci, you guys may remember him, he told us all that COVID will kill us all and as a result we need to lock down the entire world. So everyone was locked in their houses, businesses were shut down, the government began spending wildly to keep people economically active which had the adverse effect of driving inflation through the roof and we now have a spiraling debt and spending problem in this country. There was an era when 3 Mile Island had an accident and we hysterically said we're gonna destroy the entire country if we keep doing nuclear development. Meanwhile, other countries raced ahead. The cost to produce a gigawatt of nuclear power in The US today is, like, $15,000,000,000. The cost in France is 4, and the cost in China is one. I think we're in this hysteria phase of AI doomerism. I I think once you're in this phase, it's very hard to get out because it basically becomes the default social system. Everyone says we are facing an existential threat. We are all going to die if we don't do something about it, if we don't stop it, and the absence of proof that we're not gonna die and that we have absolute security lets the doomsayers get away with the compounding effect of getting all of the social systems and social networks activated, which is where we're at right now. The majority of Americans, that's why data centers poll at negative 80, and people believe very deeply that we're gonna die, and I think that there's, like, a deep unconscious rooting to all this. Humans are primates living in a cave, and we're deeply scared of what we don't know, what we don't see, and where we haven't been. And where we're going is a place we've never been, and it's scary. David Friedberg (00:17:40): And in this era when people thought that the world was flat and you would fall off the edge of the world, it was scary to sail west because you would go off the edge of the world and you would never make it back and then Columbus did it and hid some land and lo and behold, the new world was discovered. And I think that we've had many moments like this in human history where we're kind of like a pioneering species, but pioneering is not everyone's pioneering. The majority, the vast majority of people convince each other and convince everyone that we have something deeply threatening us and we're always facing existential threat. It is rooted in our beings as a species. It is deeply, deeply rooted. It's what's created survival instincts for us over generations and millennia. But it takes just, you know, a little bit of pushing and someone gets to the pioneer and the new world is discovered, but it's because you haven't been there, it's easy to say there's dragons, you'll fall off the end of the world, we're all gonna die, climate change will destroy us all, and on and on and on. COVID will wipe us all out. And I think we're kind of in that social panic phase right now and we're told we have to listen to the experts once again. And in this case, the experts is a six week employed individual who has not had a real job for very long and worked at an NGO whose literal job was to scare the shit out of people to stop doing AI development. And this individual went in and did six weeks of work, came out, and suddenly the whole world says, this is an expert. Bernie Sanders says this guy's the expert that once again we all have to listen to. Now I think it's important to note one thing, we could sit here and argue that we should follow the precautionary principle, this idea that if something is existential to us, we should take precaution and we should take our time and we should slow it down. But the difference here is that in order for recursive self improvement, which is AI that continuously improves itself and its capacity, reaches that moment where that happens, you really just need an adequate amount of power, a set of chips and a connection to the internet. You don't need to be approved by the US government or anyone else because you could do that anywhere on planet Earth. David Friedberg (00:19:51): And as we'll hear about at the summit next week, there are technologies now that are reducing the cost of power per token of output by 10,000 x and there's enough compute out there that's publicly available that's floating around. Someone is going to stand up a data center or a set of computers, doesn't even need to be in a data center, and they are going to develop a system that's gonna recursively self improve and it is going to happen. So if The US wants to kind of stop all quote development and make it illegal for people to use computers to effectively write speech, which is what software is, is writing the speech, we can go ahead and do that and then someone else will have this capacity and we will be the tribe in the Amazon that has never seen civilization because civilization will evolve all around us and somewhere in the world that has this technology, it will evolve, it will have a capacity to advance and The US will be left behind. So you can have the doomerism precautionary principle, but the reality is in the world today, we don't have the ability to control. And at the end of the day, I do believe that the fundamental motivation is a system of control because think about this, this guy is going on all these non tech podcasts telling people they're gonna die and he's saying one thing at the end of the day and so is Bernie and so are others, give power to x to control the development of AI. Give power to someone to control the development of AI. Someone has to be given that power, someone is being given that control and all of them will have a different answer on who it is, some regulatory body, the senators, some new agency, but they are centralizing control and power to some individual or set of individuals. Jason Calacanis (00:21:31): Let me build on that point. Let's imagine we went through that whole COVID period with AI. You know, AI happened a little bit after the whole COVID thing, but let's assume that AI had happened before and furthermore we had a federal department of AI. Imagine that whole trust and safety regime that happened during COVID where social media was basically censored in cooperation with the federal government. The White House told, you know, was then Twitter and Facebook that these accounts are dangerous, disinformation is dangerous. And people who had alternative or distant viewpoints on the origin of COVID or the efficacy of the vaccines, they were suppressed. Imagine if that had happened during AI, right? You'd be asking your personal AI model, hey, should I get the vaccine? What are the risks versus benefits? Do you think it would tell you the truth? No, it would basically give you the official perspective and the government will have pressured through the federal Department of AI, the FDAI would have set standards for these companies saying you can't allow disinformation through your models, right? That's one of the harms that we want to prevent. And so, you know, think about how much more totalitarian that whole episode would have been if, you know, again, instead of turning to social media or the web for our answers, we were getting them from our personal AI. And that personal AI was being influenced through the government to give us basically official answers. I mean, you can see how dystopian it's gonna be. And that is where an FDA AI will take us. David Friedberg (00:23:05): And that is also the problem with open source because open source doesn't have the individuals employed because remember, open source is a community developed effort. So community members contribute code and develop something. It might be a single company, but technically open source can be forked and developed and pursued down different paths. This is what happened with Android. There are lots of different forks of it and so on. But with open source, there is no infrastructure, corporate infrastructure to go and do the regulatory submissions and do the sort of review that's being proposed with AI. That is the biggest thing to take note of because open source is what drops the cost of AI by 50 x and makes it available to everyone so everyone can benefit from AI and no one gets rich. We all get rich with open source. I don't own any shares in OpenAI or Anthropic in full disclosure. I don't care if either one of them win. I use both those products. I think they're both fantastic. Good for those companies, good for those leaders. I also use open source. And I think open source is the game changer because it does give everyone the ability to get wealthy and progress and make more income and have more freedom to operate in the world with AI. I'm a big advocate for for open source, but I do worry that this system of control doing quote regulation, doing reviews, slowing it down, that means someone gets to decide when it gets to speed up again. That means someone is controlling the the gas pedal, which means someone gets to say open source is not submitting to the regulatory process. Therefore, we will ban open source. And as soon as open source is banned, you have now created a monopoly that is in partnership with the federal government and you now have a centralized system of global control that is realized from this sort of an approach. And I'm not saying that AI shouldn't be tested and that we shouldn't confirm that AI is safe and that we shouldn't build safety systems and that we shouldn't be responsive and thoughtful about where things are going and there's a lot of ways to do that, a lot of ways to do that and we should do them all. David Friedberg (00:25:09): But to create systems of control and centralize them and get rid of open source is where this gets to and that is not a world any of us should want to live in. David Sacks (00:25:18): Well said. Well said. I, you know, I... I just wanna... Jason Calacanis (00:25:21): That is where it's headed. I mean, look, this is a tumor SIOP and the ultimate target is open source. That's what it all comes down to because that is what an FDAI will ultimately ban. They won't call it a ban. They'll just say, look, we have to apply the same standards to open and close models. What are those standards? Dario has already testified before the Senate. He says that models are dangerous if you can't centrally monitor and control them and roll them back. That is technologically not feasible with an open model because once the weights are published to the public domain, they're out there. They can't be rolled back. And so we're gonna have to prevent those weights from being published or used or hosted. That'll be the way that they deal with this. And so look, that ultimately is the target. And you can see that there's an alliance forming, right? You have this doomer community who are kind of these like highly ideological, the sort of EA rationalist group. They favor centralized status solutions. Then you got politicians like Bernie Sanders who like the fear because, again, it grants