DeepSeek Panic, US vs China, OpenAI $40B?, and Doge Delivers with Travis Kalanick and David Sacks

That's more of like a today analogy. So you go, 100 years, of course, that's the thing. Nobody's going to be making food. What about 20? What about 10? And so the company is real estate, software, and robotics that's all about the future of food. And if you can get the quality there and you can get that cost down to start approaching the cost of going to the grocery store, you do to the kitchen what Uber did to the car. And that's the thing. And it's like a grind. It's like a lot, you know, bits and atoms in the Uber world. This is like five times more atoms per bit. This is like heavy duty industrial stuff.

probably more along the lines of where Elon goes in some of his companies. They're super interesting tech, but you've got to grind out those atoms. Do you see people actually cooking in the future or does it become a centralized service? And is it optimized to people's health? And what do you think? the implications to the food supply are if your vision holds how do you think about all those things look uh people will cook in the future as a hobby i sort of i make a joke at the office i'm like i like horses i love horses but i don't ride a horse to work and it's gonna be a little bit like that whereas you can cook it's it's a soulful thing to do it's just very human but you know it's late, you know, mom gets home late from the office, needs to get the kids, you know, a nutritious meal. She doesn't have to cook it now and she doesn't, she won't have to cook it and she won't have to go to McDonald's either. It will be high quality and convenient and low cost all at the same time. And yes, dietary preference, everything, because it'll be hyper personalized. Like the way the internet is in content, plus, plus, plus in terms of your specific preferences for what you want i mean you've got these computers rocking oh these

robots rocking i think in philly somewhere uh in the lab where they're making bowls yeah i mean we're out of the lab at this point we have our machine so we have a machine called a bowl builder

like food delivery was very early we built these itza restaurants that were smaller footprint we 800 square foot restaurant that was doing 3 million a year in revenue. And it had a handful of people working in it, but we were putting about 800 people an hour during the lunch rush through that restaurant, ordering custom bowls. This was by one market, right? One market, exactly. And so- By the way, did you guys notice that JCal was plugging his product there in the background, even though it has absolutely nothing to do with what Travis was saying? Oh, welcome back to the show. Nothing's changed. Sax is here. No one else even noticed that. I just heard this voice from above. It was the czar of AI and crypto. I was like, wow.

That's all, sit back and listen. The czar is back. Saks, any anecdotes you want to share about life in DC? How exciting it's been in the administration the first week? It's been amazing. I mean, it's hard to believe it's only been a week, right? So you're in the White House or that building next to it? Do you have an office? You mean the treasury building? I don't know. Somebody was talking about there's a building next to it or something. thing i don't know i have an office in the old executive office building otherwise known as the eisenhower building and then i have a pass where i can just walk over to the west wing if i want to walk over to it there's kind of a whole white house complex behind the gates that the west wing's part of it and the eisenhower building and there's a couple other buildings in that complex it's really cool it is really neat to to show up for work at the white house just saying it's awesome it's like being in a movie or something or a tv show it is really cool you know it's awesome any interesting meetings you can talk about and i mean i know we are here today to talk about deep seek but any interesting meetings or anecdotes from just the vibes and walking

around what's the coffee like is there like a commissary you run into anybody interesting there is a commissary actually in the white house called the navy mess and i think they're just opening up for business now. That is one of the cooler things you could do is you can take people to lunch at the Navy Mass. Oh, look forward to it. J. Cal just invited himself. We'll see. I look forward to it. I look forward to taking Chamath and Freeburg there. I'll wear my MAGA hat. All right. Well, let's get started. You're here because we have a very specific... He's here because the world is ending, Jason. The Western world is something okay the western world's ending and david sachs is going to save it but we had a little bit of a freak out the last week regarding this deep seek if you don't know that's a chinese ai startup they released a new language model it's called r1 and it's on par basically with some of the best models in production in the west like open ai's o1 model but they claim and listen you can trust claims coming out of China.

you know, for what it's worth. They claim to have done this all for $6 million on only 2,000 GPUs. For comparison, OpenAI spent reportedly $80, $100 million to train GPT-4, which you're all using now. And Sam claims they're going to spend a billion dollars training GPT-5. And so that's about 7% of the cost of GPT-4. Obviously, there are export restrictions on NVIDIA H100s to China. So there's a big debate as to if they actually have H1s or not. And Monday was a bloodbath in the stock market. NVIDIA had the worst day in the history of the stock market in terms of total dollar amount of market cap lost.

It was down 17%, which is $600 billion. TSMC was down. ARM was down. Broadcom was down. So I guess everybody's asking the question, how did they do this? Did they do it? And then there's a bunch of debate on whether they stole, which is kind of rich coming from OpenAI, which got caught red-handed stealing everybody else's content. And now they're crying foul that the Chinese stole or trained, did what's called distillation of their model in order to build theirs. Sachs, obviously, you are the czar of AI. I'm curious what your take on all this is. And thanks for coming. Well, I think one of the really cool things about this job is just that when something like this happens, I get to kind of talk to everyone and everyone wants to talk.

And I feel like I've talked to maybe not everyone and like all the top people in AI, but it feels like most of them. And there's definitely a lot of takes all over the map on DeepSeek, but I feel like I've started to put together a synthesis based on hearing from the top people in the field. It was a bit of a freak out. I mean, it's rare that a model release is going to be a global news story or cause a trillion dollars of market cap decline in one day. And so it is interesting to think about, like, why was this such a potent news story? And I think it's because there's two things about that company that are different.

