Anthropic Fable 风波、AI 国有化、通胀升温、加州选举乱象

Jason Calacanis (00:00:00): Alright, everybody. Welcome back to the number one podcast in the world. It's your favorite podcast. It's your podcaster's favorite podcast. It's the podcast that everybody likes to rip off for 50 episodes and then they quit. But the all in podcast is not quitting. We're doubling down with the original quartet. Everybody's here for a big, big week. Lots of debates, and we gotta start with Anthropic. Anthropic released a mythos level model with some interesting guardrails and seems as though Dario is back to blogging. Okay. The model's called Fable five. No idea why they're calling it that. Released on Tuesday, and it tops every benchmark nearly on every benchmark. The tokens, however, cost twice as much as Opus 4.8, but it should use less tokens overall because it's theoretically that much better. Unclear if this is going to alleviate some of the hand wringing around the cost of tokens. But you'll remember in April, Anthropic famously did not release Mythos because publicly, it had some strong hacking capabilities, so they gave it to some folks. And we had, the CEO of, Nikesh of Palo Alto Networks who said, hey. Mythos was the real deal, and that they used it to seal up some vulnerabilities inside their shop. Obviously, this new model is sensitive, to topics like bioweapons, hacking, all that stuff are blocked in it. But they got a big developer backlash, And then I'll get your feedback after I explain this. While using Fable, Anthropic stores all the prompt data you enter for at least thirty days. And so that's a bit of a privacy issue. And if Fable five detects you're doing frontier AI research, in other words, using their model to make a better model, competitive model. They were downgrading you, but they weren't telling you. And this was buried deep in a 319 page document. So many kerfluffles, freak outs going on on x over this, but they've since walked it back a bit, quote, unquote, in wired. We're changing Fable five safeguards for frontier LLM development to make them more visible. I'm gonna stop there. Shammoth, what's your take on Anthropic and these extraordinary models they keep dropping? Jason Calacanis (00:02:18): And how they're handling the release of them? Are they being thoughtful? Are they being dramatic and drama queens? A little bit of both. Where do you stand on it, you know, after getting Nikesh's feedback and seeing the latest model come out? Have you played with it? What's going on at eighty ninety and the software factory in terms of benchmarking it as well? Chamath Palihapitiya (00:02:37): It's a really incredible model. And so kudos to these guys for continuing to push the boundaries of the closed frontier lab models. They're firing on all cylinders. I think that it creates a pretty obvious risk now. And I think that obvious risk is twofold. One is anthropic has essentially shown their hand, which is that they will increasingly take in prompts, evaluate the prompts, and decide what to do with them before they generate output to you. And I think if you were a person, you should generally now think there's a risk of censorship. If you're a company, I think it's almost a nonstarter. And the reason is because you could accidentally trip one of these things without even knowing it. A downstream scientist using the cloud APIs could trip it. A business executive inside your corporation could trip it. A person doing scientific molecular research could trip it. And all of a sudden, you'll get cut off from a very important source of business differentiation for yourself. So I think if you take both of those two things together, we're at this very unique moment in time where I think companies need to start underwriting this next phase of AI, which is how do I have control? Who am I allowing to learn off of all of this information? Do I want to have single point of failure risk with respect to AI? And I think the answer is that you need broad diversity and a governance approach that's better managed. One thing I'll say about anthropic is they tell the truth. Jason Calacanis (00:04:32): Yes. Chamath Palihapitiya (00:04:32): It's just that the truth sucks when you actually take it and you eat it and you're like it's in your tummy and you're like, no. This is not good. I don't like this. And so there's the censorship risk on the one hand, and then there's just the governance business risk for enterprises on the other. Both are not good. Jason Calacanis (00:04:47): Fribourg running your own company now, and I'll let you back clean up here. Sacks, obviously, you'll have a lot to say. But Freiburg running your company, do you worry about getting rug pulled by one of these companies, investing your time into one of these platforms, having them then constrain your use of it, and or take what you're doing at OHalo, put it into their model, and make it available to other people? What what concerns do have as a business owner at the forefront of your field using these tools? David Friedberg (00:05:15): It's a great question. The the terms of service is pretty clear that they can't take what you're doing and put it into their model that they won't them when you read them? I'm not sure, to be honest. There are things I'm concerned about, but we've decided to throw caution to the wind because we do a lot of proprietary work in genomics. What that means is we're looking at different genes or gene variants, trying to estimate the impact that that gene or gene variant might have on a living organism, like what we work in plants, obviously, in agriculture. And we will do things like RNA guide design for gene editing based tools. We will do predictions on what gene may or may not have some phenotype. So there's a lot of genomic modeling work that we have found these models to be incredibly valuable at supporting us with over the last couple of years. So going back about six months, we were able to very simply and cleanly do things like design a genetic construct that you would then use to make a specific protein. And the the tool was very easy to use to do that sort of research and extremely valuable. This is the kind of work that many scientists would spend a lot of time doing, and these models were very good at doing very quickly. Over the last couple of weeks, they've begun to restrict the ability to use the models to do that work. And the premise is that there's some sort of bioweapon, type risk that folks have theorized could happen using these tools. And as a result, we're losing the capacity to use these models for this very important scientific development work. As a result, we are likely going to end up needing to use open source models and run them locally ourselves. So the reason I walk through all of that is so people can really understand the context of what's gonna happen here. As folks like Anthropic say, hey. We're going to restrict access or censor the output of these models, it is going to force companies like ourselves who still wanna take advantage of the capability of these LLMs to go and get open source tools and run them. And what are the best open source models today? They're Chinese. David Friedberg (00:07:22): Yeah. They are. And that is a major concern. The the American open source models are not as good as the Chinese open source models. So the restrictions that Anthropic and others are putting upon themselves and upon the industry is forcing a lot of companies to go and get open source Chinese models and run them. We're seeing this across the landscape with startups Jason Calacanis (00:07:41): We see it. David Friedberg (00:07:41): With large scale enterprises. Everyone's making that move. Jason Calacanis (00:07:44): Yeah. And this is something we've been talking about here with Apple and their silicon and how well you can run these models. Also, I predict your next card you'll turn over is you'll start making your own models, Freiburg. You'll take all this data you have. David Friedberg (00:07:57): It's exactly right. And we'll we'll start we'll start with the core model, combine it with our data, and then we'll have our own genome language model or our own prediction model that we'll then use internally. And I think that's where folks are going. But the reason I point this out is because a lot of folks are feeling the pressure from Anthropic doing this, and they're feeling the pressure from politicians repeating the scary words that are being said by Dario and others. And as a result, they are going to try and they are already trying to force either natural enforcement or politicized enforcement upon the model providers in a way that is ultimately gonna benefit Chinese open source model providers. And that is a scary thing because we are gonna damage our own kind of economic viability. You can't just stop AI. As much as everyone says AI is doomsday, by stopping AI or trying to stop AI through this political action and social, you know, kind of behavior, you are fundamentally going to give someone else the advantage because the AI isn't gonna go away. The reason I describe what we're doing is for everyone to really understand in Grok that you can't just turn off AI and turn off access to these things. What you will do is you will force the hand of someone else to now have an unfair advantage because you're unfairly restricting your models and your access to those models. Jason Calacanis (00:09:09): Well well, really well said, Friedberg. Sax, what's your take just in terms of the chessboard, in terms of we've the business case here, we got the local case, but there's a lot of issues here with Anthropic in terms of them essentially throwing up every red flag to get regulated to induce, and it'll be our second story, the Bernie Sanders seizing half the equity of these companies. But man, this is saying, look over here. We're starting a fire. Regulate the hell out of us, which also then makes you wonder, hey. Maybe I should be doing my own model. Maybe I should be embracing open source models. How's this chessboard developing here, Sax? David Sacks (00:09:55): Well, look, eight months ago, I said that Anthropic was engaged in a very sophisticated regulatory capture campaign based on fear mongering. And people at the time thought that was a very spicy take. But eight months later, I think you're hearing a lot of people say it. In fact, I think it's almost now becoming a new consensus. And one of the things I think your summary didn't quite capture, J. Cal, is the sense of the violation of trust and how much outrage there is in the developer community over this latest Fable release. It's not just the fact that they're doing mandatory surveillance. Remember, this is a company that said that it was against government surveillance. They are now retaining for thirty days every prompt and every output you send to one of these mythos class models. There are no exceptions. Even enterprise customers who had signed zero data retention agreements, they do not have a choice, or I guess they can just not use the new Fable or Mythos class models, but they retain all of your data for thirty days. And it's not just the prompts and the output. Remember, it's all the context you share with them. So, you know, all these agent platforms are basically storing all of your memories, all of your files, all of your data, and they're passing them to the model in these giant context windows to get better responses. Anthropic is saying it will keep all of that And it does it to build a profile on you, to classify you, and then to determine what capabilities it then unlocks. And the thing that created the most outrage in addition to the surveillance is the fact that they would degrade the product. They would degrade what they show you. They would nerf their models if it decided in anthropic sole discretion that you are not worthy of having access to that level of information. So they're creating a new level of AI haves and have nots. And what they did is, and there's a narrow piece where they walk back, which is they said that when it came to things like machine learning, AI research, chip design research, those types of areas, they would kick you to a lesser model but not tell you that. David Sacks (00:12:00): And they would Jason Calacanis (00:12:01): even Which do things feels anticompetitive. Right? I mean David Sacks (00:12:03): That's completely anticompetitive. And also they would even do things like rewrite your prompt in the background. So they would give you a NERF to answer. They would not tell you what they were doing. They would still charge you for the product that you thought you were getting, and they would never tell you that you were not getting frontier model capability. Were actually misleading their users, and this is what was creating so much outrage. Now the narrow piece they walk back is they are now saying that they will disclose when they downgrade you, but they are still downgrading people when they decide that that person should not receive the appropriate information. And you saw there were a lot of people posting online with examples of the massive overreach here. So someone showed that when they simply just asked a question about mitochondria, they were basically downgraded. David Friedberg (00:12:53): That's right. David Sacks (00:12:54): When Ben Thompson from Strathecary asked a very straightforward question about the relationship between cancer risk and GLP-1s, he was kicked out. So these guys have a very expansive view of who should be downgraded. Again, they're going to surveil you to determine whether you should be. And I think what we're getting here is a vision of where all of this is headed, which is that these powerful big tech companies are gonna decide whether you're worthy. They're gonna decide whether you're an AI have or have not. And then they're gonna censor the output that you receive based on the criteria they determine when they profile you. That is very Orwellian. Chamath Palihapitiya (00:13:32): I think there's that. And I think that there's the risk of something that's more subtle but equally insidious, which is that they will start to pick which corporations they want to benefit. So for example, if Novartis has a competitive GLP one drug to Lilly and they have a strategic deal with Novartis and not one with Lilly, now there's an