them more power. So it's more power for the government. And then, you know, you got groups like Open frankly seems to be running an anthropic slipstream right now from a red capture standpoint. I don't think they're as doomer as anthropic, but they can see the benefit if the federal government effectively creates a moat that, you know, there's huge economic benefits to essentially creating a duopoly situation. So some of these players are gonna reap economic benefits, some of them are gonna reap power benefits, some of them are just, you know, latent totalitarians and they like the idea of socially engineering society, so they're on board with this. And that's kind of what's happening right here. And the whole idea is to panic the public to stampede us into this FDAI. David Sacks (00:27:02): I think what we're seeing here is either this is a conspiracy theory that is being debunked in real time, Sax. Like, we went through COVID. We've had other conspiracy theories that have come true. Twitter was being influenced by the FBI, turned out to be true. Twitter files, all that good stuff. Now you have a group of people in the public who are on the alert for conspiracy theories. So we have to ask ourselves, is this actually, Chamath, a conspiracy theory that's being debunked in real time by people like us and the broader public who's starting to say, like, is this real or not? Are these guys performing it or not? Or we actually have to ask the question, do these people believe what they're saying? And it's one of these three scenarios, I think. They either believe what they're saying and they're right. Right? So they believe it, they've seen something that we can't see because they're in the frontier labs and this could end us. The second scenario is they believe what they're saying and they're wrong and they have some level of psychosis. That's my leading theory. I think these people believe what they're saying and have psychosis. Or to your point, Saxx, there are some and this is scenario three. They're involved in some coordinated psyops with the goal of banning open source, getting regulated, pulling up the ladder behind them. And then you have to ask, is Jacob part of this SACS, or is he just like a useful idiot in all this? So they're identifying who are the people who have the psychosis and let's make... Let them speak for the company. Jason Calacanis (00:28:25): But No. Look, it doesn't it doesn't all have to be a conspiracy. So in other words, I I think it's very clear based on who amplified this post and when they did it that there was an organized PR campaign here. Right? This wasn't just a random resignation. David Sacks (00:28:37): Yes. And they Well, no. They The sit... The stats Jason Calacanis (00:28:40): We know. Yeah. David Sacks (00:28:41): The facts are aligned towards that. Yes. Jason Calacanis (00:28:43): We know he pre briefed the Wall Street Journal, and I think we can also say that these major doomer groups by amplifying his tweet within ten to fifteen minutes of him posting it on an account that had no tweets and no followers, they were alerted to this and probably participated, If not in the creation of the tweet storm, certainly in the amplification of it. So we know all those things. But do I think that Bernie Sanders is in on it? No. I think probably what happens is someone in these groups is already working with his staff or they have a conduit. They have a relationship. And they get it to him very quickly because it serves his agenda. So what I'm saying is there's a lot of, like, overlapping agendas here where there's some people who have an economic interest, there's some people who a power interest, and there's gonna be a division of the spoils. In their view of the world, AI is gonna be very centralized. We're gonna have a duopoly. The duopoly reaps the economic benefits and they give big political donations and they'll do the dirty work of suppressing speech because, again, on that side of the ledger, you can circumvent the First Amendment. And then on the government side of the ledger, you'll have those people who exercise control over our lives through the whole FDAI. So you kinda get this, like, division of labor in our system between aligned groups. Chamath Palihapitiya (00:29:54): Okay. Jason Calacanis (00:29:54): Now But look. I don't, you know, I don't think we have to get into the conspiracy. I think we should just ask, like, what is these people's track record of being correct? I think it is worth asking that. Chamath Palihapitiya (00:30:02): Well Jason Calacanis (00:30:03): Again they These are the same people. Let's just go through it. Let's just go through their track record. Okay? These are the same people who said GPT two was too dangerous to release. Okay. O for one. These are the same people who said thinking models were too dangerous to release. Remember, you know, what did Ilya see? He saw Yes. You know, the first reasoning model. That was too dangerous to Chamath Palihapitiya (00:30:23): look for. Jason Calacanis (00:30:23): Fable. Ofer two. Yeah. Okay? Said Totally right, Sykes. David Friedberg (00:30:27): You're totally right. David Sacks (00:30:27): Fable was the cyber attacks. Jason Calacanis (00:30:30): They said that this would cause cyber attacks that would bring down the whole banking system. Has not happened yet. There are cyber risks to be sure, but the best way of dealing with those cyber risks is by using AI swarms for cyber Cyber. Defense as well as cyber Yes. Exactly. Look, the only way to solve AI cyber attacks is with AI powered cyber defense, we all know that. Then you look at the job loss claims where Dario himself said that by now we'd be at, I don't David Sacks (00:30:55): know Half of all Half of all job to be gone. Jason Calacanis (00:30:59): It's the end David Sacks (00:31:00): of this year into next year. Yeah. Jason Calacanis (00:31:02): Yeah. And overall unemployment levels of 10 to 15%. Yeah. Hasn't happened. There's no evidence of that. Quite the contrary, it's all been job gains. Economy is doing well. So, again, like, what are we on now? O for four? So, you know, again, these, like, doomers just move from claim to claim, and as the last one gets refuted, they move on to the next one. And, again, my point is what what has this guy told us that is new here? Chamath Palihapitiya (00:31:25): We're still struggling to get autocomplete for Python. You you can't book a hotel room. That's actually the hardest one. You can't a hotel room David Sacks (00:31:34): using AI. It does not work yet. Chamath Palihapitiya (00:31:36): You know, autocomplete on Python is pretty good. But it's gonna kill Jason Calacanis (00:31:39): us all. Chamath Palihapitiya (00:31:39): Still not, but it's gonna kill us all. David Sacks (00:31:41): Oh my gosh. Might get us a free Chamath Palihapitiya (00:31:44): guys dare to book me in a non penthouse suite at the Bradasson. David Sacks (00:31:49): Are you sweet shaming me again? You know what Chamath Palihapitiya (00:31:52): I mean? This is a joke. No. It's a joke. It's a joke. David Friedberg (00:31:55): If you think back on the course of human history and you think about the moments where systems were set up that created power structures that didn't exist before, they were all predicated on the simple notion that there's an existential threat. You will all die. A deity, a god, some powerful system will come in and destroy Chamath Palihapitiya (00:32:14): Some weapon. Right. David Friedberg (00:32:16): And because I can protect you, you must follow me. You must do what I say. And it is the common system of human power and control structure to tell a narrative of existential threat and leverage that narrative into your solution being the path to protection and safety. And that is what sells votes, but it is also what created all these early structures where early religious institutions ran all the countries, told all the people what to do, were the power and command centers of the world, and in many parts of the world still are. And when you talk about, oh, well, if you don't listen to me, God will damn you, God will shame you, God will destroy you, or some deity will come down and get you. This is the same psychological concept, which is that there is a story being told that you will all die. There's a ten percent chance you will all die standing at the pulpit banging hard. And if you don't let me control it, if you don't give me the power and the authority to control it, you will all die. Give me that power. David Sacks (00:33:14): The only other time I can think of this happening would be nuclear weapons, which we did get ahead of. But putting that aside, a cyber hack is not gonna destroy society. So how do you get to 7,000,000,000 people or a billion people are gonna die? Really, the only known scenario here is, I guess, it creates a bioweapon and kills everyone or Well, let's play a game. Terminator two. Let's play your game. Okay. David Friedberg (00:33:40): So my game... Nick, do you have any music? David Sacks (00:33:42): Oh, it's like a N2 Matty, how we all die. David Friedberg (00:33:46): Okay, guys. This game is called how do we all die. In this game, will go around and Steel Man the concept that there's a 10% chance that we all die from AI. What is your most likely path to human extinction, J Cal, from AI? Go ahead. David Sacks (00:34:00): Go first. I'll take human extinction for eight hundred. You always wanted to be the the host of Jeopardy. That would be a great moment for all of us. I'm gonna go with Skynet and Cyberdyne Systems. This was the... If if people forget, but at the end of Terminator two, they got the ARM and one of the chipsets, and then Cyberdyne Systems built for NORAD, which controls weapons and decisions to fire off nuclear bombs. And there was Miles Dyson. He was the lead researcher. He's the Jacob. He's the Dario, Anthropic. And that engineer studied the parts that came back through time. In this case, this would be studying the LLM, and then he reverse engineered it, and then he empowered NORAD to be... To build a defense system powered by AI. And when it became sentient, it then tricked the Russians and started the nuclear holocaust. That's the number one way we all die is that they somehow use Claude inside the military to do autonomous weapons. It's the only way that this actually happens in my mind. David Friedberg (00:35:09): Chamath, do you have a how do we all die theory? How do we all die for 800? Chamath Palihapitiya (00:35:13): The best example I could get is that there are some internet connected bioreactors with internet connected robots. Okay. And access to all of the precursor materials and that the AI hacks the robots to take the precursors and use the bioreactor that it then controls, again, over the Internet to create some kind of virulent airborne mechanism that spreads rapidly and violently all around the world. So it has to have an enormously long half life, gets