One is that obviously it's a Chinese company rather than an American company. And so you have the whole China versus U.S. competition. And then the other is it's an open source company, or at least it open sourced the R1 model. And so you've kind of got the whole open source versus closed source debate. And if you take either one of those things out, it probably wouldn't have been such a big story. But I think the synthesis of these things got a lot of people's attention. A huge part of TikTok's audience, for example, is international. Some of them like the idea that the U.S. may not win the AI race, that the U.S. is kind of getting a comeuppance here.

And I think that fueled some of the early attention on TikTok. Similarly, there's a lot of people who are rooting for open source or they have animosity towards OpenAI. And so they were kind of rooting for this idea that, oh, there's this open source model it's going to give away what OpenAI has done at 1 20th the cost. So I think all of these things provided fuel for the story. Now, I think the question is, okay, well, what should we make of

It's hard to know what's fact and what's fiction. Everybody who's on the outside guessing has their own incentive, right? So if you're a semiconductor analyst that effectively is massively bullish NVIDIA, you want it to be true that it wasn't possible to train on $6 million. Obviously, if you're the person that makes an alternative that's that disruptive, you want it to be true that it was trained on $6 million. All of that, I think, is all speculation.

The thing that struck me was how different their approach was. And TK just mentioned this, but if you dig into not just the original white paper of DeepSeek, but they've also published some subsequent papers that have refined some of the details, I do think that this is a case, and Sachs, you can tell me if you disagree, but this is a case where necessity was the mother of invention. So I'll give you two examples where I just read these things and I was like, man, these guys are like really clever. The first is, as you said, let's put in a pin on whether they distilled O1, which we can talk about in a second. But at the end of the day, these guys were like, well, how am I going to do this reinforcement learning thing? They invented a totally different algorithm. There was the orthodoxy, this thing called PPO that everybody used. And they were like, no, we're going to use something else called, I think it's called GRPO or something. It uses a lot less computer memory and it's highly performant. So maybe they were constraint sacks, practically speaking, by some amount of compute that caused them to find this, which you may not have found if you had just a total surplus of compute availability.

And then the second thing that was crazy is everybody is used to building models and compiling through CUDA, which is NVIDIA's proprietary language, which I've said for a couple of times is their biggest moat, but it's also the biggest threat vector. for lock-in. And these guys worked totally around CUDA, and they did something called PTX, which goes right to the bare metal. And it's controllable, and it's effectively like writing assembly. Now, the only reason I'm bringing these up is we, meaning the West, with all the money that we've had, didn't come up with these ideas. And I think part of why we didn't come up is not that we're not smart enough to do it, but we weren't forced to because the constraints didn't exist. And so I just wonder how we make sure we learn this principle. Meaning when the AI company wakes up and rolls out of bed and some VC gives them $200 million, maybe that's not the right answer for a Series A or a seed. And maybe the right answer is $2 million so that they do these deep seek-like innovations.

Constraint makes for great art. What do you think, Freedberg, when you're looking at this? well i think it also enables a new class of investment opportunity given the low cost and the speed it really highlights that maybe the opportunity to create value doesn't really sit at that level in the value chain but further upstream apology made a comment on twitter today that was pretty funny or i think the rapper is about the right he's like turns out the rapper may be the moat, which is true. At the end of the day, if model performance continues to improve, get cheaper, and it's so competitive that it commoditizes much faster than anyone even thought, then the value is going to be created somewhere else in the value chain.

Maybe it's not the wrapper. Maybe it's with the user. And maybe, by the way, here's an important point. Maybe it's further in the economy. You know, when electricity production took off in the united states it's not like the companies are making a lot of money that are making all the electricity it's the rest of the economy that accrues a lot of the value well you're about to see a big test of this because if open ai raises 40 billion at 340 billion that just hit the wire the underwriting logic at 340 billion exactly what you just said freeberg it is the wrapper meaning chat gpt is the next killer app it's getting to a billion plus mal hundreds of millions of DAO. It's competing for consumer usage. That's the model. That's the model is like consumer usage. Which puts them on a collision course with Meta. It's the only company that could really impact that because the only company right now that has billions of eyeballs of DAUs per day. And by the way, Zuck said this in his earnings release. He's like, there's only going to be one company that brings AI to a billion plus people and it will be us.

some version of that quote in his earnings released yesterday. And then Microsoft showed weakness in their cloud. And then Microsoft's down 6% today. And, you know, I think it's a window for OpenAI to say, we're going to go up against meta. This is it. We're going to be the players. And everyone's kind of ignoring Google. What do you guys think is happening right now between OpenAI and Microsoft? Because if it's true that this distillation thing actually happened, well, there's only one place where you could have distilled the O1 model. but it's on Azure. So what the hell is going on over there?

Well, and there are one is supported on- Explain distillation real quick. Yeah, so when you have a big, large parameter model, the way that you get to a smaller, more usable model along the lines of what Sachs mentioned is through this process called distillation where the big model feeds the little model. So the little model is asking questions of the big model and you take the answers and you refine. And by the way, you can see this, Nick, I sent you a clip. you guys can see this. I mean, there's clearly distillation happening. Nick, can you show the clip of the DeepSeek run where it shows the China answer and then deletes it? What was Winston's job in 1984, right? And it sort of starts to go through this whole summary. And then the person says, are there any actual states that currently do that? Hold on, here it goes. It says North Korea, wait, it goes China, and then wait, watch this, boom.