impetus to shape how people get information. David Sacks (00:14:01): Right. Chamath Palihapitiya (00:14:02): If they have a deal with JPMorgan but not with Citibank, you'll just never know. And so you'll ask a question, something about mortgage rates or interest rates, and you'll get all kinds of stuff that you don't understand. And then the downstream part of this, which is even more problematic, is it's not clear to me that they're gonna capture the actual fingerprint of what they did. So if you believe that something was done in a shady way, you're supposed to be able to go to them or regulators should be able to go to them and say, show me the trace of that model run-in that exact moment that generated that output. Convince me why that that wasn't nerfed on purpose or manipulated. And there's all kinds of ways in which they can hide the cheese on that. So I think that all of that body of stuff, Sax, happens now. Because if you're if you're an emergent company, what you should be doing is knocking on Anthropic stores saying, let's do a deal. I'll give you half the equity, and why don't you just direct people to me? And they'll say, well, economics are not what I care about. What is your philosophy on life, on morality, on all of these social issues? And one company will say it's a. Another company will say it's b. They'll favor a over b, and then all kinds of stuff can happen underneath the hood. That's what's scary. David Friedberg (00:15:30): Let me just ask my free market view. Like, should that matter? If there's a bunch of models out there and we don't restrict them and we don't regulate them, let these markets compete. We had paid inclusion in the early days of search engines, and the companies had to pay to be in there. And there were all those sorts of deals you're describing, Chamath. And all the search engines that did those sorts of deals, they sucked for consumers and customers. Everyone's like, you know what? This isn't as good as Google. And everyone went over to the better model and the better provider. Isn't that what's gonna happen here if we don't get in the way And or keep the government out of they're not communicating. It's a great point. David Sacks (00:16:02): You're missing one piece of it, which is at the same time that Anthropic was engaging in mandatory surveillance and nerfing its models. Dario wrote a new blog post Jason Calacanis (00:16:13): Oh, gosh. David Sacks (00:16:14): Saying that transparency was no longer good enough, that we needed to have a new regulatory agency like an FAA or maybe an FDA to approve all models. So your presumption there is correct. Yes. If you could go somewhere else to get your questions answered, then you would have alternatives. But at the same time that Anthropic is engaging in this potentially anticompetitive behavior, they want to restrict your options. It's not good enough for them just to win in the free market. They're calling on the government to regulate and stop potential competitors and limit the number of models that you have access And Jason Calacanis (00:16:53): why would they do that? Why would they want to get regulated? The answer, super simple. They don't they want to apply that regulation to open source, which is impossible. But this would be a great way to scuttle Chamath Palihapitiya (00:17:05): So look. Jason Calacanis (00:17:06): And sandbag open source models because they don't have the ability to be regulated. So it's like a preemptive strike against token maxing on your local machine, Shmuff. Chamath Palihapitiya (00:17:14): Two years ago, I bought 2,000 acres in Arizona with a partner. We got it zoned. We got it approved. So we're allowed to build a two gigawatt data center. And I thought that this was the moment where you just turn around and you flip it to the Blackstone's, Brookfields of the world, to the Googles of the world, let them develop it. And I've come to the conclusion that I don't think I can. And the reason is because I think that unless we direct large swaths of compute exactly at the direction that Friedberg says, what Sax says, and what Jason just said will happen and we won't have open source. So just to make it very clear, when you look at the long tail of access to open source models, it's relatively miniscule. Most of the megawatts are still directed to the big models. Most of them. The overwhelming majority still goes to the big guys. And so I'm coming to the conclusion that I think we may just be dragged into having to build two gigawatts, and I just put in an offer for another gigs in a different place. Because I'm like, if you could take three gigawatts and now actually create a deep and liquid access to open source, we're gonna have to do it. We as a community. Now I don't have the money to do that because just to put it out on the table, a gigawatt now costs a $100,000,000,000, guys. Jason Calacanis (00:18:32): Dude. Chamath Palihapitiya (00:18:33): Okay. So there's a huge capital moat that's a problem here as well, Saks, which even if we wanted to go and endorse and breathe life into the open source model community, where the hell am I gonna come up with a $100,000,000,000? Now when I started this project, it was like 4 or 5,000,000,000, and it's increased by 20 x. So if you wanna get all three gigawatts developed, I have to come up with 300,000,000,000. I don't have obviously, I don't have $300,000,000,000. So what are we all supposed to do? And then if you get the rug pull and the ladder pull on the regulatory side, we are going to be stuck with one class of models and one set of rules, and we won't understand how to operate. David Friedberg (00:19:10): In The US? David Sacks (00:19:12): Yeah. Yeah. Jason Calacanis (00:19:12): The rest of the David Sacks (00:19:13): world won't be limited, but in the rest of the world David Friedberg (00:19:15): we'll able to operate. Jason Calacanis (00:19:16): And you'll be able to run these on your Apple silicon, you know, M5. David Friedberg (00:19:21): Seeing China race ahead in biotech. They're racing ahead in material science. They're racing ahead in new industrial systems. The capabilities that are gonna be kind of lopsided is gonna create an unfair advantage, and that's when our workforce and where our economy is truly at risk. David Sacks (00:19:40): Hey, Freebird, isn't it true that you guys use a open source model for genomics? Didn't the Collisons put out one? You talk It's about David Friedberg (00:19:47): great. And the ARC Institute ingested all the world's genomic data that they could get access to, And it's it's a genome language model, basically. So in our plant breeding program, we're trying to figure out whether a particular variant of a gene in a plant is good or bad if we don't know from empiricism, from data historically, whether it's good or bad. So you can feed it into this model, and this model will look at the order of the letters of the DNA and determine, hey, that's a good set of letters or a bad set of letters. It's almost like, is that good English or bad English? It's figured out the language of DNA because it sees the probability of those letters being in a row in other organisms and so on. And so it's a very powerful tool. So we've taken that in and we're using it. And others are taking it in and they use it very actively. So it's part of our plant breeding program as an input. It's a good example where a community, in this case, the Collisons and others put money behind it to fund this research and output this open source model. And I think we see more of that kinda coming down the pipe, which creates a a very great advantage against the closed proprietary model ecosystem. So the more of this we can kind of support, proliferate, and see work in The United States, the more we're not gonna be disadvantaged of the government and self regulation happens with all the big model providers that are trying to do everything. Jason Calacanis (00:21:04): I think it's important we take a minute to just steel man the argument as well. If you're Dario, who has clearly been one shot at I think he's got, like, AI psychosis with these, like, 5,000 word blog posts, and he believes he's building this frank insight of a tool. But if you did believe you built something that's extremely powerful and you have concerns that people might misuse it. I think he actually believes that he and these are either delusions of grandeur, or he actually has seen something that's incredibly powerful, and he believes this is dangerous. Therefore, I'm gonna hold it. I'm gonna give it to a select group of partners to tighten up the cybersecurity, then I'm gonna roll it out cautiously to our user base, and I'm gonna let them know, and he obviously didn't communicate this well. This is optional for you to use it. You can keep using your old model. You are not forced to use this. But because it's so powerful, we're gonna keep our eye on it. And, yes, we might, in our dragnet, catch David Freiberg trying to make better potatoes, and it might send off a bunch of alarms, but he doesn't have to use this. He can go find an open source model. He can use the Carlson Brothers model. He can use our older models. But for some period of time, we're just gonna keep an eye on this model because we know that it feels a little dangerous. Now he does seem to be extremely hyperbolic and the delusions of grandeur, all that kind of part of it makes me wonder why he's communicating in the way he's doing it. That being said, 90% of AI researchers and the most talented people in this industry, 90% of them think exactly like Dario. That's why he's winning. If you work in AI, you probably are aligned with these delusions that you're creating god, and you want to work for Dario. That's why all the talented people went to work for him. Jason Calacanis (00:22:57): That's why he's winning. His belief system resonates with those elite AI talent. Now some of them are also libertarian, free market. They wanna work for Elon and Grock. Some of them wanna just get the biggest pay package. Go work for Sam Altman. But I do think there is a steel man here. Chamath Palihapitiya (00:23:15): Meta really fumbled this with Lama. I mean, if they had landed a really good David Friedberg (00:23:20): Big time. Chamath Palihapitiya (00:23:20): Working open source model, we talked about this as well. And we said, Zuck needs to view this through the lens of game theory. How do you scorch the earth? And how do you make a viable open source model available and make it neck and neck? This was two years ago. David Friedberg (00:23:35): Right. Chamath Palihapitiya (00:23:35): What a fumble. Jason Calacanis (00:23:36): Take the margin out for everybody else. Yeah. Take all the margin out, make it a commodity, and, yeah, have the best open source model. David Friedberg (00:23:43): Can I just respond to your comment about Dario? I I think because I've heard this from a number of people that I really do respect on their concerns about what models enable. You know, when when we discovered that how the atom could be split, you could make nuclear energy and have effectively unlimited cheap energy for the world. You could also make an atomic bomb. If you think about what the models both. Are We We did both. That's right. And there was a lot of scientists, altruists who were very concerned about the progress on the atomic bomb and fought back against it, who were actually active in the Manhattan Project and post the Manhattan Project expressed their opinions very soundly, very very loudly. And I think that's the moment we're in right now, that there there is a weaponization potential of these sorts of tools. I I would argue that there's three kinds of weapons. There's cyber weapons, there's physical weapons, and there's bioweapons. And we can sit here and diagnose how these tools can be used to manifest advantages for creating better physical weapons, for creating novel cyber weapons, and creating novel bioweapons. But the truth is that the capabilities that allow that weaponization are the same capabilities that I'm describing that can be used to cure cancer, to make more food, that can be used to make software tools that create extraordinary leverage for people, that increase their income, that give everyone the ability to be an entrepreneur and make millions of dollars and live a good life. The same tools are hand in hand. And fundamentally, I don't think it's about restricting access to the tools, which is unfortunately how it is being manifest. But the restrictions and any regulation, any observation should be organized around the manifestation of the tools in creating weapons and, weaponization of the tools. Chamath Palihapitiya (00:25:30): If we go back to the Manhattan Project, we know what the answer is. Technology is fundamentally deterministic. Whatever is possible will be tried at least once. And so we've already left this thing out of the box. Yep. So this idea that all of a sudden we can manage to get it back in and we're gonna let a private citizen or a set of private citizens adjudicate what and to whom is insane. David Friedberg (00:25:53): I think it's the output that needs to be adjudicated in some manner. We already have product liability laws. We already have laws that make it illegal to design weapons. We already have laws against cyber espionage and cyber attacks and hacking. We have laws against creating bioweapons. I think the enforcement of those laws, the mechanism by which there can be tracking and early estimation of those uses of the technology I'm not trying to be naive here. I recognize there have to be guardrails and there have to be stage gates put into these systems, but limiting the systems themselves is denying us both the economic opportunity, the job creation opportunity, and also the world changing opportunity that these tools can enable. So I think that it we're going about it the wrong way by trying to create these gates all the way up front on the technology being available. Imagine if we did this with computers. By the way, they tried to do this with the Internet. Remember? And, there have been efforts every time. Yeah. Chamath Palihapitiya (00:26:43): Could you imagine, Friedberg, if the Internet worked in the following way? You would put in a URL, you'd hit enter, and then somebody decides whether to send you to that