into the jet stream, can kind of go all over the world, and that when we inhale it, we die. That is the... Now, again, that would need all of these other things. David Sacks (00:36:11): So contagion by robots and a sentient AI. Chamath Palihapitiya (00:36:14): Again, you'd also have to have bioreactors and and precursors which is Yes. It's a couple of step. David Sacks (00:36:19): What do you got, Sax? Jason Calacanis (00:36:21): Well, look, the problem with these types... First of all, I think it's kind of a dumb thought experiment to make arguments that you don't believe in. But look, the the problem with the like the cyber example or the bio example, it's like, yeah, is AI gonna allow for misuse in new kinds of ways? Will there be new AI powered cyber attacks? Could there be new viruses created using AI to create novel sequences? Yes, those are risks, but at the same time you can use the same technology to create antidotes and prevention and cures and all that kind of thing. And so it's like a lot of things where, yeah, there are tools that can be used by bad actors. But there are a lot more good actors than bad actors out there and it's illegal to use them for bad actions. And, you know, it was possible to break into systems and hack before AI and a lot of people who could do it didn't do it because they didn't want to go to jail. And so again, with the combination of the tools being used for good and then the legal penalties for doing bad, these are I think things that we can control. David Friedberg (00:37:22): Part of the argument that I wanted to make in going through how does everyone die is it is very hard to have a clean scenario given the human in the loop dynamic and the air gap dynamic. Explain both of those, please. Chamath Palihapitiya (00:37:35): Well, hold on. What's your best answer, Freeberg? What's your best answer? What's the best thing you David Friedberg (00:37:39): can Chamath Palihapitiya (00:37:39): come up How David Friedberg (00:37:39): do we all die? I think shutting down financial networks, but then there's hard backups. Like, there's there's a solve for this because a lot of the financial institutions already have nuclear response scenarios where they they make physical hard copies of everyone's assets and records. They sit in different locations. There's a lot of systems of redundancy that are air gapped, that are designed to not be connected and not hackable, and that of a human in the loop process where there's an actual human process involved. So I think a lot of our critical systems are importantly set up in such a way that they have human built redundancy for the notion of cyber defense, for the notion of hacking effects, nuclear, all these sorts of things happening. Because my biggest thing is, like, if everyone lost all of their digital assets, maybe that's a world that falls into chaos and people start to attack each other and whatnot. But I think it's very important to take note, as I've thought about this a lot, there's so much that's human in the loop that is also what makes AI so hard today to be successful from a productivity perspective. Like, we all experience it. AI can do these amazing things. But if you need a human to do something as part of the process, AI doesn't really do that much for you. Let's say you wanna get a toiletry kit brought up to your room at a hotel. You tell your assistant on your phone, get me a toiletry kit brought up, and the AI figures out how to connect to the front desk and call the guy and tell him, and it's all digital. It's all automated. AI does all these amazing things that it couldn't do a few years ago, but you still need the guy to bring the toiletry kit up from downstairs. David Sacks (00:39:08): Did you get the intimacy kit or not? Well, this is David Friedberg (00:39:10): the point. This is this is the hard... This is the longest pole in the tent. It's like getting the guy to actually come upstairs and bring you the freaking toiletry kit, and there's a lot of examples. Chamath Palihapitiya (00:39:18): Autocomplete doesn't work yet, god. I know. Mean, there's David Sacks (00:39:21): so many I need to explain two terms to the audience. Air gap means it's not connected to the Internet, therefore, AI can't get it. And the human in the loop, the example would be a two key system that you see in every movie when you're trying to launch a nuclear missile two The human... The human service have to do something. The keys and and turn it at the same time based on reality. Jason Calacanis (00:39:39): Guys are actually not confronting the core argument that I've heard him make. I mean, so if we wanna really steel man it, I mean Yeah. The core argument that he's making is about RSI. It's about Yeah. Recursive self improvement. And his argument is that the capabilities are improving at such a rate that very soon going to be able to fully automate an AI researcher. So in other words, we're going to have an AI that does the job of an AI researcher. And so the AI can create its own training run for the next model. And then when that model gets created, it will then train the next model and so forth and so on. There'll be no human in the loop and it's just off to the races. That's basically the argument. And I think the counterargument that you guys are making by saying, look, we haven't even got autocomplete right, is we are nowhere near removing the human from the loop of AI development. David Friedberg (00:40:29): Or even AI applications is my point, sir. Right. David Sacks (00:40:31): Yeah. We can't get mundane tasks done yet. Therefore, how are we gonna have a a task that kills all of humanity? Even if you put it at kill one person, can you David Friedberg (00:40:40): get it to kill one person? Right. That's also our insurance and our security against AI taking over the world. Because even if you wanna make a meeting... Decision at your company, you still need a meeting of the decision makers to make a decision. The AI can do all the analysis, but you still need to get the humans. They gotta wake up, take a drink their coffee, come to the office, sit down in a room together, and make a decision. So you got that sixteen hour window between decisions that's happening. Yeah. And so even if the AI is infinitely more intelligent than any human, humans are still running their day to day processes in a human timescale, and that's what also protects them. The part David Sacks (00:41:14): I don't understand, Sax, is Yeah. If these geniuses are building such amazing tools, did they ever think that when they set it on its, you know, loop and they actually build AI researchers, which I believe they will, and and they they certainly have done some approximation of that to improve large language models. They're having AI make them better. That's why they're getting released quicker. That's why they're building... They're solving hard math problems like we should get to in the next story. You ever think of putting in there, hit space bar to continue or allow the human in the loop to say, yes, you may continue your run? Like, it's pretty obvious that if you try to let it right now, if you try to let Claude or OpenAI use your browser, it's like, can I open your Gmail? Can I submit the form? And then it's like, I don't wanna book the ticket for you, but I'll select the flight for you, then you have to book. You you can build these things directly into the software. We're acting as if we're not building the software and we have no control. It's a false premise. Jason Calacanis (00:42:15): Yeah. So, I mean, look, I think even, you know, someone who's pretty ensconced in the doomer community like Jack Clark, who's one of the Anthropic cofounders, and I think he's running their foundation, who's, like, pretty hawkish on on these questions, meaning pro doomer, he distinguishes between what he calls prosaic RSI, prosaic recursive self improvement, and then RSI maximalism. And the prosaic kind is when the AI researchers are using AI to do part of their tasks, like I don't know, writing 80% of their code, so it speeds them up, okay? And we can all see that the prosaic recursion is happening. RSI maximalism is more about what you're saying where there's no human in the loop anymore. That the AI devises its own training run completely and pushes the button on doing it and then has the next run and the next run and the next run and it just... It's off to the races. Right? That's the takeoff. There are so many ways of us preventing that and I don't know why any lab would wanna do that. I don't know why Anthropica wanna do that. I know why OpenAI would wanna do that. I don't even necessarily think that Chinese companies would wanna do that. So, you know, as we get closer to that point where Chamath Palihapitiya (00:43:26): Could you unplug it? David Sacks (00:43:28): Well, no. I mean, they did. They do experiments like this. The whole thing is Chamath Palihapitiya (00:43:32): self part. Part. Carpin just comes and unplugs Yeah. David Sacks (00:43:37): No. But they literally... We we went through this with Dwarf Keshe's post last week, which was OpenAI set up this recursive, like, here's a bunch of goals, get better at it, work with each other, and they just watched it work. Like, okay, just watch it work. And maybe if there was a liability that Anthropic and OpenAI are responsible and the researchers who set these models into recursiveness sacks, those researchers themselves are responsible for what happens and the company's responsible for what happens. And along the way, they're gonna get speeding tickets or shut down. Jason Calacanis (00:44:09): Agents working together as a swarm is so far removed from AI being able to do its own training run. I mean, these are just two totally different things. And look, it's certainly something we should keep an eye on. But again, he's going from this idea of we now have AI as a tool to make AI researchers more productive to we're gonna get to RSI maximalism and then from there everyone's gonna die. And there are so many intermediate steps where you have to show how we would get there. Like what Bill Gurley said is, okay, wait. Let's slow down this argument, and let's just talk about, like, all the intermediate steps between those things and why they would happen, and then the interventions we could take if we ever got near that point to stop them from happening, and then the argument starts to fall apart. David Sacks (00:44:54): Yeah. Because there's 50 waypoints along the way to Chamot's, you know, computer generated bioweapon being released into wet markets everywhere by robots. Chamath Palihapitiya (00:45:03): Again, my example is so pathetic because as Friedrich said, there's just so many steps between here and there that it's just so implausible. Again Jason Calacanis (00:45:14): And even if you got to there, you haven't even established how everyone would die. Chamath Palihapitiya (00:45:18): Yeah. And in a world where