So, the reason why this is happening is like you're seeing this chain of thought, you're seeing the several layers, and then it's catching it after the fact. So, we know that this is distilled from some other model. And my only point there, it's a little tongue-in-cheek, is right now, when you go and use OpenAI, you're using it sitting in an Azure instance somewhere, right? So this is Microsoft's cloud infrastructure that runs it. So it begs the question, it's not that it's O1's fault or OpenAI's fault that this distillation happened. And I'm not trying to assign blame, but typically if this were to happen, you'd look to your cloud provider and say, how are you letting this happen?

And I don't think anybody's had a good answer for that. Well, and the cloud provider is hosting R1 now. So they're literally undercutting ChatGPT and OpenAI at the same time. Just to clean that up. They're hosting their own copy of it, right? Because R1's been open source. When you say they, who are you referring to, Sachs? Microsoft. Yeah, Microsoft is hosting their version of R1, which means they are actively subverting their partner, OpenAI, and pushing people to a cheaper model. Well, whatever. I mean, look, Amazon's going to host their own version of R1. Grok has a version of R1. Yeah, we have one.

Cerebris just rolled out. It's open source now. Guys have a buddy who has R1 on his laptop, you know? Yeah, exactly. Yeah, but if it was stolen and the IP was stolen, as Sam is claiming, that would be like, you'd think he'd be able to call up Softe and say, hey, can you not put the stolen IP on your server and promote it to everybody at a lower cost? It just shows Microsoft has no loyalty to OpenAI. Yeah, but you'd think they would have loyalty. They have no loyalty. But guys, what it would take to distill a one brute force, it wouldn't be like, oh, geez, I can't believe it was distilled. It would be like such a massive number of calls against an API or against something that it wouldn't be unnoticed.

Well, they did actually came out and said they blocked some suspicious activity recently. Yeah, no, but they're always doing that. That's constant. You're always doing that. That's like, you know, the old school. Go ahead, Zach. Let me address the distillation point. So I mentioned this a few days ago on Fox News that I thought it was likely or possible that distillation had occurred. And there was some evidence for this. And it became like a news story. And I didn't even realize that saying that would be news because it's kind of an open secret in Silicon Valley. Everyone I talked to – They're doing some level of distillation.

Yeah. Because you need to test your model against theirs anyways. Yeah. And every single person I've talked to basically has agreed that there was some distillation here from OpenAI. Now, that doesn't mean it was the only thing going on here. I mean, to be sure, the DeepSeek team is very smart and there were some innovations, but also there was some distillation. And really, this wasn't even a fresh news story, I think, from the point of view of Silicon Valley, because a month ago, we had a press cycle in Silicon Valley when DeepSeek's V3 model came out, that DeepSeek V3 was self-identifying as ChatGPT.

When you would ask it, who are you? Like, what model are you? Five out of eight times, V3 would tell you that it was ChatGPT 4. and there's lots of videos and examples of this online that have been posted right the point is that we knew a month ago that v3 had been trained on a substantial amount of chat gpt output obviously because v3 was self-identifying as chat gpt and there's two ways that that could have happened so the let's call it innocent explanation is that deep seek had crawled the web and found lots of published output from chat gpt and then trained on that and that wouldn't be a violation of OpenAI's terms of service or their IP, or the other explanation would be that they used the API from OpenAI and basically, you know.

went to town yeah went to town and there's no way i think based on what we know to prove that one way or another but i know what most people think happened and at the end of the day open ai can probably figure it out and they they've indicated that they think there was some improper distillation here but yeah in the financial times it says open ai says it has found evidence that chinese artificial intelligence startup dc used the u.s company's proprietary models to train its own open source competitor right that's what i'm referring to so they say They've been very clear about this. By the way, you have to be sympathetic, I think, to OpenAI in this, because if you're building a startup, you're trying to raise money.

We've all gone through this cycle, guys, where it's like, there's momentum. We celebrate internally the momentum. That's what gets you the energy to push your team even further and harder. And then all of a sudden, it turns out that some portion of that, like Travis said it well, like there's probably a chart inside of OpenAI's offices where you're showing how many times these APIs are getting hit, right? how many times these endpoints are getting hit, it all looks positive. And then you realize that some portion of it was actually bad and trying to undercut your value. It's a hard pill to swallow.

And then you have to course correct very quickly. You have to lock down. This is one area where- Exactly. We have not talked about this. You have to lock these models down. Now you have to lock the endpoints down. Look, in the Biden administration, if this had happened, the first conversation would have been, we need to KYC the people that use these models. And it's like, what are you talking about? We don't KYC the cloud. If you're trying to use like an EC2 endpoint or an S3 bucket, you don't have to all of a sudden prove who you are. You just use a credit card and go. That's the whole point of why proliferation can happen so quickly.

But if we take the wrong takeaways from this period, there's going to be a bunch of people that'll clamor to lock these folks down and make innovation go much slower. I think that that would Here's the other side. And totally agree, Chamath, but here's the other side. You go through the white paper, you see what it is they did, what they innovated on, the science behind it, the thoroughness. And you're like, these guys are bad ass. It does not feel or sound like somebody who took something just when you get through it. It could be that OpenAI wrote the white paper for them, just putting it out there. But it's real innovative.