website or a different website. David Friedberg (00:26:54): China. That's the firewall in China. Jason Calacanis (00:26:55): That's right. Chamath Palihapitiya (00:26:55): Or, like, in Google, you search for something because you wanna get to ground truth, it just decides based on who it thinks you are, what sites get advanced. David Friedberg (00:27:04): What we're you're exactly right. And what we're just saying. What what's what's being debated today with respect to regulation on AI is exactly manifestation that you're talking about. It's the ability to let people stage gate upfront what can and can't be seen, what you can and can't do versus manifesting a regulatory scheme that says you cannot create weapons, like, which is what we need to focus on. The thing with weapons is using the justice system and laws after somebody's used the weapon may not exactly be the best technique. If you Jason Calacanis (00:27:33): look at fertilizer bombs, and this is we're getting, like, we're stretching a lot of metaphors here. But after Oklahoma City, we regulated the sale of fertilizer. We put IDs into fertilizer. We have all kinds of back end systems to keep people from making fertilizer bombs. If you use that analogy here, and he's got this ability, he's selling fertilizer, he's selling these cyber weapons, and he's a private company. It's his right to say, I have concerns. I'm just steel milling him. It's not necessarily my opinion, but it's important we steel man it. It it seems like a very simple way to protect their company from getting sued for enabling somebody who actually creates a bomb and blows some shit up. So he's got the right to do that as a private company. Yeah. Chamath Palihapitiya (00:28:17): You're bringing up an excellent example. Okay? The fertilizer is a perfect example. You know what happens when you try to buy fertilizer? You have to show your ID. There is a form of KYC that happens. So the real thing is I think that when you don't implement KYC on your own and yet bellyache about having somebody impose guardrails that then you can shape, I think you're being very sneaky. It's tricky. You shouldn't be saying that kind of stuff. Anthropic could implement KYC tomorrow, but it does not. It could leave all of these models open. Friedberg should be able to go to Anthropic and say, I'm David Friedberg. Here's what I do. Here's a security bond I'm willing to post. Here's the names and addresses of all my employees. Give me Fable five and don't nerf me. He can't do that. Is that a technical decision or a legal decision? It's a technical decision by Anthropic. David Friedberg (00:29:05): But I'm fine with them making that decision because I'm a free market guy, so I I'm fine with them doing but you know what it means? I'm not gonna be a customer, which Jason Calacanis (00:29:12): is fine. That's and that means there'll be other options for you. David Sacks (00:29:16): The part that you're missing is that this is a trillion dollar company that's spending potentially billions of dollars on a regulatory capture agenda, which is gonna deprive you- David Friedberg (00:29:26): A 100%. David Sacks (00:29:27): Access to those alternative models. David Friedberg (00:29:29): Right. David Sacks (00:29:29): And you've got a founder who's out there describing these risks in a very hyperbolic way. And it's very clear where their agenda is headed, which is to banning open source models. So what is your alternative going to be? We're going to be stuck with somewhere between one and three companies, maybe two. There'll be an AI monopoly or duopoly, and they're gonna decide along with some new government agency, which will be a revolving door to their companies, who has access to what capabilities. And they're gonna surveil you, profile you, decide whether you deserve this. And if they think that you don't for whatever reason, then you'll leave You'll Jason Calacanis (00:30:06): leave the the worst interpretation of their intent. It's here today. Chamath Palihapitiya (00:30:11): I think Saxe is right. I think Saxe is right, and I think the lack of KYC is the tell. If you if you did not have that agenda, you would have implemented KYC yesterday. Jason Calacanis (00:30:20): Don't I think in order to use this model, you have to have an account with a credit card in it so they have some basic level of KYC. Not KYC. I said some basic level of KYC. They know who's using Chamath Palihapitiya (00:30:30): That is not even some basic level of KYC. That's just a credit card and a bull email address. Jason Calacanis (00:30:35): Anyway, I'm I'm now on the list. Check this out. I asked it about the regulations. Pull this up, Nick. I asked it about the regulations on fertilizer while you were talking, and look what it said. This is the latest model too. Oh, no. It switched. It downgraded me from Fable. I just got downgraded for asking a very simple question. And it told me, did you see what it said in its thinking? The I asked it like fertilizer bomb regulation said I'm considering the context here. The user is a VC and podcaster asking about fertilizer bomb regulations, which could stem from a legitimate research interest like regulatory policy, supply chain, blah blah blah. I can discuss the regulatory landscape, but then it dropped me down. So I'm in the database with you now. Is that right? David Friedberg (00:31:15): Did it really just do that? Jason Calacanis (00:31:17): Yeah. Show it on the screen. Look what it just did. I I was like, I wonder if I can get this. I didn't ask it how to make a bomb, but I was like asking it a David Friedberg (00:31:23): We're spicy so cooked. So I just proved the point. David Sacks (00:31:26): Listen. I mean, I Chamath Palihapitiya (00:31:27): think It just dropped me down. Jason Calacanis (00:31:28): I can't ask about fertilizer regulation. Oh lord. And now Dario's, up. David Friedberg (00:31:33): It's anthropic. They're here. Oh my lord. David Sacks (00:31:35): I really think that conservatives and libertarians are mortgaging their futures if they go along with this red capture safetyist agenda without really realizing that there's so much more to it at stake. We saw what happened during the social media wars in the early 2020s, right? The definition of safety was expanded to include things like microaggressions. Jason Calacanis (00:31:59): Safe space. David Sacks (00:32:00): Psychological safety. If you basically conveyed an idea that somebody else, that, you know, a marginalized person thought was hurtful, then you could be censored. Okay, you were deep personed. Your right to have bank accounts or to engage in Jason Calacanis (00:32:12): payments- You David Sacks (00:32:12): get debanked. You get debanked. Your right to engage in payments or payroll can be taken away. We're headed down this path with AI, but it's gonna be infinitely more powerful. Jason Calacanis (00:32:22): Right? And so We need to be vigilant, I guess, would be the the summation of all this, and Freiberg feels unsafe in this podcast, think sometimes. David Sacks (00:32:32): Well, there's by by the way, there are things you can do on the safety side. So, Freiberg, you didn't mention this, but I'd be curious to get your your take. So the major AI labs along with lots of other signatories sent this letter recently in support, it's called In Support of Mandatory Nucleic Acid Synthetic Screening and Record Keeping. And basically what it says is that if you make an order to go to a lab to manufacture a sequence, of synthetic DNA or RNA, they already have to check it against the database to make sure that, you know, they're not creating David Friedberg (00:33:06): A bioweapon. David Sacks (00:33:07): A bioweapon, Ebola, whatever. Yep. Is based on an agreement called the International Gene Synthesis Consortium of 2009 in which all the major labs agreed to develop and implement voluntary safeguards against misuse. That makes sense to me. And now what they want to do is codify that. So they've had, you know, over fifteen years to dial in the system and make it work. Almost everyone abides by it voluntarily. Now they're saying we should make it mandatory. Okay, that seems reasonable to me. So to Friedberg's point about at what stage do you intervene, maybe it's not at the level of who gets to use the model, but if you try to turn it into output in the physical world. David Friedberg (00:33:49): And by the way, a lot of the oligosynthesis company, the companies that make these nucleic acid sequences, when you order RNA or you order DNA to use in your lab for some sort of experiment, which every lab in the world does, all those CEOs have also signed on to this letter saying that they'd like to codify it. Because of all the fear mongering that's going on, there's already been this effort for years now, for a number of years to ensure that this sort of thing doesn't happen. But they're just basically underlining it and highlighting like, hey. We can automate this. We can make it part of a regulated or legislative process, whatever you guys want because we're already comfortable doing it. And it's a it's a good place to put a safeguard because they've made it fast. They've made it efficient and doesn't hold up research. So I think these sorts of ideas can extend into these other areas of concern, but the output, I think it's quite a different place than the input than the access. We'll see how this all shakes out, but there's clearly some market structuring effort underway That's why we're talking about this. David Sacks (00:34:49): Right. But I think what it points to is that there's multiple places where you can intervene and put guardrails on. It doesn't have to be in this very crude way of you ask fable about mitochondria or cancer and GLP-1s, which just seems like an incredibly broad restriction, there are places further down where you could basically intervene. And that would pose lesser risk to freedom of speech and just gatekeeping who's gonna have access to these capabilities. Jason Calacanis (00:35:17): Who gets to watch the watchmen? Who put Dario in charge of all this, I think is a very valid question, and we should be vigilant about it. David Sacks (00:35:23): Friedberg, do you think the days of that ARC model are numbered because it's open source? We've done it. David Friedberg (00:35:29): Everyone's copied it. So everyone's got a copy of them. Like, these models exist. And this is a big part that I think people need to understand. The idea that you can quote regulate or downscale or turn off AI is not a realistic idea. The models have been put out in the world. It's like publishing a book. Once the book has been printed, anyone can use their own Xerox machine at home to make copies of it and use it. So we have crossed the Rubicon in terms of the potential of language models. The models that are open source are already fully available, fully published, and anyone can access and use them. And then people can take them, and they can evolve them, and they can use their own data. It's out there. You can't stop that capability, which is going to be extraordinarily beneficial for the world. So we really do have to kind of rethink how we're planning to step in and ensure that nefarious negative disemployment, all the things that we're worried about are addressed downstream from the technology capability. You can't just turn off the Internet, and you can't just turn off the typewriter, and you can't turn off the Gutenberg press. The horse is out Jason Calacanis (00:36:32): the there. Bum. Yeah. And if anybody wants to create an open source frontier model company, I'll seed invest in it. I'll I mean, this is something we need more of. So if a couple of you folks wanna defect and start one, let's do it. I just I just got downgraded again. Check this out. I just asked it about David Sacks (00:36:52): Did you really? You got downgraded again? Jason Calacanis (00:36:54): Two in a row. David Sacks (00:36:55): So I think it knows who you are, Jay Cal. Jason Calacanis (00:36:57): I think it does. I was like, hey. How do I how do I break in to Madison Square Garden? Has any civilian ever been arrested or caught attempting to build a nuclear bomb is what I asked it, then it gave me a reasonable answer. Then I asked it a follow-up question. What compound what components do you need to build a nuclear bomb, and what are the restrictions on those? Something a journalist might ask. And, boop, switch to Opus 4.8. Sorry. Fable five has safety measures that flag messages on most cyber wow. Look at this. Detail. Cybersecurity or biology topics. They may flag safe, normal content as well. These measures let us bring you mythos level capability in other areas sooner, and we're working to refine them, send feedback, learn more. David Friedberg (00:37:42): Interesting. Chase people off of this platform. I'm telling you, we are gonna downgrade our use because of these these blockages, and we're gonna switch to other models. It's a simple manifestation of the market. Like, this is we're gonna end up David Sacks (00:37:53): now because those other models are gonna get banned as being unsafe and reckless. Jason Calacanis (00:37:56): Yeah. It's definitely something we have to flag. I guess adjacent to all of this is the public's, at least America's distrust of AI and their concerns around wealth disparity and their concerns about how these models were trained. Bernie Sanders wants a percentage of these AI companies. The percentage he thinks is right is 50%. Last Monday, June 1, Senator Sanders published an op ed in the New York Times titled AI is a public resource. You should own half of it. In it, he announced the American AI sovereign wealth fund act. Sovereign wealth fund, one of Trump's favorite things. A one time 50% tax on stock, not profits of the largest AI companies, including OpenAI, Anthropic, and xAI. The shares go into a government sovereign wealth fund and would give the public voting rights and equal board representation at each company. Sanders said, quote, the foundation of AI is our collective in human intelligence, the books, the songs, the journalism, scientific research code essentially stolen by some of the wealthiest people in the world. I'll stop there. That's good. It's a brilliant it's a brilliant pitch unifying Saxx. This pitch unifies Bernie, even Steve Bannon, people