there's any other kind of model that's out there, the fact that it, as you said Sax, couldn't actually create a vaccine at the same time. David Friedberg (00:45:26): Yeah. And someone else is gonna be doing it. And if you try and create one system of control for some of it, the recursive self improvement scenario will play out somewhere on planet Earth and when that happens, when that person or that organization or that country now has that capacity, they have now a huge technological advantage and then it becomes very hard to catch up and we've seen this time and time again with technological races. This is a moment that The United States would be deeply, deeply mistaken to kind of write off. And let me just say one more thing about open source that I didn't say earlier. I want people at home to understand what open source really means. With open source, you don't need a data center. You don't need a third party billionaire getting richer. All of these kind of retorts about why AI needs to be stopped, it's for data centers, it's for rich people getting richer. If you get open source AI, you can install it on your computer at home or on your phone and you can run it on your phone for free and you now have an open source AI agent model system that can do all sorts of things for you. It can book your travel. It can do work for you. It can make your life easier. It can do all these amazing things in terms of productivity. Open source AI is critical for everyone to benefit from this technology and keep it from being centralized and controlled by a handful of companies and individuals and a small set of governing officials. Open source needs to thrive and if you give power and control systems over to governing people, open source will die and you will end up with more power and more of David Sacks (00:47:07): an oligopoly than you have ever imagined. Who's positioned here? What impact does this have? I'm being obviously a little bit playful here, but how does this impact the anthropic IPO, which was one of your original points at your mouth? 88% chance they're gonna go public right now according to Chamath Palihapitiya (00:47:21): I don't David Sacks (00:47:21): know. Polymarket. So let's pull up that chart for a second here. Chamath Palihapitiya (00:47:24): When you are in a quiet filing period, just to give you the the technical understanding, there is a... An important back and forth that happens between you, the filing company, and the SEC. Now what is the SEC trying to do? They are pressure testing how you've written, what your best understanding is of your business. And the reason they do that is that when the s one flips public, that is meant to be this anchoring document that is supposed to be an extremely accurate then current snapshot of all the opportunities, but also all the risks. And so you now are in this very awkward position. You know, Saxe's tweet is actually really important. It's what are we all to believe? And are we to believe that there is something that's extremely dangerous that's hiding inside this company because this person that quit said it and then it was amplified by a bunch of people that are currently then there? If it's true, now you have to go back and actually say, these risks properly disclosed? And if so, what should the investors do in reaction to it? And I'll tell you what they'll do. They'll demand an enormous discount. And the reason they'll ask for an enormous discount is the other part of what Sachs and Friedberg said, which is it creates massive long tail product liability risk because you're effectively evading a known major risk. Then there's the other path, which is you have to completely disavow this person. Now the reason that they can do that is if they actually believe that this is a little bit bull and it's a SIOP. So that allows the IPO to go more smoothly, But then the other part of it is then you'll have a plurality of employees inside of Anthropic revolt because they, unless they're lying, they actually believe that this is a huge risk and if you disavow it, they're gonna feel enormous tension. So I think that anthropic leadership is caught in an extremely difficult situation. The SEC is caught in an even more difficult situation, which is how do I deal with these disclosures now? What does it... Chamath Palihapitiya (00:49:33): No no company is trying to go public and raise money, a very capitalist scenario, by also talking about how they're trying to destroy humanity. Nobody has ever done that. So there is no legal precedent for this. David Sacks (00:49:45): There is a risk factor section, Sacks. Chamath Palihapitiya (00:49:48): Sacks said risk factors are extremely benign. These are superficial risks where you talk about if this happens, then that could happen. If, you know, demand goes away, that could happen. Speaker 5 (00:49:58): Let me Chamath Palihapitiya (00:49:58): finish my question. Risks... Okay. Just explain. The typical risks, Jason, that they would have had would have said Competition. NVIDIA may not give us the chips. There may be other models that come David Sacks (00:50:08): around the equation. Chamath Palihapitiya (00:50:10): This is not a risk that anybody actually writes in there as a 10% chance because a bunch of employees now have David Sacks (00:50:16): sent Let me ask Sax this. Sax, with all these employees coming out saying all this kind of stuff, they represent the company. They're resigning on behalf of the company. Do you think the s one is being amended right now to include this chaotic... These chaotic tweets? Jason Calacanis (00:50:29): And have to. David Sacks (00:50:30): Yeah. I I think so too. Jason Calacanis (00:50:32): Because here's the thing. The key tweet actually from a legal standpoint wasn't Jacob Coxen's tweet of resignation. It was Evan Hubinger's tweet Chamath Palihapitiya (00:50:43): Endorsement. Jason Calacanis (00:50:43): Endorsement, cosigning. Chamath Palihapitiya (00:50:45): Yes. That's right. Jason Calacanis (00:50:46): Because this guy is still a senior executive or senior alignment executive at the company. He's managing one of these safety teams, And he is cosigning and endorsing what Coxen is saying and then embellishing it by then putting this greater than 10% chance number on it, which just makes the thing go super viral. David Sacks (00:51:05): Let me ask you a question for you. Jason Calacanis (00:51:06): So now... Hold on. So it crosses over. If it was just Coxen, you could just say, oh, this is just some disgruntled employee. If Anthropic was a normal company, what would a normal company do in that situation? They would say, look. This guy just joined a short time ago. He was barely here long enough to find the bathroom. Okay? He probably joined the company knowing he was gonna resign and make himself into this David Sacks (00:51:29): AI vow him. Jason Calacanis (00:51:30): Yeah. He had an intention to turn himself into an AI safety celebrity. He's certainly availing every opportunity to go on every talk show right now, except ours, to basically promote himself. So this guy's a self promoter. He did not actually reveal anything damaging to our company. He's calling himself or the media's calling him a whistleblower. But frankly, all he's got is vibes, and it's hyperbolic, and it's ridiculous, and we're moving forward. Okay? That's what a normal company would say. But they won't say that because fundamentally, they agree with him, and their employees are saying they agree with him, and he's amplifying their message. And frankly, whether they plan this or not, they are happy that he's doing this. Why? Because they like the political outcome that he is steering the country towards. Right? They want an FDA eye. They actually like what Bernie Sanders is doing. They like the fact that 30 Democrat politicians, quote, tweeted to this guy. This is part of their regulatory strategy. So to go back to what Chamas said, there are now legitimate questions here of, did they violate their quiet period? Maybe Dario didn't. Dario hasn't said anything. He's been very quiet. But we know this Hubergenrei, did he violate the quiet period? Is he a sufficiently important executive? And again, this... Is this all part of their strategy? David Sacks (00:52:49): Well, let me just talk from very basic principles here. Everybody who joins a company signs a nondisclosure. They sign a nondispairagement. They have a corporate communication policy. Especially, they have the legal department talk to every employee and explicitly tell them, do not talk because we're in the quiet period. We're leading up to an IPO. Everybody keep your mouth shut and do not talk about what's going on here. That is job number one. What is going on with the management of Anthropic that they're allowing people to cosign this, retweet it? They should do what Apple and Steve Jobs did or Tim Cook did. Nobody in the company speaks for Apple unless it's Tim Cook and unless it comes from the corporate communication department. Who's David Friedberg (00:53:35): running Toms? Chamath Palihapitiya (00:53:36): We don't know that they haven't said that. All we know is that there is a pile on that's happened. The brush fire was initiated by a disgruntled ex employee who was kind of like floating around and was there, as Sacks said, barely long enough to find the bathroom. But the problem was then a bunch of insiders piled on. And now they have this issue which is, is it properly disclosed? And then beyond that, how will people view that disclosure? There is no way that you can now have a disclosure like this and have it pass muster. Meaning, you have people at the company saying there's a chance of existential risk and civilizational extinction. Downstream of that is that there is risk to individuals and individual lives. Downstream of that are going to be cases where something bad happens because the AI is said to do a or b or he was trying to give love advice. The person gets rejected. The person, you know, hurts themselves, self harms, whatever. There's gonna be all of these issues. Okay? The long tail of issues are going to be if social media is a guide, this will be as bad or worse. Except in all of these cases, nobody at those companies actually thought they were doing something bad. We thought when we all worked there that this was legitimately good. There were these spurious things that brought that into question. Some of us talked about that at that point, but this was ten, fifteen years into the journey, not when you were making it. Now in the middle of making it, you're like, woah, wait a minute. This is gonna kill a bunch of people. And then so what do you expect people to do if something bad happens to them or their loved ones? They're gonna go back to you. It doesn't matter what the disclosure says, and they're gonna say, excuse me, this. And what do you think a jury's gonna do in a jury trial? Chamath Palihapitiya (00:55:26): What do you think