I agree with that. Real innovation, strong tech. You're like, this is legit. I agree with that. But in that paper, they're very easy about where the data is coming from. And they're fairly transparent about everything else they did, but they're not really clear about the data. And specifically, they say that to get from V3, which is the base model, to R1, which is the reasoning model, they had about 800,000 samples of reasoning. they were quite unclear about where those reasoning samples came from by the way it is remarkable that you can get from a base model to an r1 with just 800 000 samples but this is the problem like we meaning like the western ai community we've been trudging around on this path where we've been very we had a very orthodoxical approach the only way you can do reinforcement learning is through ppo okay but is that true and it turns out that if you're like a really smart team that has no other choice, you move away and you invent your way out of it. And so we have to get that example too. I think it's technically brilliant, some of the things they've done, but they also use constraint as a very much a feature, not a bug. And the Western AI economy has been the opposite so far. I think the best part of this is the fact that Sam Altman was

supposed to be doing open source. He made it a closed source company. He stole everybody's data. every got caught red-handed he's being sued by the new york times for all that and now the chinese have come and open-sourced all the stuff he stole and he's got a real competitor on the original mission of what opening i was supposed to do. So I have zero sympathy for him or the team over there. I'm glad that this is all going open source. It should have been open source and it's better for humanity. And the fact that the Chinese did it to Sam Waltman is come up for him stealing everybody else's content. That's my opinion. Okay, so you have it. But I don't have strong opinions on it. It's hilarious. Does nobody see the irony in this? He was supposed to be doing open source for the good of humanity.

Because, J. Cal, I will say the models are closed. You're right. There's the lawsuit with Scarlett Johansson for stealing her voice even when she said no. There's a real question. And people have asked New York Times. And then there's now the question about YouTube data being used to train the video models. So there's a lot of being on their heels a little bit. So I definitely see your point. Stealing. I think all the pressure right now, I think, is on Meta. Because I think Meta has to show up with the next iteration of Lama that beats and exceeds Gemini, that exceeds R1. And I think that that is going to be crucial for us to have a counterweight to whatever China is going to put out after this.

But I mean, Chimot, it's open source. Like, does it not kind of- So this is my point. Embrace and extend. Embrace and extend. Meta has to embrace and extend everything that these guys have shown. Meaning, like, Meta's buying tens of thousands of NVIDIA GPUs. Great. But what did this show? This shows that actually CUDA, high-level languages in general, I think we've all known that they suck, okay? And so we've all been going through it thinking that it's like the right thing to do. DeepSeek throws it out the window. They use something called PTX. What does Meta do is critical now to understand.

They need to embrace this stuff. And this is where I think, again, apologies to the invidiables, but it's going to create a more heterogeneous environment. And the reason is because there's too much money and risk on the line to go through a single point of failure. A chip, a high-level framework to get to that chip, that's nuts. So I think like that kind of like emperor has no clothes moment is upon us. Well, let me ask you another question. Let's assume that we start the world of AI today. So there's no legacy of the last three years.

with a little bit of what's been said here is like when AI gets cheap, you know, what's going to happen guys, there's going to be a lot more AI, right? I don't think, I think the price elasticity on this one is actually positive. So as the price goes down, the revenue usage, everything's going to go up. This is a history of tech forever. Since like Bill Gates said, I don't know what to do with more than 64 kilobytes of memory. Like, you know, the question is, did we- Cheap oil in the United States drove the industrial revolution, right? And like when we started discovering oil, suddenly we were able to build factories and make stuff that we never imagined possible. And so then you're like, okay, AI is like, you know, it's going to get cheap. It's going to be oil, but it's also going to be specialized for different tasks. Like you're going to start getting into nuances of like, what does the investor AI look like? What does the autonomous car AI look like? What does the Google search, I'm trying to figure some shit out AI look like? The lawyer, the accountant, the pilot.

So you could go vertical and siloed, siloed air quotes, but you understand what I'm saying? Yeah. So there's a thing called Jevons Paradox, which kind of speaks to this concept. Satya actually tweeted about it, which is the, it's an economic concept where as the cost of a particular use goes down, the aggregate demand for all consumption of that thing goes up. So the basic idea is that as the price of AI gets cheaper and cheaper, we're going to want to use more and more of it. So you might actually get more spending on it in the aggregate. That's right. Because more and more applications will become cost-efficient. Economically feasible.

Economically feasible, exactly. That is, I think, a powerful argument for why companies are going to want to continue to innovate on frontier models. You guys are taking a very strong point of view that open source is definitely going to win, that the leading model companies are all going to get commoditized, and therefore there'll be no return on capital and basically continue to innovate on the frontier. I'm not sure that's true. For one thing, the R1 model is basically comparable to 01, which OpenAI released four months ago and was training on internally, call it nine or 10 months ago. So OpenAI is on 03 now. Its frontier is ahead of where R1 is. Anthropic and Google, I think, have things in the work and even meta that may be ahead of where r1 is so i think r1 or deep seek's done a good job being a fast follower here it's not clear that this is the frontier and Those frontier model companies now, having seen what might have happened with distillation, have a pretty strong incentive to make sure that doesn't happen again.

And they're going to be taking countermeasures. I mean, there's a question of like how much you can do to stop it. But I think it's a little premature to conclude that there's no reward for being at the frontier. Anybody have any other questions for Saks before we drop him off to go back to serving the American people? Before we drop him off. One final point on the whole open source versus closed source. Look, I'm not going to take sides in that. But I think that it's a mistake to just view what happened here as, oh, it's just like plucky upstart that's like doing the community a huge service out of the goodness of its heart. You know, it's basically open sourcing.