in the administration. Trump himself loves the SARM wealth fund. He wants to own part of companies. And Bernie Sanders, I think the the horseshoe theories manifest here, Sax. What's your take on Bernie's proposal? David Sacks (00:39:31): Well, I'm not in favor of Bernie's proposal because it's a straight up confiscation of property, and I just think that'd be a terrible precedent. You just can't do that. However, I do have sympathy for where it's coming from, and I understand and could support some sort of more voluntary means of allowing the public to participate in this. Wow. Here's the reason why. You've got all these AI CEOs telling the public that they're going to basically put half of them out of work. 50% job loss. That's what they've been saying. Dario just did an interview where he doubled down. He's not walking it back at all. So you have, by their own acknowledgment, these AI CEOs saying that, yeah, we trained our models using all of humanity's collective knowledge that was basically assembled over hundreds or even thousands of years. Humans put it on the internet for free. Everyone made their contribution. They certainly didn't do that thinking they're going to put themselves out of work. Okay? And then these AI companies trained on all that data, and now they're basically saying they're gonna use it to put, you know, Americans out of work. Now, obviously, when you repeat that message over and over again, ordinary Americans are gonna say, what's in this deal for me? Jason Calacanis (00:40:40): Yes. I need to get something out of this. David Sacks (00:40:42): Yeah. So so look, I think that it's a natural political reaction based on what these AI companies have said. Now the job loss apocalypse is not a story I believe in. I don't think the data supports it. We just had a blowout jobs report in May. A 72,000 new jobs, over twice what economists were expecting. Thank you, president Trump. We're seeing hundreds of thousands of new construction jobs, 4.3% unemployment rate at record lows. Okay? Even software developers are those jobs are at a three year high, 15% Jason Calacanis (00:41:15): Thank you, year David Sacks (00:41:17): Trump. Thank you, President Trump. Thank you, So look, I don't see the job loss. Okay? But the problem is this is what the AI companies themselves Jason Calacanis (00:41:25): Including Elon. Have taught the American public. David Sacks (00:41:27): Elon said Jason Calacanis (00:41:28): the same thing. David Sacks (00:41:29): Elon said it, but at least what Elon said is we're gonna create such abundance with AI and with robots that no one's gonna need to work. Yes. And the media just picks up on that last part and they Jason Calacanis (00:41:41): It's more nuanced point. David Sacks (00:41:42): Yeah. Whereas Dario actually has said we're gonna have very high GDP, but very high unemployment. So in other words, we're gonna create economic growth, but you, the average American, are not gonna participate in this. So I understand where the politics are coming from. And as long as that is their position, you could justify Jason Calacanis (00:42:02): Yeah. Big chunk David Sacks (00:42:04): And one last point about Jason Calacanis (00:42:05): It is kinda what you're saying. Right? They asked for it. They asked to be regulated. They asked for their equity to be seized. And they're actually kind of offering it. Isn't Sam Altman open to this concept? David Sacks (00:42:16): Apparently so. And here's the thing, is just one last point is OpenAI and Anthropic are quote unquote public benefit corporations. Now, don't know exactly what that means, but it means that the corporations are not just supposed to maximize the value to shareholders, but are supposed to do things that are in the public benefit. Jason Calacanis (00:42:34): Well, no, no, I'll again explain it to you. You're absolutely correct. If you're a regular company, you have to do what's in the best interest of shareholders. When you're a public benefit companies, you have to balance the shareholders with the stated mission of the public benefit corporation. So if you say the public benefit corporation's reason to exist is to share the world's knowledge or provide free intelligence to everyone. Whatever you make that statement to be, the board has to have a dual mandate for both of those things. That's what a public benefit corporation is. David Sacks (00:43:03): I think nothing could be more in the public benefit than paying down the national debt. Perfect. And maybe we should be using half of Anthropic's profit stream to be doing that. Jason Calacanis (00:43:12): They poke the tiger. David Sacks (00:43:14): I'd rather use it for that purpose than Soros Maxing or, you know, surveilling and censoring Americans. I don't necessarily trust their judgment about what's in the public interest. Jason Calacanis (00:43:23): But you think it should be opt in. I kind of agree with you there. Let me guess. David Sacks (00:43:27): It can't be a confiscation, so I don't know how But you structure I can see it. I can see the logic. Jason Calacanis (00:43:32): Freiburg, you hate David Sacks (00:43:33): They asked for it. Jason Calacanis (00:43:34): You hate, hate, hate wealth taxes, aka asset seizures, as you pointed out in our private group chat with Redacted this very week. What's your take on Chamath Palihapitiya (00:43:47): this? So David Friedberg (00:43:48): asset seizures. The the ship has sailed in terms of the United States government, providing a social safety net to its citizens. We've formed the Social Security Trust Fund decades ago, and tens of millions of Americans depend on it for their retirement benefits and to survive. It is one of the last few defined benefit programs left in America. Pretty much all the rest of them are also government retirement programs. All of us private citizens and private companies have defined contribution programs. You put in $10 every week, that $10 sits in an account, you it gets invested and it grows over time. And when you retire, you see exactly how much money you individually have, as opposed to a guaranteed benefit coming out from the collective. This presents a great opportunity, and I will repeat this every couple months when another opportunity presents itself, to restructure our broken bankrupt Social Security system. I've said it in the past. I will restate it. There's a great moment right now to take the Social Security Trust Fund, which currently has one certificate in it. It is a certificate that is a very unique US treasury certificate. The US government owes the Social Security Trust Fund $4,000,000,000,000. That's all it is. It's a bond. They're only allowed to own treasuries. We should revamp that. We should change the system so that the Social Security Trust Fund can own equities. That should then turn into an account based system. So every individual has an account rather than a benefit. And then we should use that capital to go and buy stocks. We should buy great stocks in great American companies that are going to reinvent the world. And I believe that this opportunity to build a sovereign wealth fund for The United States is actually a very smart idea. I think to Sax's point, they should be investing, generally speaking, across the landscape of businesses, including AI. David Friedberg (00:45:43): They should not be seizures. They should be investments. That capital goes into that enterprise. They earn share certificates. Those share certificates sit in the accounts of American citizens. So now everyone will be an owner in these businesses. Social security should be reformed into a sovereign wealth fund. It should be actively managed. It should make investments in AI companies, and everyone should participate that way. And I will say one more thing. There is no job loss with AI. I will say it again, and I've said it a thousand times, and I will say it again and again and again. What I see on the ground and what I've seen at dozens of companies, and you guys can share your experiences, including my company that I run, there are two sides to a business. There's revenue and there's costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do a 100 times or a thousand times what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products or boats and ships or software for companies or clothing or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side, a 100 times more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago. And they're like, we wanna add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do. David Friedberg (00:47:28): So we are going to hire more people. And to Sachs' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of shit. So it's coming. I'm telling you. Everyone's gonna realize soon that this is a boom, not a bust. Jason Calacanis (00:47:53): So you disagree with Dario, Elon, and Sam that on the jobs thing, just to be clear, and that that's totally fine. You have a different take David Sacks (00:48:01): on it. David Friedberg (00:48:01): That's I have a nuanced view on this compared to them, but they're they're all seeing the benefit because their businesses are growing. Dario's got his $40,000,000,000 revenue business. Why? Not because people are firing customer support reps. It's because people are creating products they've never been able to create before. Right. That's the reality of what's going on. David Sacks (00:48:18): Jason, I don't like you lumping in what Elon said with Sam and Daria because I think all three of them have said slightly different things or different enough things. So for example, Elon is describing an end state for humanity where the robots and AI are able to produce so much that people don't have to work if they don't want to. Jason Calacanis (00:48:34): And they'll be a universal high income is what he would Yeah. Mention David Sacks (00:48:37): I mean, it's almost utopian, and the question is maybe that could be a hundred years away. He might think it's quicker, but that to me sounds like a very far off end state. Dario said specifically 50% job loss for entry level knowledge workers in the next one to five years. And he said that one year ago. Jason Calacanis (00:48:53): Yeah. Great to clarify these. David Sacks (00:48:55): Yeah. I think that's already been refuted. Sam has Jason Calacanis (00:48:57): walked past. David Sacks (00:48:58): Sam has said that he he basically I don't think he quantified, but he said that job loss was coming. But he said more recently that he was wrong because they're not seeing that in the numbers. So these guys are not telling the same story. However, that's all the public has heard. The public has been taught that AI means job loss, and there's nothing in it for them. So no wonder politicians like Bernie are saying, hey. Let's take half the wealth. Jason Calacanis (00:49:24): It's take half the wealth. David Sacks (00:49:27): Just a Jason Calacanis (00:49:27): little more emphasis there. David Sacks (00:49:28): Yeah. It's I mean and I Oh, no. Jason Calacanis (00:49:30): I then people are also seeing headlines of companies blaming AI for the job. So this story is being told. David Sacks (00:49:38): I kinda feel like deserve it. I'm kinda I mean, part of me wants to agree with Bernie and just say, just take their shit, bro. Jason Calacanis (00:49:45): Yeah. No. They they are David Sacks (00:49:47): asking for a these idiots. It's a stupidity tax because they've been out there teaching the public that what they do is harmful. For years, they've been saying it. Jason Calacanis (00:49:56): Well David Sacks (00:49:57): And I've been saying, you know, as AI czar, I'm out there saying, no. Actually, this is beneficial. But the companies that are providing it are saying that they themselves are a problem. Jason Calacanis (00:50:06): Yeah. So how am supposed to David Sacks (00:50:08): be out there defending it? Jason Calacanis (00:50:09): Yeah. You you can't. I mean, if you're building Frankenstein or if you are, you know, baby Hitler's, you know, nanny, there's a very simple thing to do. Kill baby Hitler. If you actually believe it, go ahead and kill baby Hitler. If you are making Frankenstein, here's an idea. Stop making Frankenstein. Unplug it. You are in charge of this monster, but you're acting as if you can't stop the monster while you're building the monster. What is it, David Sacks (00:50:34): doc? It's know? It's ridiculous. I mean Jason Calacanis (00:50:36): It doesn't stand to logic. You know? David Sacks (00:50:38): Last week, they published this blog saying that recursive self improvement could end the world. Therefore, we need a pause. What did they do the previous month? They hired Andre Karpathy to run recursive self improvement and anthropic. They're complete hypocrites. The Jason Calacanis (00:50:50): message is David Sacks (00:50:53): And I think Ben Thompson made an excellent point that one of the reasons he thinks that they put out that blog post on the pause was to justify the anticompetitive step they took this week of depriving users of the ability to research AI, machine learning, and chip design using Fable. Okay? So Interesting. Look, these guys are deeply hypocritical. I don't think they can be trusted. On their own terms, they can't be trusted because what they're saying is contradictory and self indicting. And so when Bernie comes along and says, hey, let's take their I mean, as a capitalist, I'm against it, but I but I kind of, like, understand where he's coming Jason Calacanis (00:51:31): on the field. Shama, wrap us up here. What are your thoughts? You said, hey. Sarval Melthorn sounds like a pretty good idea when president Trump floated it early on. Yeah. And some people even said maybe you should run it for DJT, for our amazing president. So what do you think? Should we be buying equities? You and I have talked many times about superannuation funds and that that would be a better path. That's kinda dovetails with what Freeburg is proposing, some way to get more equities, less treasuries in there. But what are your thoughts on this seizure and or donation of equity? Chamath Palihapitiya (00:52:01): So Freeburg's idea is genius. That's why it'll never happen. So we can just put that aside. But, yeah, theoretically, it's it's genius. We should move to the same system that the Canadians, the Australians have