grand juries will do in the reaction? What do you think state AGs will do when they're trying to build their political bona fides? I think that this is an enormous problem for Anthropic. Jason Calacanis (00:55:36): Yeah. Let me let me actually peel peel the onion on this one more layer, which is you not only have employees of Anthropic possibly violating the quiet period by stepping out and cosigning this, You also have the fact that this whole resignation tweet storm was amplified by these groups who were funded by Jan Talen and Dustin Moskowitz who co led the series a of Anthropic along with Sam Banquemfried. It was an EA funded round, which is a really interesting detail in Anthropic's history that Dario went to the EA mega donors for funding at the very beginning and that's part of why they have this culture. But think about their financial interest. They're on the cusp of making many billions of dollars. Chamath Palihapitiya (00:56:20): Hundreds of billions. Jason Calacanis (00:56:22): I mean, the series a will turn out to be one of the great venture investments of all time. And the groups they funded, Encode AI, the AI Policy Network, the AI Futures Project, these groups are funded by Series A investors in Anthropics. So this is getting like really twisted, I think. David Sacks (00:56:46): Let me just say, this makes no sense to me because we were sitting here less than a month ago, three weeks ago, we had Gavin on the podcast. And I don't know exactly when their quiet period started, but Dario thanked Gavin for a thoughtful exchange, and he went and explained in detail all of their concerns and, you know, countered this claim that Gavin had that he heard from insiders that people inside Anthropic believed they were the last company standing, which is to say they would take all of capitalism and coalesce it into one company with their superintelligence and be able to be every company on the planet. Freiburg, at some point, Dario believed he should comment on this. So where's the Jason Calacanis (00:57:34): comments department? Anthropic did release a statement, but it's David Sacks (00:57:37): basically saying did, but Dario did himself. The the CEO did. Jason Calacanis (00:57:40): The statement they put out is kind of this mealy mouthed, like, vague post about how they're a responsible actor or whatever. And again, it's basically more of the same from them, which is they have this fundamental tension. They're a Frontier AI company that believes that frontier AI is inherently dangerous. Okay? So, you know, where that obviously leads to is Bernie Sanders, is shut it all down or at least stop it, right? But they don't want to do that for their own motivations, right? So what they claim is we're uniquely situated to protect humanity. It's the savior complex. But the rest of us aren't buying that, and we're not gonna give them a monopoly because we think they're so virtuous. So their way of resolving the tension is not acceptable to the rest of us, And that's the problem they have. David Sacks (00:58:24): Here's their chief brand and communications officer, Sasha, responding to the clip from all in. Dario has never said this complete and utter nonsense, and that was on August 14 after the show. And she's obviously... Dario and her have not said anything right now, so maybe they weren't in the period on October 15 than they are now. Alright. Listen. In other news in AI, great discussion, everybody. OpenAI says it solved a 200 year old math problem, but claims now are that somebody may have front run an actual scientist's work that was being done on OpenAI. So the Navier Strokes equation written in the 1,800 describes how fluids move, every aircraft pipe, and weather model on earth is built on them, and they apparently... Give us the history of this here, Friedberg. A lot of people have been working... David Friedberg (00:59:12): Look. I'm not the guy. These are methods for modeling fluid dynamics, partial differential equations. These are mathematical approximations of continuous things in physical world and OpenAI's solution that they published, they said that they used a reported 130,000,000,000 to do the work between 10,000 agents that were spun up to work with one another and I just did the math on this, like the human equivalent hours is kind of the real estimate of what this work was that was done by these agents because it's not like the AI, and I think this is so important for people to understand, it's not like the AI had some stroke of genius, some magical insight that no human brain could comprehend. What happened was the AI just did a bunch of brute force work to come up with this answer and the work was done across many many computers, 10,000 agents just means 10,000 applications running on a computer, talking back and forth to one another, sharing information, sharing analysis and the equivalent if you were to think about human work years is somewhere between fifty and five hundred thousand years of human work with humans typing at 40 words a minute, you know, having mathematical problems, solving them with calculators, doing this sort of stuff back and forth, and you could probably reduce that down by call it an order of magnitude, but it's still in the order of tens of thousands of years of human knowledge labor. I And think that that's really what this indicates about AI. AI is a tool of leverage for humans. AI is not some magical genius super god that sits above us that understands things we don't understand. Every piece of the OpenAI message set that went back and forth between these agents is documented, can be read by people, can be understood by people, and we can see the work that the agents did over the equivalent of tens of thousands of human years of time to get to the solution that it got to. And so for me, the solution that was described here is more of an insight into what AI is rather than what AI isn't. David Friedberg (01:01:25): AI isn't some mathematical god. AI is an engine that gives humans extraordinary leverage. And when you think about the application of this particular set of problems and what else we might be able to do with things that are similar, is instead of spending years trying to design a new aircraft wing, a new aircraft wing can now be brute force designed on a computer in a matter of seconds or minutes. New engine design, a new energy system design. AI is a tool of leverage that takes tens of thousands of years of work and reduces it down to minutes or seconds. And so just like any other technology before it, I think it indicates that this gives humans leverage. It seems magical at first. It seems unbelievable at first, but when you dig into what actually took place, what's really going on is just really intelligent systems designed to solve problems using human known techniques. So I just wanna kinda make my summary point on this whole thing. You guys are welcome to talk about partial differential equations and why they're so hard, but that that for me was my biggest takeaway on this whole thing. David Sacks (01:02:25): Yeah. The bigger issue here, Chamath. Chamath Palihapitiya (01:02:27): Your takeaway is that this was a very clever systems approach to brute force problem solving. David Sacks (01:02:35): Yeah. The other issue I agree with that. Here, Chamoff, is Chamath Palihapitiya (01:02:39): Also, Jason, the autocomplete still doesn't work. David Friedberg (01:02:41): Yes. We solved one of David Sacks (01:02:43): the seven hardest math problems in the world and you still can't get your intimacy kit from the front desk. Chamath Palihapitiya (01:02:48): And depending on the model, it still can't spell strawberry right. Speaker 5 (01:02:51): Or count to a 100. How David Friedberg (01:02:54): many r's in strawberry? David Sacks (01:02:57): Chamot, the other issue here, which we've talked about here in terms of AI sovereignty using open source in the enterprise, not trusting the frontier models with your data. When OpenAI came out with their solution, there was a claim that the original scientists working on this may have trained the LLM from OpenAI to make it easier for them to solve and OpenAI posted the following statement. While unlikely, we cannot rule out that de identified data derived from their usage, there being mathematicians, of our products helped improve our models. So maybe you could speak on AI sovereignty here. Should any scientist or law firm or, you know, person working in biotech making new potato seeds, should they trust any of these LLMs with their proprietary knowledge for fear of having it cribbed into a core LLM? Chamath Palihapitiya (01:03:56): If you have incredibly sensitive proprietary data, you have to make a very difficult decision because the reality is is that something is leaking, that there's remnant memory of how these solutions were solved that sits within these models even after the fact. There's a concept inside of these models called Zero Data Retention, ZDR. It's a best efforts basis. It's a commercially best efforts basis at that. They can't guarantee it. You know, simple example. You could say, do not retain the decision making process of this protein design. Okay. And it can kind of do that, but then if anybody that's using it clicks the like button inside of the chat window, that's not necessarily guaranteed. So there's all these vectors where this data leaks into the broad corpus and understanding that these models have. So if you believe that the information that you have is critically important, you cannot use these services the way that they're currently offered by most people. What you need to do is you need to stand up your own sovereign solution. What does that mean? That means you need to go to a vendor that you trust, could be AWS. In terms of the neoscalers, could be Nebius. And what they will do is they'll stand up your own hardware, and then you'll stand up your own models, and then they'll provision those models to you, and that's how you should probably be consuming it. And if you don't do that, you are creating risk. And look. Let's be clear. Will a handful of CIOs get very publicly flogged and fired in the next year because they accidentally didn't understand this and just did an API deal because they wanted to feel popular and leaked data into these models, guaranteed. David Sacks (01:05:50): Why will people get fired, Chamath? What... What's gonna happen? Chamath Palihapitiya (01:05:52): The thing that's happening right now is that a lot of this AI understanding and awareness is bubbled up through the audit committees and the risk committees of public boards. Who are those? Those are a handful of directors who are responsible for understanding the IT posture, the security posture of their business, and then they disclose that back up to the board. And then that understanding and awareness is what gets signed off and then submitted back to the SEC in these filings. They also have these consultants