Oh, they stole it. They stole it. It's the Chinese. Come on. You still have this huge geopolitical aspect to it, right? And DeepSeek is a Chinese company, and they're trying to catch up. And so if you're behind and you're trying to catch up, then open source is a strategy that actually really makes sense for you. And they're trying to basically undercut the leading American companies. And I don't think they did it with $6 million. I mean, they have massive resources behind them. So I think some of the pro DeepSeek vibes i think are they're a little bit naive you know in silicon valley it's like that's only the people who worked for sam previously and quit who feel that way i think there's a lot of like support for deep seek yeah it's looking valley because again people think that they're doing this huge service for the community and i think it's a little bit more self-interest in that than that it could be both right i mean there there is a theory that they're trying to undercut and neuter the lead and at the same time there's a bunch of people who believe in open source and nobody should control this and certainly not Sam Altman should be the person who controls it. So two things could be true at the same time. David, thank you so much for coming on. We appreciate

it. And thank you for all your hard work and service. Thank you for coming on your own podcast, David. We appreciate it. Thank you, David. I know that this is... And now we're going to talk about a bunch of other crazy stuff. You're a scholar and a gentleman, David. Yes. Thank you. All right. Thanks to David Sacks for coming in. And, you know, I guess let's open up the aperture here and talk a little bit about relations with china we're obviously in a bit of a cold war with them we have tariffs we have taiwan and then we have uh the sort of trade war going on here with uh exports of h100s where do we want to start gentlemen and you know travis you've got some a deep you're one of probably five american entrepreneurs who ran an at-scale business with Uber and the DD relationship in China, so you have a unique position of understanding business in this along with maybe Tim Cook and Elon are the only other two people who've really had an at-scale business there. Maybe Disney. They have Disneyland there. What's your take on the relationship and what's going on here geopolitically?

How's China going to operate differently than the US, Travis, from your experience, your point of view? Tell us a little bit about the culture and business ethics in China, particularly as it relates to ai okay so okay so look we i had this thing this is i'm going back

concept in DTLA? Well, look, okay. So we got a couple of things. So we have in every one of our facilities and we've got hundreds of them. We'll have lockers there. So the courier then waves their phone in front of a camera, the right locker pops open, they get the food from there and they go. The courier pickup is asynchronous from production of food. You don't have lines anymore. There's no more lines, which then speeds up delivery, shortens the amount of time, reduces how much money you spend on couriers. And we've got a whole other thing. This doesn't work. It probably wouldn't work in China because, well, for a lot of reasons, but let me explain what it is. It's called picnic, where if you are in an office building, you order food, you go to a website, you order whatever it is from 100 different restaurants. Those restaurants happen to be in my facilities. And there'll be one courier that goes to one of our facilities and picks up 50 orders at a time brings it to an office puts it there's a shelf on every floor you get notified when your food arrives and it arrives the same time time every

day and you just go to the shelf get it on your floor and dip it right back into your meeting saving people time at the office giving them selection on food especially in food deserts but even going like there's a sweet green right down there in my current in my office right now I could say 20 minutes by just using our own service versus doing that. And you get it at the same price because the courier economics, the courier is delivering 50 orders at a time. So courier costs go basically to zero. What do we think of the export controls here? Should we, Chamath, be maybe banning more H-100s or other chipsets going there, or is that futile?

I don't know the answer to that, and I think Sachs and President Trump will make a good decision. but here's the curious case of the export controls. Nick, I sent you a couple of tweets if you want to just bring this up. So the first thing that people are claiming is that DeepSeek is getting access to a bunch of NVIDIA GPUs using Singapore as a backdoor. So essentially you create a Singaporean shell company, you place an order with NVIDIA, NVIDIA fulfills that into Singapore, and then the chips go someplace. Uh-oh. And so there's a bunch of examples where people are saying that you're talking about up to a quarter of all NVIDIA revenue goes into Singapore.

And the speculation right now is that 100% of those then go into China, which is an enormous claim because that's a huge amount of NVIDIA's revenue. Now, the interesting thing is if you actually try to understand, well, maybe that's not true and maybe it's sitting inside of Singapore, this is where that kind of unravels. So just to be clear, Singapore is about 250 or 260 square miles. It's like a small, small place. Also the TikTok headquarters. And I tried to find out how many data centers are in Singapore and it's about a hundred. And so you would think that, okay, well, what does that mean? A hundred could mean anything. But then you look at the energy and they publish that. And all of those hundred data centers consume about 876 megawatts. So these are small data centers, right? And the entire industry is like a $1.5, $2 billion revenue business. So I do think that SACS and the administration are going to have to dig into this and figure out what their opinion should be. But there is clearly a ton of these chips going into Singapore. I don't think anybody knows where they end up. And the question is, what does America think about that? And why did we implement these export controls in the first place? And if there's a simple backdoor, how do you want to react?

If the US finds a path, I mean, let's talk about like what happened with sanctions in Russia and other prior kind of sanctioning efforts around the world. But as you kind of close the floodgates and close access, the buyer or the receiver of those goods or that capital are going to look elsewhere. They're going to look to create a market somewhere else. And so if we do cut off access to NVIDIA chips, we do cut off access to US exports, are we not kind of recognizing that the second order effect of that is that China will take IP that they've stolen, copies that they've made to travis's point and develop and build out their own fabs and they'll find ways to copy the asml technology and you know at the end of the day there's a lot to put together and i know it's deeply technically complex but if ever there were a group of people in the history of human civilization to pull it off it's probably the modern chinese to be able to say let's go build our own it's worse than that our own infrastructure this is a great great point, but it's worse than that. The models today are capable of designing chips for you that don't rely on the most complicated technologies that ASML creates. I mean, look, one of the

luckiest things that happened to Grok was we designed our chip at 14 nanometer, which is effectively in the spectrum of technology like VHS and beta. So we chose a simple, simple technology stack to build towards. The latest cutting edge chips at like two nanometer that use these complicated ASML machines, it's not clear that the yield is actually that good. So why would you spend all that money? And if China is forced to engineer its way around it, yeah, Freeberg, the answer to your question is they'll use these models to design chips that can be manufactured in simple ways, and they'll make simple stuff. So this is why- I'm just not sure it solves the problem is my point.