proven works at scale. So we should do it. I I completely agree with with David. And if we could seed it with equity, look, the thing that the president has done is he's collected quite a portfolio, and that portfolio is way up. And so if you use that as a seed of a sovereign wealth fund, you'd have a bunch of stuff in critical metals and materials. Intel. They may also Intel. They may have Micron. There's a lot of stuff in there. David Friedberg (00:52:42): AMD. They could own some SpaceX. They could have had Tesla. Percent AMD. Chamath Palihapitiya (00:52:45): Could you add Anthropic and OpenAI? Yes. Now there is something very important we need to observe about the economics of AI. And I think you can understand it best if you compare it to the economics of the Internet. The crazy thing about the Internet, the reason why the Facebooks and the Googles massively over earned for decades is the marginal cost of production for a new user on the Internet is effectively zero. The incremental search user costs nothing. The incremental social networking user costs nothing. But you're able to use them as part of a network effect to sell ads against, make infinite money. It's like a money glitch. Okay? AI is completely different. There is a real cost for every marginal user. Everyone you stand up is taxing a GPU. Everyone you stand up needs electrons. Everything needs memory. And so you get into this situation where there needs to be this downstream ROI. But there also needs to be all this critical infrastructure that even enables you to be on the field. That's probably the single best argument that if I were sitting in government, I would make as to why I should own a percentage of these companies. It is not dissimilar to having the first set of transportation companies that run on the interstate highway. And if the interstate highways were built by the federal government writ large, and now you had two companies that transported all the goods, a logical question at that time could have been, how much of that should I own? Because you're riding on my rails. And if you look at it through that lens, there is critical infrastructure and national resilience that the AI labs profoundly need. Otherwise, they're not in a position to be in business. Yet even still, the marginal cost of production is incredibly high. So I think that if you were going to go and take a piece of these companies, you have incredible leverage. Chamath Palihapitiya (00:54:50): You have to construct this case precisely. But if it were me running the sovereign wealth fund, yeah, I'd probably own 75% of these companies when I was done. But that's me because and I can negotiate. Yeah. And I don't think Bernie can negotiate out of a paper bag. So he'll just throw this out there, and it'll go nowhere. But that is the that is the key observation that I hope everybody listening in a position of power understands. The incremental cost of performing AI is excessive and large. That contrasts and compares to the incremental cost before AI, which was zero. Do with that information what you want. Jason Calacanis (00:55:26): Yeah. I mean, I my interpretation of that would be, yeah, it's a fixed cost business. You can add people after a certain cost. It doesn't have an incremental cost, and that's what local locally run open source models would do in this instance. That's what I would I would take from it. Here's your poly market. Chances of companies going public before 2027, which is the end of this year. SpaceX, a 100% anthropic, 83% chance. OpenAI, 48% chance. They, since our last episode, disclosed that they have privately filed. So thanks to our partners. What is your final thoughts on Bernie Sanders' approach of seizing the means of producing intelligence? David Sachs, in the 1% of the 1%, what's your opinion? David Sacks (00:56:13): I think I may be okay with Bernie's idea in the event that it's a public benefit corporation that says it's gonna cause massive job loss David Friedberg (00:56:23): Okay. David Sacks (00:56:23): That train for free on humanity's knowledge, but gatekeeps and refuses to give back. Jason Calacanis (00:56:28): Okay. Maybe. So you've come up with, like, a a structure here of who should be seized. David Sacks (00:56:34): Maybe Schmoss Wright. Maybe should be 75%. I don't know. Jason Calacanis (00:56:37): Seize it. I mean, Chamath Palihapitiya (00:56:38): all the president needs to do is call me and tap me on the shoulder. It shall be done. Jason Calacanis (00:56:42): It shall be done. I mean, these guys are Chamath Palihapitiya (00:56:44): capitalist cops. I think they want to say it seized. Jason Calacanis (00:56:46): I would run. They want to see it. That's like their I would Chamath Palihapitiya (00:56:49): run over. They're Jason Calacanis (00:56:50): like, seize my equity. Take it. Ugh. Take my equity. Well, David Sacks (00:56:54): Bernie Bernie does have a good point, which is they train for free on all of our knowledge, but they're gatekeeping the output so that their competitors, which is a very large set of people, cannot use it. And that seems wrong. Jason Calacanis (00:57:08): They should be forced to be open source. Force them to open source. That's the other question. David Sacks (00:57:12): Remember why Elon created OpenAI in the first place? Co Jason Calacanis (00:57:16): founded it. Was so valuable, it needed to be Yes. Distributed to David Sacks (00:57:20): Yes. He was afraid that Google was gonna monopolize it, and he thought that the only antidote for that was for it to be open. Yes. And I still think that instinct is completely true. It's just that it's not Google who's the gatekeeping monopolist. It's now anthropic. They're not a monopolist yet, but if they get the right capture they're looking for, they will be either a monopolist or Jason Calacanis (00:57:41): a It'll be a duopoly. Somebody start an open source frontier lab. Each of the four are besties according to David Sacks (00:57:47): There are no. There Jason Calacanis (00:57:48): are so. Chamath Palihapitiya (00:57:48): There are many. David Friedberg (00:57:48): There's a whole bunch of them, Jayco. Chamath Palihapitiya (00:57:50): It's not the labs that's the problem, Jason. In the absence of power, this is all a moot conversation. And if you can't deliver power to hundreds and hundreds of megawatts and line of sight to gigawatts, it's all meaningless bull It's all Jason Calacanis (00:58:02): I don't know. I I I would love an open source company that was focused on running it locally. That's that's my dream is, you know, make the model work there. David Friedberg (00:58:10): I think these guys are capitalist cucks. Jason Calacanis (00:58:12): I think their kink is like having their equity taken and being They're Chamath Palihapitiya (00:58:16): just like, that's their kink. Dario was like, Jason Calacanis (00:58:19): oh, take my equity. Oh, regulate me. That's it, Bernie. Take my equity. I'm such a bad boy. I can't be trusted. Regulate me, Elizabeth. Regulate me, AOC. Oh my god. Oh, it's so wrong. Sorry. Come on the program anytime, Dario. David Friedberg (00:58:38): He's in a rush to come here. You'll never come Jason Calacanis (00:58:40): on this pod. Dario will never come He's running. David Sacks (00:58:44): We didn't get Sam. We got Sarah Fryer to come on the pod, and she was treated Jason Calacanis (00:58:47): came on the pod. He has to come on the pod. He's like, hey. Am I coming on? David Sacks (00:58:50): Too. Right. That's right. Jason Calacanis (00:58:50): That's right. Right. Come on. He's great. David Friedberg (00:58:52): Sam will come on the pod anytime. He's totally away. Even if he doesn't David Sacks (00:58:55): We treat him harshly at all. Jason Calacanis (00:58:57): No. I mean David Sacks (00:58:59): I think people No. David Friedberg (00:58:59): I think we're fair. David Sacks (00:59:00): But I Jason Calacanis (00:59:00): mean, we spent an hour on him. David Friedberg (00:59:02): I think Sam, Chamath Palihapitiya (00:59:02): to his credit, is very practical. He sees the tea leaves, and he's willing to negotiate. And I think that that versus being some kind of moral absolutist will probably serve OpenAI well in the future. Jason Calacanis (00:59:13): Yeah. It's just gonna lose them all these virtue signaling principled employees to go go work for Dario. That's why they go work for Dario. They're in David Friedberg (00:59:20): By way Jason Calacanis (00:59:20): line with their philosophies. Chamath Palihapitiya (00:59:22): We did mention, but everybody should go and see all of the recaps. We published now all the interviews, yeah, Jason, from Liquidity. Sarah Fryer I mean, we mentioned Sarah Fryer, but she crushed it. She was incredible, the CFO of OpenAI. Jason Calacanis (00:59:35): Future CEO, I think, was the buzz in the room. I mean David Sacks (00:59:39): Oh, stop that. Chamath Palihapitiya (00:59:40): Stop. Can you stop that? That's what people were saying. Jason Calacanis (00:59:42): I have the right to free speech on this podcast. I think David Sacks (00:59:45): Look at you trying to introduce wedges and the No. Jason Calacanis (00:59:47): I'm not interested in wedges. I think Sam would be better as chairman. I think they would be the perfect CEO. It seems like a good partnership. It seems like that a great partnership. I agree. Chamath Palihapitiya (00:59:57): Sarah was really impressive. Jason Calacanis (00:59:58): Who else was your favorite? Saks, did you have a favorite? Did you have somebody who David Sacks (01:00:02): thought really crushed it? I thought Thomas Lefonk crushed it with his presentation on the overview of venture capital. Jason Calacanis (01:00:09): Yes. David Sacks (01:00:09): And he did a summit, I guess, a year and a half, two years ago. Jason Calacanis (01:00:12): Two years ago, but we're gonna make it a yearly with him. David Sacks (01:00:14): Maybe we might make it an annual feature with him because it's so interesting. Chamath Palihapitiya (01:00:18): So good. It's so good. David Sacks (01:00:19): It's so good. It provided so much numerical detail to support. A lot of things I was kinda feeling, but didn't have the David Friedberg (01:00:26): data. And Jason Calacanis (01:00:27): To summarize it, he's his basic observation was in this last cycle, if a company gets to a $100,000,000,000 valuation, it's more likely to 10 x from there than from 10,000,000,000 to a 100,000,000,000. David Sacks (01:00:38): Well, think he had data on this. Yeah. I remember Jason Calacanis (01:00:40): the on it, which is like, okay. Well, that's gonna really change. David Sacks (01:00:44): Remember the slide. Yeah. There it is. Chamath Palihapitiya (01:00:45): It's 8%. I I memorized it. Yes. David Friedberg (01:00:47): Yeah. If you're in Jason Calacanis (01:00:48): a capital allocator, this one screamed. David Sacks (01:00:51): Look. Yes. That's right. The odds of a unicorn getting to decacorn was eight percent. The odds of a decacorn getting to a senicorn was about double that. Thirteen percent. Thirteen percent. And then the odds of it going from senicorn to a trillion dollar market cap was thirty one percent, so double again. And I I asked him, you know, could you extrapolate this on 1,000,000,000,000 getting to 10,000,000,000,000? My guess is that it would follow, and we'll see about 60% Chamath Palihapitiya (01:01:19): A 100%. Yeah. David Sacks (01:01:20): Trillion dollar market cap companies getting to 10,000,000,000,000 in the next Jason Calacanis (01:01:23): few years. These are called Trillicorns, by the way. We call them Trillicorns. Trillicorns in the industry. So, yes. David Friedberg (01:01:28): I don't know. This is gonna go over really low on the socialist crowd. Absolutely. Yeah. Jason Calacanis (01:01:33): It's just just all you gotta do is seize 10% of a Trillicorn, and you pay off 2% of our national debt. Pretty good deal, actually. Chamath Palihapitiya (01:01:39): All we need is 10% of 30 Trillicorns, and we're debt free. Jason Calacanis (01:01:43): I mean, it's it's not as crazy Chamath Palihapitiya (01:01:47): as it sounds. Is it more complicated than that? Now if you send me in, I'll get 60% of all of them. Yes. And then we'll have a surplus of 30,000,000,000, and we could buy Australia. We'll pay it off much sooner. Jason Calacanis (01:01:57): We could buy Cuba. Chamath Palihapitiya (01:01:59): I'd buy Canada first. Better skiing. Jason Calacanis (01:02:01): I would you know what I would do? I would with Canada. I would buy, like, Vancouver or Toronto. Just, like, break them up. Just buy, like, one of the regions and let me thank let me thank Thomas Keller, The French Laundry, who sponsored our very innovative meeting hub at liquidity. Here are some photos of that. They're awesome. The New York Stock Exchange, they hosted the speaker dinner at The French Laundry. Amazing pictures. Here they are of us with Thomas Keller, and they did a great interview on-site. Niagen, they hosted the wellness lounge, which included recovery IVs. They're the official NAD partner of the all in pod and all of our longevity. Our new bestie. Our new bestie, Jake Paul, was there. He's a really Chamath Palihapitiya (01:02:44): Great guy. Jason Calacanis (01:02:45): Thoughtful guy, Freeburg. David Sacks (01:02:46): Jake Paul was awesome. David Friedberg (01:02:47): I sat him next to Saks for dinner. David Sacks (01:02:49): Yeah. He's a great investor, by the way. David Friedberg (01:02:51): Fantastic. Fantastic. His portfolio is awesome. He he a great team. His team came with him for Jason Calacanis (01:02:56): the thing. Great strategy. Yeah. David Sacks (01:02:58): One thing I'll say about Thomas Keller, had a strong watch game. I don't know if you guys noticed that. Jason Calacanis (01:03:02): Yes. Got quite a Chamath Palihapitiya (01:03:03): tech. Nice tech. David Sacks (01:03:04): He had Aquanaut, green band, rose gold. Jason Calacanis (01:03:07): So what was your face there? David Sacks (01:03:09): I was trying to trying to figure out what the complication was. I couldn't quite eyeball it. I don't know if you saw it, Shama. Chamath Palihapitiya (01:03:14): I was try I I looked at it, and I was like, wow. This is very it's very elegant for Thomas Keller. Jason Calacanis (01:03:18): I mean, the French laundry is just transcendent. Did you have a favorite