that help them, folks like Ernst and Young, Deloitte, and others. Increasingly, what we are all learning is that ZDR is not an effective solution and there's a ton of leakage. And so what's happening now, Jason, is that that information and that awareness is bubbling up through the risk and audit committees of these boards. It's now going to the broader boards, and now CEOs understand that, hold on a second. My information could leak. So now they turn to their CIO and say, okay. Whatever you thought was happening, we now clearly know that it's not. What is your answer? And it's when that happens or when all of a sudden they'll have to disclose some critical IP was leaked into a model or that they don't know whether it was or was not and all of a sudden something similar appears on the other side, that's when shareholders will be really upset because they'll say, guys, when OpenAI even tells you that they can't guarantee it and you have closed your eyes and assumed that your information isn't leaking, what are we to do? And if that decays and erodes my share value that I purchased from you assuming you were gonna have your hand on the switch, that's where folks get fired and Yeah. This is gonna be shareholder lawsuits. It's gonna be a mess. David Sacks (01:07:33): What does it mean for frontier models in terms of distrust leakage, etcetera? Another reason to, I guess, embrace open source in the enterprise and individuals who are doing import chain work. Chamath Palihapitiya (01:07:43): By way, sorry. It doesn't have to be open source. It just has to be On prem. Your own entire... Well, it doesn't even have to be on prem. It's effectively like your own VPC. You must go straight to the bare metal on your own terms. You need to control everything. You can work with folks like Amazon or Nebius or Fireworks. You can have open source solutions. You could even probably have Clod allow you to host a version of Clod in your VPC. But if you don't go through these hoops because you took a standard rate card API deal either because you were lazy or you didn't know any better and after today, you're still doing this stuff, you'll probably get fired. David Sacks (01:08:19): I had mentioned this over the summer. A lot of these AI application companies are now moving off of the frontier models and I think that's a headwind. We'll soon be able to see some data on, you know, these very large customers they have who are spending 10,000,000, 100,000,000 per month on these services. Chamath Palihapitiya (01:08:38): This is why we, eighty ninety, this is why we partnered with and Deloitte because we're like, hey, let's find a way to help solve these problems in advance. And initially, when when we would go and talk to a bunch of companies, they would be like, we did the ZDR thing. And we're like, okay, well, we'll just keep educating you. In five or six months, you'll realize that ZDR means literally nothing. And it's flimsy and it's Swiss cheese. And now, all these companies are coming back to and Deloitte and us and they're like, oh my god, fix the problem. David Friedberg (01:09:05): Yeah. Chamath Palihapitiya (01:09:05): And part of it is this realization that folks like OpenAI confirm in their own press releases. David Sacks (01:09:09): Yeah. Harvey announced September 9 that they had their own proprietary legal AI model, it's called Tenet, t e n e t and they based it on Kimi k three and I mentioned earlier, we incubated a company. It's called Go dot ai. And this company is on fire and what they do is just they build on prem, I think called the Go One box I'm showing here on the screen, just for people who want to get control of this. This is one of our incubated companies from our Launch Accelerator. I'll just give them a quick shout out there. Any thoughts on this and the data leakage issue, SACS, and what it means for the frontier models and how their biggest clients either trust or don't trust them with their data and their innovations? Jason Calacanis (01:09:58): I tend to believe Noam Brown, who's a senior researcher at OpenAI, and what he said about this is that nobody looked at Levent and Tristan's prompts. That'd be insane. So he's denying it. I think it just doesn't make sense to me that they rummage through their their prompt chains. Could there be data leakage through the unidentifiable data, perhaps? But look, I think the more plausible explanation here is that OpenAI heard that researchers were making progress on DeVeer Stokes and just threw a ton of compute at it to see if they could David Sacks (01:10:34): And Sam actually confirmed that part as well, that they heard that Anthropic was getting close, etcetera. So they were like, yeah, let's take a swing. Yeah. Jason Calacanis (01:10:41): So I think that's probably what happened. I mean, but look, I don't know anything. I could be proven different, but I tend to believe that. But look, I think this raises a somewhat orthogonal issue that's worth talking about, which is data privacy. And I think we need much stronger data privacy laws around the data that you have with AI services. So right now, the data you have in your AI chats doesn't even reach the same level of protection as email. So in most contexts, if the government wants to get your emails, they would have to get a search warrant and then have to prove probable cause in a court. But that is not the standard for AI data. The standard for AI data is you can just get a subpoena or a court order. And when you think about how personal AI is becoming, right, people are using AI as their lawyer, their doctor, their therapist, the list goes on and on. The idea that somebody could just get your data without probable cause, without a search warrant, that just seems kind of crazy to me. So I think we at least need to strengthen AI data to the level of email and maybe even beyond that to reflect how personal it is to people. And again, it's kinda nuts that if you talk to a lawyer, that's a privileged communication. But then if you ask that same question to your AI and then talk to your lawyer about it, it might not be protected. So we need, I think, for the data privacy rules to reflect how people actually use these tools and how they think about them. David Sacks (01:12:09): Any final notes on this free bug in terms of the data leakage issue? David Friedberg (01:12:13): I'm deeply concerned about it. I have had experience where we've asked some fairly novel scientific questions and it identifies it as a novel insight. It's like, oh, never thought about that. It'd be interesting, like, blah blah blah. And then using a different account asking the same model later or the next version actually later, I've now experienced this, it's like, oh, well, you could do this, and it actually just describes this exact thing that we had in our chat in the previous version. Now these are a handful of anecdotal experiences, but I know the domain that we work in and the niche of it and the ideation of this stuff and the novelty of this stuff and the lack of papers being published and so on. So I know that there isn't some new corpus of information out there that's training the new model. So all I can say at that point is that my conversation or our analyses have been used for training. Go ahead, Chewy. Chamath Palihapitiya (01:13:05): Siri, please prepare the shareholder lawsuit to a hollow. Okay. Jason Calacanis (01:13:11): This does raise a really good question which what does it mean that the model is allowed to train on unidentifiable David Friedberg (01:13:17): Well, that's my point. So it doesn't use any of my personal information, but it can use an insight derived from our chat which it can then say is some training data Trust me. That is unrelated. But the truth is it's actually a piece of IP that's our organizational's IP and our engagement back and forth. We don't have any NDA or confidentiality provisions or protections with them being a service provider back to us. And I think that's what's lacking in the terms of service in all of these, you know, hosted. This is why I care a lot about open source because I don't want them having my chat logs because they can use it for training to create an IT advantage that is now diffused to the rest of the market. Chamath Palihapitiya (01:13:59): I find this very unfair. And look, full disclosure, yes, I'm an OHALO shareholder. But Me too. Take any company. Like, you have these brilliant scientists at OHALO. They're pushing the boundaries of science. They are in a position to create true abundance. Okay. The first real manifestation of abundance would be food, right? And now Friedberg has to sweat whether his ability to actually build a viable business has been compromised, not because they did anything wrong, but because they thought they were just trying to use a tool to advance his ability to get to the answer faster. And he thought he was doing it in a reasonable way, and now all of a sudden it could just leak out. And I just think that that's not fair. David Sacks (01:14:42): I'm gonna get you a Go AI machine. I I literally just ordered two Mac Studio m fives. I just ordered two of these. We're gonna be running local models and we're moving off Claude for a lot of our sensitive data. Chamath Palihapitiya (01:14:53): Okay. The problem with local models, just to be clear, okay, whether they're closed or open, is that you need a multiplayer experience and it needs to be cloud based. You need to have a knowledge base. You need to have memory. So I don't think buying a machine solves the problem. The problem is that the way that these models are constructed, they are these layers of embeddings. Right? When you go from an input of token to an output token and the stuff that happens in the middle is a total leaky black box. That's the problem. And they give you a fig leaf to make you feel like you're not leaking your IP to folks, but then when push comes to shove and you ask them, have you learned and can you guarantee you have not learned? The answer is no. Not really. David Sacks (01:15:38): Yeah. The the thing we're doing is we're putting open source models on this and then we connect IP to IP to these as if they're servers and we've already experimented with it. I think we're gonna take like 90% of the work off Chamath Palihapitiya (01:15:49): of But our how does a thousand or a multi 100 person company It's gonna be more... David Sacks (01:15:55): They're gonna need to have rack servers. Chamath Palihapitiya (01:15:56): They're gonna stack Speaker 5 (01:15:57): rack servers and David Sacks (01:15:58): subs. Yeah. Jason Calacanis (01:15:59): Let's say that the folks at OpenAI are looking for mathematical breakthroughs and they would just ask their model, hey, what do you think are the top problems that we could solve like in the next few weeks? Would the model be able to use unidentified data from all of its users seeing all the math usage and seeing what is close to being