Well, it doesn't. And this is why I think it doesn't solve the real problem, which is how do we incentivize people in America to really out-engineer and out-innovate? Competition. Or AI ushers in an era of extraordinary abundance and that abundance ultimately reduces the drive for conflict and things are better off. Or the other version as well is that China could just bear the cost as a central authority of building an incredibly great model, right? And they will spend all the money and then they will tell the Chinese companies, you can distill from this model for free because we have a golden vote and a seat on your board anyways, which is effectively de facto what happens if you get big enough in China.

So there's that possibility as well, where one central authority bears the capex of creating something that then everybody else can draft off of. And let's talk a little bit about OpenAI. They're in Washington asking for money now. Is that the concept now? Is that our government should back? The rumor today was they're raising $40 billion at a $340 billion pre-money with Masa potentially being the lead. I would love Travis's read on this because Travis has taken large money from Masa in the past and has been through this, but how does he think about and make this decision? Obviously, we all know, and I mentioned you guys at the meeting I had with him last summer where he basically kicked me out of the room because my company is not generative AI.

Someone said, you should go meet with Masa. So I'm like, sure, I'll sit down with him and start talking. And he just looked at me and he's like, this is not generative AI. I only do generative AI. I think your company will be very successful. You will be very successful. Goodbye. And he always walked out And that was like the end of the meeting. It's so great. Yeah. Well, that's all he's doing now. So this is the big bet, right?

The question is, do you get to this place of overcapitalized, too big, too bureaucratic, too loose, too weak, too soft?

and with when you have an open source model that's very smart and it's a thousand flowers blooming lots of innovation happening everywhere could be an overwhelming force uh now i think there's going to be different sectors treated different ways we're like going full stack in certain industry sectors is going to matter and then in other places having like a very sort of chaotic everybody does a little slice it's going to be okay in other places and i think we could probably spend days or hundreds of dozens of hours just talking about the nuances there you know well it seems like there's some degree of relationship between the stargate announcement with masa and sam standing up there with larry and then satya showing up in the conversation as well and this raise and the idea that more hardware more infrastructure faster creates a moat and i guess that's the real thing you have to believe, which becomes harder to believe in the context of what happened in the last week. I personally think that these models are, and I've said this for a while, it doesn't make sense to have one large do everything model. This mixture of experts, architecture, ultimately, you can kind of think about taking a large model, making two copies of

it, and then trying to shrink each model down to whatever the necessary so that you run two models in less frequently meaning that that combination of two models uses less power and takes less time and then you do the same thing again and you shrink it down to four and then 12 and eventually you have lots of smaller models some of which in some cases are experts at one thing like doing mathematics or reading or writing but the reality is we don't know how whether humans have kind of thought about the world the right way that the ai may resolve to having smaller expert models that we don't really understand why that's the expert on something but you have a network of very small kind of things that work together and that ultimately leads to a like commoditization not just in kind of model cost and in development and runtime but also in like what's needed like do you really create much of an advantage by having all these data centers this is the key point i think freeberg is you're not going to get an advantage by having more h100s at a certain point and the actual advantage is going to be in the ip and owning content and the really smart thing to do, would be for somebody to go buy Reddit, Quora, the New York Times, the Washington

Post, and Disney, and take all that IP, and then not allow other people to use it, sue the hell out of them every time they try. Well, I take Washington Post off that list, but yes. But I'll say it. New York Times comes off the list too. Well, whatever. I mean, all those archives are definitely going to be what would be great about You could then, like a patent troll, then tell anybody else who's absorbed New York Times stories historically or Disney IP historically, and you could just sue the hell out of them, and then you've got the best, most proprietary one. You're describing text. So you're describing text content, which is a fraction of where- Also video.

This is important. So video, I think you can recognize that Google's YouTube content library is probably 100 to 200 times larger than the rest of the internet combined. But they don't have the right to do it. Well, they do, actually. Jason, you're such an old school copyright guy. You're such an old school media guy, by the way. Sorry, I believe in artists and their right to content. We've had a series of conversations that I feel very confident to tell you that they do have the right in a good chunk of that content, not in a lot of the copyrighted content that the big media companies have given them, but a lot of user generated content.

They do have the right and they are using it and they're legally doing it. And then there's the separate kind of body of content, which I think comes, for example, from Tesla. Tesla has an extraordinary advantage that they were really pressured to put cameras on everything years ago. And that gives them this ability to build models that do self-driving. So I think that there's a lot more data advantage that arises in certain industry segments than others. And that's where the moat will lie. And that moat will allow you to actually build better products that get you a more persistent advantage in gathering more data. That's ultimately where I think this resolves to. It may not necessarily be about who's got the biggest data center network. Yeah. I mean, here's the thing, guys. At some point, the amount of data becomes the long pole in the tent. At some point, the quality of the algorithms becomes a long pole in the tent and more compute is not going to change that. I don't think we're there yet.