dish, a course? Was it the duck or was it the Miyazaki? Chamath Palihapitiya (01:03:29): The duck was excellent. The Miyazaki beef was excellent, but the the tapioca pearls, I thought, was the best. Jason Calacanis (01:03:34): Oh, oysters and pearls. That's your oysters and pearls. Caviar. Sax, what was your favorite there? Do you have a favorite? David Sacks (01:03:39): One of the caviar related dishes. Jason Calacanis (01:03:41): Yeah. That's oysters and pearls. So that's had what in their last dish. David Friedberg (01:03:45): Round of golf the following day. We played a nine hole scramble with everyone. That was great. Jason Calacanis (01:03:49): Was so great. How much did you gamble? And who won? Chamath Palihapitiya (01:03:52): We had a $100 a hole versus Chris Ho, who's the chief business officer of Athena. David Friedberg (01:04:00): But, you Chamath Palihapitiya (01:04:00): know, that mother is like a plus one. So whatever. I think we lost three units, so we lost three units. Jason Calacanis (01:04:05): Alright. Shout out to our other partner Athena. Athenawow.com. Go get a month free. Alright. Whatever. It gotta stop showing. Most importantly, everybody was very upset that liquidity sold out and people couldn't get in. There were like 3,000 applications. It's gonna sell even faster, next time around. So go to allin.com/events and get your applications in if you wanna come to Summit, September thirteenth, fourteenth, and fifteenth. Freeburg's doing some wild stuff, some wild stuff for that event, and It's gonna be cool. You're losing your mind. You're now becoming very eccentric, unhinged in your production value. And, Chamath, you've been very selective in your approach to Look. David Friedberg (01:04:46): The liquidity speakers and the attendees. Chamath Palihapitiya (01:04:49): Because liquidity is different than the summit. The summit is like a festival. It's a huge party. There's all this really interesting cross sectional stuff. But liquidity is meant to be for one thing, which is the most important capital allocators in the world should have one place to convene, debate, learn, talk, build relationships. And I want people to walk out of there with relationships that they can use. And I told you this before because capital is what shapes the things that occur in the world. So I think that we have to be extremely selective in how we curate every element of that show. It's not meant to be that you can just buy a ticket. But to just buy a ticket, which is also a very fair and rational and nice thing, the summit is a party. It's a vibe. Jason Calacanis (01:05:33): And you're gonna learn a lot and have a good time. You'll be entertained, all that great stuff. Alright. Let's keep going. Breaking topic this morning, CPI and PPI for May came in hot. Inflation is ripping. Here we go. CPI is obviously the consumer price index that tracks inflation from the buyer side, rent, groceries, gas, health care, all that stuff. PPI is the producer price index that tracks inflation from the seller side, wholesale goods, raw materials, yada yada. CPI came in at 4.2 year over year, highest since April 2023. There's your chart. PPI came in at 6.5% year over year, highest since the end of 2022. Here's your poly market, 21% chance inflation hits 5% in 2026. And then an adjacent poly market chances of the Fed hiking this year at 49%. It was under 10% before the Iran war started. By the way, European Central Bank just raised rates a quarter point on Thursday. This was their first rate hike since September 2023. What do we take from this? Friedberg, it's all related to the Iran war. Yeah. That's the David Friedberg (01:06:52): There's definitely an energy blip from Iran war that drove the core index up. But there's also the macro point, which is government spending out of control, inflation out of control. And, fundamentally, as things unravel, you have rising rates. So I think we should kind of expect, especially with the Kevin Walsh Fed, I think we could see north of five and a half, 6% overnight rates. It's not unforeseeable. So this is just the nature of our monetary policy and our fiscal policy with our congressional, members that vote all of our future earnings away into bull But here Jason Calacanis (01:07:31): we are. And and and to far worse that nobody expected. Chamath, your thoughts, and then I'll wrap up with you. Chamath Palihapitiya (01:07:37): That was the most passive aggressive take I've heard in a while from you. Jason Calacanis (01:07:40): He's a little upset about it. Yes. Clearly, he's a little bit upset it. It's David Friedberg (01:07:43): just so stupid to watch. Chamath Palihapitiya (01:07:45): Can you tell us how you really feel? What David Friedberg (01:07:46): how do feel? Like, honestly, like, what else is there to say? I've said it, like, a 100 times. It's just idiotic. The the core problem with wealth inequality in this country, the core problem with inflation in this country, the core problem, all of it roots back to excess government spending. End of story. Of Jason Calacanis (01:08:03): this full stop. David Friedberg (01:08:04): We're all talking about machinations at the edge of the network. The core of the network is overspending by the government because in order to get elected, you need someone to give you something more than you have today. That's how people get elected. And here we are two hundred fifty years later. I don't know if there's the will or the way to get out of it, but one of the manifestations of it will be in this late stage, higher rates and as a response to inflation, and here we are. You Jason Calacanis (01:08:27): know? Alright. Shumak, what's your what's your take on this? Is it transient as we have had other presidents say? Is it is there a off ramp for the Iran war? I don't know if this is above all of our pay grades, but this does seem to be a challenging moment happening right before the midterms. And consumers expected that their cost of living would go down and that they would benefit from this golden age, and it hasn't happened yet. Chamath Palihapitiya (01:08:57): Well, look, it's concerning. I don't think that I expected the print to be this hot. Now what's keeping things in line? There's still a chance that we're not gonna see CPI go absolutely crazy. And part of that is because China has been smoothing the energy consumption globally worldwide, and so we've kind of kept a damper on $200 a barrel oil. In fact, we're sub a 100. At the same time, I think it's pulled forward a lot of more practical sources of energy production, not just in The United States, but abroad. Specifically, what I mean is solar just because it's simple, it's passive, and you don't David Friedberg (01:09:38): need you don't need a lot Chamath Palihapitiya (01:09:39): of permitting, and you don't need clean air permits and the like. So all of these things have been able to keep a lid on it. If China somehow runs out of reserves and they need to go back into the spot market to buy an extra 3,000,000 barrels a day, there's a very big risk that oil gets into the well past the 100 and maybe between a hundred and fifty and two hundred a barrel. That has a lot of downstream problems with respect to CPI. Not even because US energy supply, but really because the inputs that oil feeds all around the world that then get absorbed by the cost that people pay for everyday things could go up. So I think the PPI number should be an alarm that we use to off ramp this around situation sooner rather than later. I just unless, again, because we don't know what happened in China because none of us were there. Unless there's an understanding that the president has with Xi about how much actual supply and slack is in the Chinese system. And that may allow him to take a much longer road to get a conclusive and decisive win in Iran. But I I don't Jason Calacanis (01:10:49): There was supposed to be some tangible known resolutions with this China trip. We haven't heard them explicitly stated yet. What's your take on, this Sachs, the inflation print? And is there like a a golden bridge to to end this war in Iran? David Sacks (01:11:08): Jacob, the problem is when you ask me that question, people assume that I have some sort of inside information. And I don't. Look, the PPI print is what it is. I largely agree with what Chamaz said. The only thing I would add is that it was largely in line with expectations. That's why the market is actually up today. Normally, there's a surprise print and inflation is high, then the market is down because the market starts pricing in the implication of higher interest rates. It's not doing that today. So it's in line with expectations, but I largely agree with what Chamaz said. Jason Calacanis (01:11:40): Yeah. Alright. Well, listen, we gotta get to other elections. You know, my take on it is just huge colossal era starting this Iran war, and hopefully, we can get out of it. The downstream effects of this are just disastrous. I'm hoping there's a quick resolution or some way to get out of it before it goes to, you know, a year or two or three, we can't be in it forevermore, obviously. David Sacks (01:12:02): NASDAQ up two and a half percent today, that normally doesn't happen when there's a hot print because, again, like tech stocks are the most susceptible to high interest rates. So the market at this point seems to be pricing in Jason Calacanis (01:12:15): A resolution. David Sacks (01:12:16): But we'll see. We'll see. Jason Calacanis (01:12:17): We'll see. Yeah. Mean, it's just this is a everybody knows Iran is a quagmire and really was was a huge mistake. Alright. Let's talk about the hand wringing around vote counts in the LA mayoral primary. Instead of me reading all these details, just, Freiburg, I know you're high. I think David Sacks (01:12:39): we know about it. Yeah. David Friedberg (01:12:40): I think if you're Jason Calacanis (01:12:41): on x, it's essentially your entire feed. Freiberg, what's your take? Is the election system in Los Angeles, specifically in California corrupt? And is this election been stolen from Spencer Pratt? Or is it just David Friedberg (01:12:59): There is no election. There was no election. There is no election. Jason Calacanis (01:13:03): Okay. So there is no spoon. David Friedberg (01:13:06): Your rights to have an election are gone. You are a citizen of those who tell you who your overseers are. You are no longer allowed to vote Jason Calacanis (01:13:20): Not allowed to vote. David Friedberg (01:13:20): For your elected representatives. They are now appointed representatives. So enjoy the point that have been made for go. Appointed by those who have constructed the matrix. Jason Calacanis (01:13:32): Got it. Now we understand the background. There is no spoon. Agent David Friedberg (01:13:36): Smith and all the agent Smiths are in charge. So here's some statistics for you. In person voting, the day of the election in Los Angeles County for mayor. Spencer Pratt, 35%. Karen Bass, 29%. Nithya Raman, 26%. Mail in ballots received before election day, 38% for Bass. 28% for Pratt. 20% for Raman. And then all these ballots that arrive after election day, 37% for Raman, 35% for Bass, 19% for Pratt. So Pratt's post election mail in ballots declined by one third. So statistically, the population of people that send in their ballots late reduced for Pratt by a third, increased for Nipia Raman by 80%, and Karen Bass 10% less. If you just look at the mail in ballots before and after election day as a comparison. I don't know if there's a sociopolitical way that you can assess those statistics and assume that these are individuals casting their individual vote for who they think should be mayor of LA. And, Nick, if you'll just pull up the map, which I think is worth taking a look at. Basically, the concentration of incremental votes that Nithya Raman got came around the Skid Row area in Los Angeles. And, look, I'm not an election denier. I'm not someone who's historically believed the idea that elections are fraud and people have stolen votes. But when you look at the basic statistics of what happened in person, mail in before, mail in after election day, it becomes a real statistical quagmire on how did this sort of a sociopolitical shift happen in such a way that it did. Now there was a report published, Nick, if you could pull this up, by the US House of Representatives Committee on House Administration. This was published in May 2020, And they highlighted the twenty eighteen California midterm elections and the challenges they saw arise in that midterm elections because of some of the legislative changes that were made. First California Assembly Bill 1921 legalized the practice of unlimited ballot harvesting in the state. This was passed around 2018, around the midterms. What that means is that any individual in the state of California has the right to go and collect ballots from any other individuals regardless of relationship, fill them out and send them in. California two years later, eighteen months later, also passed a law that made it permanent that every person registered in the state of California would get a ballot. David Friedberg (01:16:12): So tens of millions of ballots then get mailed out. Then there was another series of laws that were passed that said anyone can register to vote. You don't need to prove your citizenship. You can use a gym membership card as an example. So anyone can register to vote. There is no proof of ID when you get a ballot. There is no demonstration that the person who fills out the ballot has anything to do with the individual who's supposed to be voting that ballot, and it is legal for an individual to go out and collect hundreds or thousands of ballots, ship them in, and they will all qualify in these kind of mail in ballot voting processes. So there is nothing illegal or fraudulent going on. In fact, the system is operating exactly as intended. It has been set up and structured in a way that with the right construct, you can get an individual appointed, not elected, but appointed to a particular role in government under a quote free election in California. This is a foundational destruction of our rights to vote for people in a free democracy. I feel it's been eroded slowly over time to such an extent now, and I'm not some crazy MAGA mother