Exactly. David Friedberg (01:16:19): Exactly. Exactly. So take away... So just focus on the term de identification. De identification means removing personally identified information or information that's specific to a particular company. But a general approach to a mathematical problem, the approach is VIP. So if someone is iterating on that approach inside of that tool, that iterative chat can be first step de identified. Okay. Great. There's nothing that identifies who did this. There's nothing that identifies something unique about a company or a person. Let me learn from this. And now the model is smarter at how to think about solving mathematical problems because it just observed this user using the model. This is the network effect of these closed AI model systems is they get to see what everyone in the world is doing. They're the master, you know, eye into everything. Chamath Palihapitiya (01:17:06): That's right. David Friedberg (01:17:07): And that observational system gives them more data than anyone else has and that is what builds their advantage over time so that their models are better than anyone else's models. But as a user, as an enterprise or consumer, I am personally concerned about my IP or my personal information. Jason Calacanis (01:17:25): Now we're in the Alex Karp world of you're giving them all your alpha. Yep. There's only one way to really solve this, well, from you just moving on to your own open models, your own infrastructure, is those companies have to for forswear, forgo the opportunity to go into vertical applications built on top of their platform. In other words, they can't compete with their customers. But they've already indicated a desire to compete with their customers, and they can't even tell you. David Sacks (01:17:51): They've already released Claude code. They released Claude design, and that really pissed off Kursor, who was one of the biggest customers that Anthropic had to date. And they felt they got rug pulled by Claude. Jason Calacanis (01:18:02): Right. And this is where the guys who are complaining, you know, Levent and Tristan, this is where you have to feel some sympathy for them, is they don't know. Like, they're making this accusation based on timing that actually our work got stolen. But the fact is that they are using OpenAI's models and OpenAI is competing with them to develop this breakthrough. So obviously, you're going to make that accusation whether it's true or not. I mean, I'm giving OpenAI the benefit of the doubt. I'm saying it's probably unfounded. But as long as we have a closed model duopoly of frontier AI and they're reserving the right to get into every vertical application there is, they're declaring in advance they're gonna compete with their customers. So how can we trust them with our data? Unless there are much stronger privacy laws as a starting point. And even that might not be good enough. David Sacks (01:18:51): Alright, gentlemen. Chamath Palihapitiya (01:18:53): Maybe that's the law we should pass first before we even regulate. David Sacks (01:18:56): Well, I mean, the market the market is responding to it. I mean, I think that's the the the high order bit here is that people are now taking measures. Yeah. Jason Calacanis (01:19:05): Hey. One piece of breaking news here. I don't know if you guys saw this, but Jensen is speaking at a conference right now, at the Goldman Sachs conference, and he just said that the Jacob Coxen comments are outlandish and deeply untrue. He said the labs are great, but his comments were wrong, arrogant, and ignorant of all the work being done around the industry to drive safety. Now here's my question. If Jensen can say this, why isn't it anthropic? David Sacks (01:19:35): Quiet period, I guess, ostensibly. They can't come out and say it? Jason Calacanis (01:19:38): No. They released a different kind of statement that was kind of, well, you know... Chamath Palihapitiya (01:19:43): Did you call it mealy mouth? Jason Calacanis (01:19:45): Mooshy. Mooshy mouth statement. Chamath Palihapitiya (01:19:46): What does it what does it mean to be mealy mouth? What does It's it it Oh, I see. David Sacks (01:19:51): I don't know what mealy is. Jason Calacanis (01:19:52): Vague posting, virtue signaling. David Sacks (01:19:54): Alright. Nike, the 60 year old iconic American brand, just do it, just got booted out of the S and P 100. They had been in the stock index, SACS, for eighteen straight years being replaced by, hey, shout out to our friend Nikesh, Palo Alto Networks. Congratulations to, Phil Hamyouth and Nikesh. Little history here, they went public in 1980 with 50% share of US athletic shoe market, dominant player, the Coca Cola of sneakers. And they changed things obviously forever with Air Jordans in '85. They did the iconic Just Do It campaign in 1888. Peak market cap in 2021 was $264,000,000,000. Peak revenue, $51,000,000,000 in 2024. Since then, revenues dropped a bit 10%. In 2020, John Donahoe became CEO, pushed an aggressive direct to consumer strategy, basically alienating all the retail partners who had helped build Nike and willingly removed those sneakers from the stores. That made brands like HOKA and On Running, that every VC is obligated to wear the white ones to any speaking gigs they have. China sales down 30%. H rate quarters of decline, losing share specifically to Chinese brands, Anta and Li Ning. If you're Chinese, you probably know those. Nike's marketing also went, and this might feed some people's narratives, super woke. And they started backing political movements and putting robust people sacks on billboards. I didn't get asked, but this kinda killed the entire brand stock down 80% from its peak. Sachs, $200,000,000,000 eviscerated. What's your take here? I don't know if the audience can guess. Jason Calacanis (01:21:49): I mean, this is the millionth example of go woke, go broke. You know, Nike was a brand that stood for great athletes, for amazing performance, for victory. I mean, isn't Nike the goddess of victory? Yeah. And they built their brand on goats like Michael Jordan, you know, and and great athletes like that in many different sectors, men and women of, you know, all different races. There there wasn't a need to, like, do all this woke stuff where now all a sudden they're showing people you don't know. I mean David Sacks (01:22:23): They generally had low percentage body fat prior to the work. Jason Calacanis (01:22:26): Well, but it's not it's not even about this. It's like this person isn't even an athlete. Like, who is this person, and what is the message? Like, own the floor. It used to be just do it. You know? And then they got Dylan Mulvaney in an ad, you know, like the whole trance thing? Yeah. This is like the Bud Light case. So you had the woke stuff. Then you have the other piece of it, which is this, like, consulting approach where new CEO comes in, and we know John Donohoe, nice guy, you know, central casting. He looks like a CEO. But it's like a lot of change for change's sake, it seems like, where he comes in and direct to consumer is the new hotness. So they blow up all their retail operations, all their retail relationships. They had all these stores that had shelf space for Nike, and now that goes to competitors who then took a huge amount of market share. And then the other thing I think they did is they did a reorg where they used to have departments in the company that were based on sports. So there's like a basketball division and football and David Sacks (01:23:23): tennis Swimming. And so on. Everything. Jason Calacanis (01:23:25): Swimming. And they, like, reorg that to be, I think, men, women's, and kids. So, like, why would you do that? I just... I don't get it. David Sacks (01:23:33): Working. You're surging. Yeah. To... They had a very clear model here, Chamath. Clicks and bricks. Right? Like, you could go to a brick and mortar store, have a great experience trying these shoes on, running around the store, working with people who help runners pick the right shoes, and it's nice to be able to buy direct. I have to say the Nike app's a delightful app, but why would they kill the retail channel of all things and piss off those folks who are their big advocates? Chamath Palihapitiya (01:23:59): If I've learned anything in almost thirty years of business, you have to have a very clear north star and stick to it. Mhmm. And at least when I was growing up, Nike's North Star was very clear to me, which was mastery and excellence embodied through athletics. That was it. I would see Michael Jordan and I saw Mastery and Excellence. I would see Tiger Woods, Mastery and Excellence. I would see Serena Williams, Mastery and Excellence. Pete Sampras, you name it, and it was Mastery and Excellence. And somewhere along the way, mastery and excellence became, too traditional looking. And so they they went away from things that were just nothing to be associated with mastery or excellence. I don't aspire to be a fat person. Never have. Never will. Speaker 5 (01:24:53): Yeah. Chamath Palihapitiya (01:24:53): I aspire to be Michael Jordan. Always have. Always will. And so I just think it's as basic as that. You're not going to buy the clothes of a brand that you don't aspire to be like by wearing those clothes or wearing those shoes. So I think as long as you can recenter around this idea that we're not here to make people feel better about themselves, We're... We were... Our success was when people imbued their desires of getting better through the lenses of these people that were incredible. That's aspirational. Being being inspired by somebody and wanting to be somebody better than yourself is a good thing. We should not shame that. It is good. It's how we all get better. And there are incredible athletes who give up their entire lives to master something. And I think that Nike should own that, and they should be proud of that. And so if they do that, all the other details will make sense. How do you sell? Sell it everywhere because everybody will want it. What do you sell? To everybody because everybody will want it. But if you don't get the North Star right, you're gonna miss out. And I think the North Star was clear, excellence and mastery. David Sacks (01:26:01): There's a broader discussion here, I think, that came up in your Eric Weinstein, incredible, all in interview, Freeberg, where excellence, expertise, and the desire to be elite, the desire to, to Mott's point, to be inspiring to people, somebody to follow. We... We've lost this love of excellence and expertise and it's been replaced with participation trophies or inclusiveness as opposed to excellence. Maybe you could talk a little bit about that in your field, your chosen field, science and entrepreneurship, etcetera. David Friedberg (01:26:39): Well, mean, those the entrepreneurship is a meritocracy, so you either do it or you don't. But in the case of this business, I think what they also