That's the one thing that counters the cheap AI means more AI is, is there enough data and or algorithms to make them more AI, to make it work. And I do agree with the siloing it and getting expert and getting better in these ways. But I think this is an interesting sort of trade-off between some of these variables. I just got offered 2,500 bucks to put Angel, my book, into because HarperCollins did a deal with Microsoft. And so I'm thinking- 2,500 per year? I think it's for three years is the license. And they just did this blanket license for every book. they didn't look at yourself they didn't look at how desirable it was it was just like a blanket deal everybody gets 2500 bucks per book for three years and i think i'm going to just do it just to support proper licensing so that people can start going down uh this path but let's get into doge it's been a uh i think we're in 10 days into this administration and um trump formally established doge the department of government efficiency in an executive order apparently elon's been spending a lot of time at the offices, bunch of wins. Doge is claiming on the interwebs to be saving American taxpayers around a billion dollars a day. That's $3 for every American every day, about $1,000 a

year in savings for each US citizen. And they claim they can triple this. And so for Family Five, that'd be about $15,000 a year, maybe $60,000 during Trump's second term. We got $36 trillion in debt. Have fun with some numbers there if you like. But the key announcement was a very similar to the twitter execution the ability for people to resign done in a very kind way eight months of severance ish is being offered to federal workers they expect five to ten percent of federal workers to take this buyout and it's um i mean this could be something like a hundred billion dollars in savings eight months of severance um is not actually a legal concept that you can do so these are some sort of buyouts and there's obviously some hand-wringing about it but i think they're off to a good start they've also been canceling leases as we talked about you know pre-election there is so much space not being used that the federal government is terminating a ton of stuff they own and going to sell it and consolidating folks. And at the same time, all of this is happening, everybody has to return to office. Who wants to go first here with, you know, the sort of first 10 days of Doge?

I see some eggplant emojis in the group chat. First 10 days of Doge, how excited are you? chat what's that about i'm adding you right now how are you not in the group chat i'm adding you right now i'm literally every time one of these hits the group chat it's just hilarious eggplants people are like oh my god we're not burning taxpayer dollars and the eggplant always comes with freeberg first i'm outing him as an eggplant i'm a i'm a big doge eggplant guy oh so much eggplant. So Freeberg, tell us about how much eggplant you love this. There's nothing that I would say is particularly surprising in the first week. A lot of this was kind of talked about leading up to the inauguration. Vivek and Elon published their piece in the Wall Street Journal a couple of weeks ago. They talked about the mechanisms of action that they could utilize to kind of drive reduction in cost, one of which was come back to the office, another one of which is, you know, giving people a buyout offer.

And by the way, the buyout offer is not new. Bill Clinton did the same thing during his presidency. If you guys remember when he tried to balance the budget, get to a surplus, which he did successfully, and his intention was to actually reduce U.S. death to zero by the year 2013. And he had a very specific economic and fiscal plan for doing that, which he put into place. Incredible era. I think we're seeing them take the actions that they said they would do. They said they would demand to employees, federal employees, come back to the office, and they assumed some degree of attrition from that, and now the buyout offer, and we'll see how far things go with the courts with respect to their ability to stop a legislative or statutorily mandated spending.

There's a big question mark here on how much authority the executive branch has in stopping spending and how much they're not allowed to stop because it's demanded by law. It's demanded by Congress and acts or laws that have passed. And so that's going to be the big test here. Over the next couple of months, a lot of lawsuits will fly. The courts will ultimately adjudicate and we'll see how far the Doge intention can take things. And then there's a separate set of efforts around legislative action here. There's about a $2 trillion annual deficit right now in the United States federal government, $2 trillion a year.

And if you look at the Dalio book on why countries go broke, there's a pretty simple kind of arithmetic in there, which is not complicated. It's just at the end of the day, the US needs to get our federal deficit down below 3% of GDP, which means we've got to cut about a trillion, trillion one of spending. If we can do that, then we're in kind of a more economically sound place. By the way, a really important point, which is in the Dalio interview, as you cut spending, interest rates will come down. Because right now, there's a pretty significant sell-off in treasuries and a lot of risk associated with the U.S.'s ability to deliver its debt obligations over the next 30 years, which is why 30-year treasuries are at 5% right now.

Even though the Federal Reserve is cutting rates, the rate on treasuries is going up. People are still selling off treasuries. That will stop. It's also inflationary. It's also inflationary, Dave. That's right. For sure. And so as we cut spending, we also will see that there will be less inflation and the U.S. ability to pay back their debt obligations over the next 30 years goes up, so the rates will come down. And so there's actually a really nice kind of cyclical effect as these cuts start to come into play. The rate at which you can make the cuts actually affects the amount of cuts you have to make.

The faster you make the cuts, the less you have to cut. And that's a really key kind of principle going into this, which I think we should expect a big whirlwind of cutting in the next. couple of months or an attempt to, the courts will adjudicate what needs to be legislated, and then they're going to go to Congress and start to try and get some of these cuts in. But I will tell you once again, after our visit in DC last week, there was not a single member of Congress that I spoke with who views cutting to be a mandate for them in the laws that they're trying to pass. They all have a very different kind of agenda than Doge.

Well, look, this is really one of those interesting things where it's like the difference between legislature and executive branch is like a doge is really bringing it to life is like what powers and controls does the executive branch have to spend and not to spend and especially to not spend when it's been legislated to spend this is where the action is like there's no law that says you know you can give a bunch of folks eight months of severance and they're gone and you don't replace them. There's no law that says that. The executive branch, and again, I don't know all the laws, sort of the rules or laws about how they go about doing it, but let's say presumably they're doing this and there's some legal backing behind it.