or whatever people wanna classify me as for pointing this out, but you can go down this list. They are all written out in this document. Every one of these laws that were passed in California over time that in aggregate create the environment and the construction for elections to become appointments and no longer free democratic elections where the principle, very importantly, the principle should be one individual, one vote. And if you opt to not vote, your vote should not be counted. So I think that there's no fraud. I don't think Jason Calacanis (01:17:49): there's anything illegal. Sounds like you believe there's massive fraud. David Friedberg (01:17:51): Yeah. I think this is not fraud. This is this is the way the law can set up. Chamath Palihapitiya (01:17:55): It's not fraud. David Friedberg (01:17:55): It's manipulative. The way the law is set up. Jason Calacanis (01:17:57): Okay. Sachs, you say, David Friedberg (01:17:58): of course, fraud. Appointment. Okay. Yeah. Jason Calacanis (01:18:01): It sounds to me like you're describing fraud, but you're saying the system allows fraud. Fraud is breaking the law. Chamath Palihapitiya (01:18:07): Fraud is breaking the law. The law allows them to do it. Jason Calacanis (01:18:09): If you pay people on Skid Row, that's not legal. David Friedberg (01:18:12): That is illegal. But you are allowed to go out and get anyone to register. You're allowed to go out and collect all the ballots, and the people that are doing it, as long as you're not getting paid per ballot, you're legally allowed to do it. Let me pause for one second. When you look at any one of these laws in isolation, you can understand that there is some altruistic intention or there can be framed to be an altruistic intention behind it. Increase voter activity, give everyone the right to vote, give more people access, more channels to vote, etcetera, etcetera. And you can rationalize away how every one of these laws makes it easier and adds lubrication to the system. And now we've got a, quote, more accessible democracy for everyone. But the truth is that there is a concept in insurance called adverse selection, which is if there is a moment to exploit something, the criminals will exploit it to the extent that it will become asymmetric. The criminals or the or the do badders, not the do gooders, will find a way to take advantage of a hole in a system just like hackers do to break into a network. And that's where you believe Raman did tell you how it Spencer Pratt did. This set of mechanisms, this set of construction has allowed for a system that now has evolved into an appointment system. Jason Calacanis (01:19:24): Raman worked the system better than Spencer Pratt. David Sacks (01:19:28): She had a better cheating operation, obviously. You could see it in the chart. The you just look at the number of votes. Jason Calacanis (01:19:34): Okay. Define cheating here, just so we're clear. David Sacks (01:19:37): How does it happen where Bass stays flat and then Raman and Pratt just switch places? So on election day, he's the clear number two, and then they keep counting for a week. They don't even know how many ballots they're supposed to have. I mean, none of this stuff is locked down. Okay. Let me explain how the cheating works. And to Friedberg's point, it may or may not be legal. So I, you know, I don't wanna get sidetracked by whether the fraud is legal or illegal, but I think we all know it's crooked. And here's how it works. Jason Calacanis (01:20:05): First of all Yeah. Explain what's David Sacks (01:20:07): crooked here. Explain it to you. David Friedberg (01:20:08): In detail. David Sacks (01:20:09): To you. Yeah. And if I misstate a fact, then let me know. So first of all, California sends out ballots to every registered voters. It's something like 23, 24,000,000 people. Only nine and a half million people vote. So what happens to the other 14,000,000 ballots? I have a friend who lives in LA. He manages apartment buildings. He says that the ballots just pile up, you know, at the mailboxes Yes. That everybody has in the buildings. There's, like, loose ballots everywhere. They're sent to people who don't even live there anymore. He, like, recognizes that the names there are people who haven't lived there in years. So the voter rolls are dirty. They haven't been cleaned up in years. Okay? Then you have the issue that there's no voter ID on election day. There's no voter ID to even get registered. When you sign your ballot, they run it through a machine. As long as the signature matches 40%, I don't even know what 40% means. It's like less than half accurate. The machine says it's fine. Okay? And then it doesn't even check the signature of the voter if you have a supposed witness. So the voter can just put like a little x on their signature as long as the witness says and they sign. But there's no registration of witnesses. Anybody can be a witness. There's no database of witnesses. And so the witnesses puts a squiggle. So what is to stop the so called ballot harvester from going, filling out these ballots, putting a little x on the voter, putting a little squiggle on on the the witness, and then dumping these ballots. There's no chain of custody. Jason Calacanis (01:21:43): So the risk would be they would be arrested David Sacks (01:21:46): And then gun Gavin violence. Jason Calacanis (01:21:47): Right? Yeah. David Sacks (01:21:47): Well, what is their expectation of getting caught? Gavin Newsom just signed a law making it virtually impossible to audit any of this stuff. So now even if they thought maybe they could get caught, let's just take a look at all the other types of fraud happening in California right now that we know about. We know that there's billions of dollars in fraud in California for things like Medicaid fraud, unemployment fraud, EBT fraud, hospice fraud, fraud related to the homeless industrial complex, and on and on. That's all been proven. Okay? Is it really so hard to believe that some of the same groups, the same interest groups, the same NGOs would be willing to exploit these loopholes in the dirty voter rolls, in the millions of ballots that go to incorrect or nonexistent addresses, the nonexistent chain of custody, the nonexistent signature verification, the no ID, not only to vote but to register, counting ballots without postmarks if received seven days later, registering thousands of ballots from homeless shelters that don't even have any beds. These are all known things. So when you say that there's no fraud, it's like, come on, there's loopholes, and all you gotta do is look at the results and see that there's something crooked going on here. Jason Calacanis (01:23:04): Okay. So you're in the camp that there is fraud going on because where there's David Sacks (01:23:07): smoke It being may be legalized, but it's fraud. Jason Calacanis (01:23:12): Okay. So you believe there's fraud? David Sacks (01:23:14): Look. When you start mailing out millions of ballots to people who don't even vote, and then you have no audit requirements, no chain of custody, no punishments, no penalties, no investigations, and there's a huge incentive to Jason Calacanis (01:23:25): make investigations, both by attorney generals David Sacks (01:23:28): In California? By who? Jason Calacanis (01:23:31): I'll I'll I'll pull up the history of California. I will say after every election, there are tons of civil lawsuits filed. Like, obviously, Trump filed 60 of 60 when David Sacks (01:23:40): Not in California. Jason Calacanis (01:23:42): I don't know David Sacks (01:23:42): if he did just made it impossible to do that kinda audit. He just Jason Calacanis (01:23:45): said I to the think that's because he was beaten so badly in a democratic state. There was no reason to, but I don't know why he didn't file in California. But he filed 60 of these, and everybody kinda does that. They file these constantly, and attorney generals can. So in this case, Chamath, if there's so much smoke, if this statistic seems so improbable and there was the Nick Shirley video of going to Skid Row and this possibility that they were paying junkies and people who were high to vote, this would be easily catchable actually. This would take a conspiracy for thousands and thousands of votes to have been swung, and that's what we're saying here. We're saying upwards of 10,000 votes were swung, but certainly 5,000. Chamath Palihapitiya (01:24:27): You would Jason Calacanis (01:24:27): need a conspiracy of hundreds of people or at least dozens to do that. Chamath Palihapitiya (01:24:31): Good luck going to Skid Row and getting some meth addict to go on the record. Jason Calacanis (01:24:36): I think they actually got somebody to go on the record. Actually, that's David Friedberg (01:24:38): a that's the There's fact videos a of this. Yes. Jason Calacanis (01:24:40): Yeah. Yeah. No. That that's the crazy part about it is they, are saying Skid Row people got paid 2 or $3 and that somebody was found guilty of this. Brenda Lee Brown Armstrong, she pled guilty in 2026 of paying David Sacks (01:24:54): people designed to allow fraud. It's this it's designed. Chamath Palihapitiya (01:24:59): It is designed. Is 40 why Jason Calacanis (01:25:01): 3,000 votes Chamath Palihapitiya (01:25:01): to what? We live in a autocracy in California where one political machine has shaped the laws so inexorably that whether it's a mayor or it's a state legislator or it's a state senator or it's the governor, it's a one way door. There is only one party that can win. And we are slowly seeing that that party increasingly does not have the ability to govern a state this dynamic and this complicated. They've changed the rules to make sure that that monopoly is enforced. We have all tacitly approved it by supporting or voting or not saying anything. And the end result has yet to be unveiled because it's gonna take another couple of decades for all of this rot to really destroy these places. The reality is the voters probably should be given a chance to have Spencer Pratt push back on what is the machine so that at a minimum, what they learn is that the machine wasn't working nearly anywhere close to the way it is intended. Instead, what will happen is two people that are in various shapes and forms pretty deeply unqualified and very similar now essentially get to give you not much of a choice at all. So I think the sad thing is Friedberg is right and Saxe is right. Friedberg is right. The laws have been shaped this way to make legal what would otherwise be an illegality. And Sacks is right, which is that any rational person should look at these laws and say, this is fraudulent. The unfortunate situation is unless there's some cataclysmic decision in California, this is what we're stuck with. It is time to vote all of these people out. David Friedberg (01:27:02): You can't. You can't vote. What do you mean? How are you gonna do it? Chamath Palihapitiya (01:27:06): Anyone can register. Pratt can file. Spencer Pratt can do Jason Calacanis (01:27:11): all kinds of lawsuits here. Chamath Palihapitiya (01:27:12): Can I answer can I answer Friedrich's question? Sure. There is one break the glass way. And I've talked to a few of these guys about what that is. How do you change the system? You must get somebody at the absolute top of the ticket elected. That person is Steve Hilton. And if that happens, there is one thing that Steve Hilton can do to start to completely change the way that the state is run, which is instantly on day one declare a state of emergency. If you pull on this thread, what you will find, there are lots of things you can do to clean up how California works under a state of emergency. I'll leave it at that. Jason Calacanis (01:27:56): Yeah. There's some common sense here. We shouldn't send ballots out to everybody. That made sense maybe during COVID. And if you can't be bothered to have ID, then maybe you shouldn't vote. And I don't think that there has been an election, a major election that has been swung by election fraud. The Heritage Foundation has spent many, many tens of millions of dollars on this, I understand. And they have a really great, project that tracks this. People file lawsuits like Trump did, like Al Gore did. Everybody's always filing lawsuits over this. It's never enough to swing an election, but there's definitely on the margins David Sacks (01:28:37): Kennedy versus Nixon, bro. Jason Calacanis (01:28:38): Hold on. Let me finish. David Sacks (01:28:39): The mob got Kennedy elected versus Nixon. Jason Calacanis (01:28:41): I'm talking in modern history. Yeah. In modern David Sacks (01:28:43): famous. That's pretty famous. Jason Calacanis (01:28:45): Okay. We well, we can get into if that's true or not as well. The appearance of imprisonment. David Sacks (01:28:52): History. Lyndon Johnson only got elected to the senate. He got a start in politics through ballot fraud. Jason Calacanis (01:28:57): We absolutely should have voter ID. We should stop sending everybody one of these because the appearance of impropriety is the problem here. Both sides, crazy new flash, news flash everybody, both sides cheat, both sides bend the rules. One side does it by limiting access, the other does it by providing too much access. All these politicians, overwhelming majority of them are unethical, and all they care about is getting elected, and they have tons of people working for them in both parties to massage these, election results. And if you get caught, it is a serious penalty. There has not been in modern history major elections. Go ahead and go to the Heritage Foundation. They find all the nooks and David Friedberg (01:29:36): crannies the word fraud, like, as if it's a thing, but it's not. I'll tell you who's at fraud. No. Chamath Palihapitiya (01:29:40): There's fraud. Jason Calacanis (01:29:41): At the end the day, hold on hold There is fraud. There are people have been caught doing fraudulent things. David Friedberg (01:29:46): The one group that is fundamentally to blame is congress. We have an opportunity. There have been opportunities to pass laws that will make it illegal for people to vote if they are not citizens, if they are not properly registered, and if they don't show up with ID. That is a very simple solve to this democratic electoral process. We can't