lost was and it didn't just come through in the brand, I used to buy Nike. All the shoes I owned were Nike. It's all I bought. Chamath Palihapitiya (01:26:56): Me too. I bought David Friedberg (01:26:56): my brands. I like to go to them. You don't happen over time. 100%. It wasn't it wasn't that the ads went bad. It wasn't that the ordering was bad. The product started to suck. The shoes literally fell apart in like six weeks. They were flimsy. They didn't have the same quality that they used to have. I could tell that the product started to suck. So one day, I went down to my REI store next to the place where I get salads. I stopped in. I tried on a pair of Brooks. I bought the Brooks and I started wearing the Brooks. David Sacks (01:27:24): This is the Speedwalking 900 you got? The Speedwalking 900? David Friedberg (01:27:27): Are these Brooks shoes? And Horrible. Chamath Palihapitiya (01:27:30): That's an David Friedberg (01:27:31): exception. Great product. They they last forever. I know. They're durable. Chamath Palihapitiya (01:27:34): Not me. David Sacks (01:27:35): They're Marathoners do like Brooks. Yes. And speed walkers. Chamath Palihapitiya (01:27:38): Moved to... You know, wait. You know why I moved to On? David Friedberg (01:27:40): I actually got them for running because when I started running on the Nikes, like, I got these knee problems, so I'm getting old. The Brooks are awesome. I just feel great. Is that what David Sacks (01:27:49): they call skipping now is is running? Chamath Palihapitiya (01:27:51): I moved to Ons for one reason because I I held on to Nike forever. David Friedberg (01:27:55): Right. Chamath Palihapitiya (01:27:56): I was like a Nike diehard. David Friedberg (01:27:58): Buy new car every six weeks. Yeah. Chamath Palihapitiya (01:27:59): Of course. Every six weeks I was buying... Well, no, every six months I would buy new Nikes and I have still a collection of many Nikes. I love that. David Friedberg (01:28:05): Came six weeks, so the product sucked. Chamath Palihapitiya (01:28:07): And I finally moved to Ons for one reason because I'm like, oh, Roger Federer. He's excellence in mastery. I like him. Everything he does looks effortless. And I love that. And so I was like, Roger Feder. Good for me. David Friedberg (01:28:19): Let me just tell you the story on Brooks. You know, this company is owned by Berkshire Hathaway and they've grown this company nine years in a row, double digit revenue growth to 1,600,000,000 in revenue. It's a standalone company inside of Berkshire and it just keeps compounding revenue as a sub. There's an interview with the CEO where he said, like, Warren Buffett just told me every year, make the product better than it was at the end of last year. And if you keep doing that, the business will keep growing. And that's what he's been doing. I think that's the opposite of what Nike's focused on because they shifted from product to narrative, and it was all about what's the narrative that we think the audience wants to hear. It's the same problem that Bud Light had. And the whole thing... Yeah. And when you when you kind Chamath Palihapitiya (01:28:57): of Remember that huge ad for Colin Kaepernick they ran in San Francisco? It's like Jason Calacanis (01:29:01): That was a turning point, Chamath Palihapitiya (01:29:02): to my opinion. Was like, what what the hell does that have to do with anything? I want excellence and mastery. David Sacks (01:29:07): Yeah. You don't have to comment on everything. Yeah. Jason Calacanis (01:29:10): I think that if you were to pinpoint the beginning of the downfall, that was it. I mean, look, there have been moments in sports that were inherently political and they were great moments. So you could think of like Jesse Owens, nineteen thirty six Olympics, Ray's fist. Chamath Palihapitiya (01:29:26): Yes. You know? Jackie Robinson. Muhammad Ali. Jason Calacanis (01:29:29): Jackie Robinson or Muhammad Ali refusing the the draft into the Vietnam War, but they were all the greatest. And their causes were things like standing up to Nazis and protesting the Vietnam War and protesting racism. What what was Colin Kaepernick taking the knee for? To protest the American anthem? What was the point of that? And was he the greatest or one of the greats? No. He was not. And so why would you give that a platform? What were you promoting exactly? What were you trying to say? And then they kept doubling down with, like, the, you know, the Dylan Mulvaney and then the rest of this woke stuff. It is so breathtakingly stupid. I mean, their job was marketing. Right? And they're actually, like, marketing images that are so contrary to what their brand was about. It's so craven. It was so fattish that I think that every single person who was part of that decision making chain from the marketing executive all the way up to the CEO, they should be drummed out of corporate America. I mean, how could you ever approve those campaigns? David Sacks (01:30:38): I mean, it was it was during a certain time period, obviously. Chamath Palihapitiya (01:30:41): If they find mastery and excellence as their north star again, I think they'll be fine because I think it's a coiled spring in terms of its potential. Like, if you gave me a reason to come back to Nike, I would. Well, that's what I was doing down What do we do from here? But, like, at Stanford... Well, because the problem is, like, at Stanford, the Nike store closed. You know what? Replaced it? On. And you know when you go to the On store, it's amazing. And you're like, oh, Roger Federer. Is this is Roger Fed... This is what I think when I go in there. And now I may be limited in my ability to understand why I need to care about all these other things when I buy a pair of running shoes. But normally, I was just thinking about mastery and excellence. Michael Jordan shoes, my shoes. Tiger's clubs, my clubs. You know, Sampras' clothes, my clothes. Federer's racket, my racket. That's how simple I am, and I would just happily buy that stuff. So you just, a, you gotta reestablish yourself in retail locales where there are people with disposable income, and, b, decide whether you wanna be aligned with mastery and excellence because then I think tens of millions of men and women will show up again because that's what they want. Maybe they wanna get back in shape. Maybe they want to reestablish themselves in a sport. Maybe they wanna learn a new sport. And I would just embrace Nike everything, and now I don't. David Sacks (01:31:57): Yeah. They they should have really gotten into the smart devices as well. They dip their toes into that. I thought that was, like, really good because it was so performance based. If they owned Stravia, is that the app that all the elite Strava. Strava, all the elite biking and running people do, and then, you know, embrace that, and then you should just redo the tagline. Do it or don't. Like, come up with, like, a really challenging rebranding. Do it or don't. Chamath Palihapitiya (01:32:20): I think Jason Calacanis (01:32:20): that's Yoda, JKL. David Sacks (01:32:22): Yeah. Yeah. It is Yoda. Chamath Palihapitiya (01:32:23): I would love Jason Calacanis (01:32:25): That is why or do not. Speaker 5 (01:32:25): There is a try. Do it or do not? Chamath Palihapitiya (01:32:27): If you became the CMO if you became the CMO Nike Nike. Yeah. I'll do it. I would launch an activist campaign. I would literally Do it. Buy billions of dollars of stock Dude, I lost 43 David Sacks (01:32:39): pounds. You gotta... I'm doing farmer's walk half mile, 20 pounds on each arm. Jason Calacanis (01:32:43): Bro, if you just don't buy into this woke bull you're, like, ahead of the game right there. Chamath Palihapitiya (01:32:48): Yeah. Just do it. Jason Calacanis (01:32:48): Refocus. Just do it. I cannot get past the incompetence to work your way out of the S and P 100. David Sacks (01:32:55): Alright, everybody. That's your all in podcast for September 11. Chamath Palihapitiya (01:33:01): Thank you, Jason, for your mastery and excellence yet again. David Friedberg (01:33:04): Yeah. Just do it or don't. Just do I'm getting Chamath Palihapitiya (01:33:06): thirty, forty Do or don't. Do it or don't. Do it David Friedberg (01:33:09): or don't. I mean, it's great. I Jason. Marketing genius, Don Draper over here. David Sacks (01:33:13): Everybody makes some ads with me as the CEO, and do it or don't. We don't give a fuck what you do. David Friedberg (01:33:20): This is like Brooklyn Don Draper. Jason Calacanis (01:33:22): Yeah. We go from just do it to do it or don't we don't get it wrong. Speaker 5 (01:33:26): No. I think it David Sacks (01:33:27): would be like a very Jason Calacanis (01:33:28): provocative thing to way to make things worse Speaker 5 (01:33:30): and, worse. You guys are wrong. Test it. Test it. Do it David Friedberg (01:33:34): or don't. Chamath Palihapitiya (01:33:35): Have you found a way to get kicked out of not just the S and P 100, but also the 500. David Sacks (01:33:39): 50 listed pink sheets? No. I think it Chamath Palihapitiya (01:33:43): will work. Do it or don't. David Sacks (01:33:44): I'm standing behind. Chamath Palihapitiya (01:33:45): That's what you should tell the S and P committee. Do it. Do it Speaker 5 (01:33:48): or don't. Chamath Palihapitiya (01:33:49): Do it or don't. That's or don't. Do it or don't. David Sacks (01:33:53): I mean, I'm good at marketing. Who named this podcast? Terrible. I named it Speaker 5 (01:33:57): all in. David Sacks (01:33:57): I named it. You said, what do we call it? I said all in. Then I got the domain name, you ungrateful Alright, everybody. Chamath Palihapitiya (01:34:04): Let's get seated. I love doing it, daddy? David Sacks (01:34:07): No. I negotiated with the owner. I got it for 250 beans. I got a great deal on that five letter domain. Chamath Palihapitiya (01:34:13): Okay. Well, do it or don't. You did it. Do it or don't? David Friedberg (01:34:15): I did it. Chamath Palihapitiya (01:34:16): Did Did it. David Sacks (01:34:16): Say thank you, bitches. Alright, everybody. We'll see you at All In Summit. Another thing Chamath Palihapitiya (01:34:20): Love you, boys. David Sacks (01:34:21): That I did. Okay. There you go. The All In Summit is this weekend, Sunday through Tuesday in LA presented by iRen. IRen is the AI cloud, data centers, compute, and software for training and inference. They're throwing Sunday's registration day party, so grab your badge, grab a drink, and join us at the iRen House in the Expo Hall for a meet and greet and photo op. We're also excited that Meta will be in the hizzy. President and vice chair, Dina Powell McCormick, will join us on stage, plus there's a Meta Glasses Experience Hub. Check it out at the all in summit. Speaker 5 (01:35:28): We should all just get a room and just have one big huge orgy because they're all just useless. It's like it's like sexual tension that they just need to release somehow.