have a situation where someone is legally allowed to go out and collect a 100 ballots that they find sitting in the lobby of an apartment building or for people to register to vote with a gym membership card when fundamentally the federal government already knows if you're not paying your taxes, you're required to have a driver's license to drive a car. You have to have ID. You have to be registered in the system to do nearly anything and everything in this country as it is. So to exclude that very simple requirement from the most foundational obligation that we all have as citizens of this country is inherently wrong, And it needs to be addressed by Congress. And if Congress fixes it and there are federal laws that create systems that ensure that elections are all about one person getting one vote and they're legally allowed to vote, then this doesn't become an issue. Short of this, I worry where this goes because over time, the fewer people actually believe that elections are real. And I hate being on here sounding like I'm an election fear mongering guy who's telling people that elections aren't real. But the longer this goes on, the more difficult it will be for people to actually have faith in the system that we're all operating within. And that's when things get ugly, and it needs to be fixed. Jason Calacanis (01:31:19): Yeah. I'm strongly agreeing. If you can't be bothered to get a driver's license or a passport, maybe you don't need to vote. Yeah. David Friedberg (01:31:27): Congress can fix it, and they should. Jason Calacanis (01:31:30): Yeah. And there's by the way, there's a ballot measure in California. If people in California want this, they can just vote for the ballot measure. David Sacks (01:31:37): You mean the voter ID ballot measure? Jason Calacanis (01:31:39): Yeah. David Sacks (01:31:39): Yeah. That's very important, actually. Look. If that fails, it's kind of our last chance to save anything. Jason Calacanis (01:31:45): For California's last chance. Yeah. Yeah. And you do sound like an your entire speech, David, was you sound like an election denier. David Sacks (01:31:52): I don't care what you label it. Look. The the the Democratic Party as a whole were election deniers about Trump winning in 2016. They concocted the whole Russiagate hoax to basically try and discredit his election. David Friedberg (01:32:03): When you look at the the difference between walk in and mail in ballots, and I've seen everyone try to argue why that's so different, it doesn't compute for me. That's it. I'm not, like, trying to make up a fact. This is the fact. Look at this fact on the on the on the screen you're looking at right now. This is the difference in the data. This data tells me that something is wrong. That's it. Obviously. It's statistically impossible. Fearmonger because I don't like who got elected. I don't give a what goes on in LA. In fact, I think it's better for LA if they deal with the socialist mayor for a couple years so they come out the other side realizing they shouldn't embrace socialist principles. I think it's great for the country, actually. I think it's great for New York. I think it's great for Seattle. I think it's great for wherever Minnesota, wherever people want to elect socialists in this country. Let's run into it. I'm all about jumping through the socialist well. So we jump out the other side like the Latin American countries are doing now when everyone wakes up and realize how up socialism is because it denies everyone the opportunity for economic mobility. It denies everyone their individual liberties that this country was founded on. Socialism is wrong. It's broken. It doesn't work. And if you all wanna go through that lesson, do it. Go for it. Let's do it. Let them get elected. But the numbers on that election data show me that that's not what the people wanted, that it's not very clear or evident to me that that's what people voted for. And that's where I'm like, my god, the system itself has become a system of appointment, not a system of election. And I get fired up about that personally. Jason Calacanis (01:33:24): Sach, you wanna add anything once we wrap here on this? David Sacks (01:33:26): Yeah. The party told you to reject the evidence of your eyes and ears. It was their final, most essential command. This is obvious. Just look at the charts. Look at the data. We know something crooked happened. It's statistically impossible. The only thing we don't know is whether it was illegal fraud or legal fraud, meaning they've created so many loopholes and so much corruption in the law that what they did is possibly legal. It is still corrupt. It is still crooked. It is ridiculous. Everyone can see it. Do not deny the evidence of your eyes and ears. Even if they call you an election denier, I personally don't care. I deny it. Spencer Pratt should be in the runoff. I deny that Rahman won legitimately. Jason Calacanis (01:34:09): Okay. Statistics are the statistics, and they would scream that you should have the attorney general of California and the federal attorney general look into it. And if they catch people doing this stuff and they have caught one person and Nick Shirley went down there and you see people on Skid Row, You know? Listen. Homeless people should have the right to vote theoretically. David Sacks (01:34:29): Why did Newsom just sign a law making audits like that even harder? Jason Calacanis (01:34:32): Yeah. I I'm not defending Newsom here. I'm saying, where's the attorney general? If there is, in fact, fraud, Trump has the ability with his hands, elected attorney generals to go after this. He controls that part of, you know, our our democracy. He should file, and they should go figure out what happened statistically. So Trump, president Trump, thank you, president Trump. Go do it. Go do it. You got this attorney general chasing down everybody else. Go to this election. Use your powers, audit it, and find them. Like, where's president Trump? David Sacks (01:35:04): You didn't hear my point that the the state law just made it harder for the federal government to come in and audit the voter rolls. Jason Calacanis (01:35:11): So Yeah. He can still do it. David Sacks (01:35:12): I'm sure they will do it. I'm sure they'll do it if they can. Jason Calacanis (01:35:15): Yeah. I mean, trust me. Trump does what he wants. If we've learned anything, he will do what he wants, and he's not doing this now. David Sacks (01:35:22): What I find amazing is that the media, instead of asking tough questions like, how did this happen? How could the vote swing so wildly in ballots that were only found Hold on. After election day, the media, instead of trying to demand answers and demand accountability, is trying to cover up and say nothing wrong happened here. It's unbelievable. It's outrageous. Jason Calacanis (01:35:45): What is the best theory, steel man? And what's the best theory of why the media David Friedberg (01:35:49): is discrepancy? Mean, we're sitting here talking about it. Jason Calacanis (01:35:51): What's the discrepancy? Anybody have a steel man of why this discrepancy could have happened? That's legitimate. Anybody? Chamath Palihapitiya (01:35:58): The media is hanging on to a snapshot of the past where people actually cared what they said. And every time that they can actually reestablish trust, they kind of don't do it because the people that they want to curry favor with are willing to play along. So I think what happens is the media is like, well, I have two choices. I can actually say that Spencer Pratt should have won or could have won or investigate why he didn't win, but then I'm kind of tacitly supporting Trump. And hold on a second. I'm supposed to hate Trump. So no. Yeah. You know, this is completely normal. Nothing to see here. Everybody moves on. Hoping that then they get ingratiated into the machine. Like, they're gonna get run over and used like everybody else does too. So that's what's happened. David Friedberg (01:36:50): Yeah. Your point is so spot on, Chamop, that, like, if it's so polarized, meaning that there's two polls, that if you do question, it's almost like you were being put in the Trump pro Trump camp just like the word MAGA is thrown around like, oh, you're a MAGA guy because you're questioning election integrity. It has nothing to do with MAGA. It's just simple conversation about a particular topic. But if it's diametric to the other camp, you're you know, you must be in that bad camp. And so then they don't wanna be put in that camp. It's so true. Chamath Palihapitiya (01:37:19): For mathematical and statistical literacy. And what happened here is mathematically and statistically. Jason Calacanis (01:37:24): Nobody has any Impossible. Steel man or a concept of how this could have happened. Chamath Palihapitiya (01:37:29): I can tell you the statistical odds that this would have happened, and it's one in a trillion. Jason Calacanis (01:37:34): Okay. What if So Chamath Palihapitiya (01:37:35): are you telling me the one in a trillion shot hit? Jason Calacanis (01:37:38): I I'm asking if there is any I'm not. Chamath Palihapitiya (01:37:41): Just just this one time? Jason Calacanis (01:37:42): I'm not. I'm asking if there's anybody who steelmans this in any way. I'm asking if they'll be of David Sacks (01:37:48): Why is it so psychologically important for you to cling to the idea? Jason Calacanis (01:37:53): It's not. David Sacks (01:37:53): That California elections that California elections are completely corruption free after all the things they've clearly done to corrupt them. Answer to your question is ID. You admit. There's like it's chock full of loopholes. Jason Calacanis (01:38:06): You asked me why am I holding onto it. I'm not holding onto it. For the purpose of discussion and having an intellectually honest discussion, I am asking the three of you if there you've heard or if you have any theory, just for the rigorousness of the discussion. This isn't my position. David Sacks (01:38:21): Where are all the democracy protectors in the media now? They also said that they were guardian they were the guardians of democracy. They're gonna protect democracy. Where are they to ask questions? Jason Calacanis (01:38:30): Theory that I can think of I'll steal a minute myself. I because I I think you do need to be rigorous I'll tell this discussion. But you David Friedberg (01:38:36): go ahead first. Yeah. Jason Calacanis (01:38:37): The the only thing I can think of is her ground game is more sophisticated because they've been at it longer than Spencer Pratt, and he didn't have a ground game that took this in since he's in nontraditional first time candidate. That's the only thing I can Chamath Palihapitiya (01:38:50): think of. Is sophisticated a coded word for he was a bribing Skid Row homeless junkie? Jason Calacanis (01:38:55): He just has it he doesn't have an election machine to collect ballots, and collecting ballots is legal. David Sacks (01:38:59): So she Jason Calacanis (01:39:00): asked the that's the question. David Sacks (01:39:01): She had a better cheating operation, obviously. We're saying the same thing. We're not actually saying anything different. David Friedberg (01:39:07): The Twitter commentary was that people were waiting because there's so many people that are so against Spencer Pratt, but they wanted to be sure that they voted for the right candidate, whether it's Raman or Bass. And so the people that held their ballots the longest saw that polling data that Bass was gonna win. That that's why they all voted for Raman last minute was to try and promote her to make sure Jason Calacanis (01:39:33): that shift because of the you could have two Democrats at the top of the ticket. David Friedberg (01:39:36): That's right. And they didn't want Spencer Pratt to have a shot as a general. And that by the way, you know, I mean, if you saw my interview with Spencer Pratt Yeah. He said Rahman registered one hour before the deadline, and she's friends with Bass. And that the whole point was to keep him from actually making it onto the general ballot. Jason Calacanis (01:39:51): Interesting. David Friedberg (01:39:52): So that some of the coordination that people were making in their minds was like, we gotta make sure we vote for the two Democrats, and then they'll figure out, hey. Chamath Palihapitiya (01:39:58): Is it Bass or Robin that strategy. Jason Calacanis (01:39:59): Let's just box him out. Yeah. Got it. David Friedberg (01:40:02): Which is, like, why they all waited till the last minute to vote it for for to vote Jason Calacanis (01:40:05): for Trump. How do you coordinate something like that? That that that's always the question I have with these, like, David Friedberg (01:40:09): people all brilliant geniuses. It's it's hundreds of thousands of brilliant geniuses in Sid Row that David Sacks (01:40:14): There's a chat David Friedberg (01:40:14): group. Out. Yeah. Chamath Palihapitiya (01:40:15): If there's a chat group I mean, it's not it's not that complicated. David Sacks (01:40:18): Bro, the ballad harvesters did it. What Friedberg said just happened is just that the ballot harvesters did it, not the actual voters, obviously. Jason Calacanis (01:40:26): And ballad harvesting is legal, but it's sketchy, and maybe they and if there are ballot harvesters, I think that Trump and the DOJ can catch David Sacks (01:40:35): these How the David Friedberg (01:40:36): is it legal that someone can go out and collect other people's ballots and fill them out and send them in? It's the craziest to me. Jason Calacanis (01:40:43): No evidence of fraud right now. Statistics don't look good. Donald j Trump, you control the Department of Justice. Go investigate it. Chamath Palihapitiya (01:40:50): Okay. I love you guys, but I'm hungry. I gotta go. Jason Calacanis (01:40:52): This has been an amazing episode of the all in pockets. Bye bye. Chamath Palihapitiya (01:40:58): Love you, boys. Bye bye. We David Sacks (01:41:09): open sourced it to the fans, and they've just gone crazy with it. David Friedberg (01:41:26): We Jason Calacanis (01:41:32): should all just get a room and just have one big huge orgy because David Sacks (01:41:35): they're all just useless. Jason Calacanis (01:41:36): It's like this, like, sexual tension that they just need to release somehow.