They just go and do it and now they're not spending money. If it was really hard to hire people and they could even make it harder to hire people, do they fight bureaucracy with bureaucracy that it's harder to spend, hard to hire people, harder to procure certain things that you're supposed to spend money on, you can reduce the spend through a lot of very interesting nuanced rules that they're in control of. Yeah. Some friction could slow things down. They're talking about putting competency tests in. They're talking about giving people reviews and maybe they have to hit some standards and the gentleman's riff. I mean, when you force people to come back to the office, you're going lose 5%, 10% of people and 10% take the buyout. And now all of a sudden we're saving things.

I mean, it'll be interesting to see if it's 5% or 10% on RTO. I mean, it could be a lot more. I mean, what I'm hearing about these buildings is that they are super, super empty, like next level empty. And let's just say I'm really glad I don't hold it. Like I'm an owner that has a bunch of leases to the federal government right now. Oh, the government. And you know what the interesting thing about those leases? I was talking to the team at Density, which does people accounting and building. So they obviously are very interested in that. The government is such a reliable client that they're all on one-year leases.

So people don't do what they do at startups, but just force them to do five or 10 years because they know, hey, this company could go out of business. They're just like, yeah, yeah, we're just on a rolling year-over-year lease. So you can actually just cut these. it's going to flood the market. Shamath, your thoughts on also the stopping of, because they're obviously going for it, they stopped all payments, which is a part of the playbook I saw on Twitter up close and personal, which is, hey, let's turn off subscriptions and see if anybody's using these subscriptions, basically. Obviously, a judge got involved in that, but aid going to other countries, we're just starting to look at what are we actually sending to other countries and for what purpose? And then there's a naming and shaming and maybe appealing to the public through social media and saying, hey, do you want this money going here when, hey, we have tragedies in our own country that need to be solved? We have healthcare, we have houses burned down, we have infrastructure. And so maybe you could talk a little bit about hearts and minds and winning those and what your general take is so far. I think that we have to remember that we're only

nine or 10 days into Doge. So the fact that we're already at a billion dollars a day is really incredible. And there has really been no discernible impact. There has been a lot of fissures of fake news and misinformation, but the real impacts have been negligible to none since they started making those cuts. I think that Doge is a three-layer onion. So layer one is the people. We have now given a pretty generous offer to folks. and I think Elon said it. It was like basically the maximum allowed by these contracts, but they tried to do a very good thing there. The second, as you guys just said, the second layer of the onion is going to be the infrastructure, all the buildings, all the physical plants that the government owns and operates that may be empty, that may be idle, and getting them back into private hands so that they can be repurposed. That's going to save a ton of money, but both of them will pale in comparison to the third layer of this onion, which is the IT and the services and the spend. And what I mean by that is when you read how the department is set up, at the center and nucleus of every single one of these Doge teams is an engineer. And I think the reason is that they can get into these systems of record and start to trace where the money is

going. And I think when you start to uncover through forensic analysis, where these dollars are going and how it's spent, that's probably how you're going to close the gap from a trillion to I suspect, to be honest, it could be more than $2 trillion when it's all said and done. That is an enormous amount of waste and it's unproductive. So I'm very excited for what happens over this next little while. Just the transparency is going to be incredible. Guys, just for kicks, check this out, right? If we took 2019 spend, right, the year before COVID and put it up against 2024 revenues, $500 billion surplus. Wow. That's crazy. Versus the $1.5 trillion dollar deficit so a two trillion dollar swing on like uh four years yeah on a four trillion dollar budget that's all waste well a lot of it remember we've got a trillion dollars a year of interest payments now i mean this is guys this is the thing like there's two deflationary things that we need one is doge and two is where ai is going to take us if it really does its thing and that will keep us in an okay spot economically.

But like, we got to, this spend has to go or we're in sort of like, we're in Greek territory, if that makes sense. Yeah, and I think this is, the popular support for this is pretty incredible. I'll just go through a couple of numbers with you. You know, looking at what people agree with that Trump's doing early on and what they disagree with. You know, obviously we talked about it last week, Chamath pardoning the January 6th protesters and, you know, ending requirements for government employees to report gifts. That's sort of like the Supreme Court thing. These are tremendously unpopular. And then if you go and you look at downsizing the federal government and imposing a hiring freeze and requiring all federal employees to return to an office, these are incredibly popular. And Elon tweeted these graphs out as well. So right now you have Trump at the apex of his political popularity. And you have these issues specifically in a very polarized time as incredibly popular. He's also done an incredible job with the border. That's another consensus-based issue. So Trump now has downsizing the government and controlling immigration and getting rid of violent immigrants as incredibly popular parts of his mandate. And that's the big

win for him, if you look at his popularity, Trump is massively more popular than he was the first time around. He's at 49% compared to last time, 44. He's still the historically least popular president ever. So my point in all of this is, when you see Trump doing things like his meme coin, or, you know, taking on Pete Buttigieg today, all that kind of Trump 1.0 negativity, grifting, that's the stuff that's going to derail. this. But the stuff that's not going to derail it is focusing on the Trump 2.0 agenda. And that is, as somebody who was a never Trumper, as you all know in the audience, and now somebody who is supporting him relentlessly, that margin, that extra 10% of people who support him right now is me and other folks who are looking at the people who put around him. He has to stay with the 2.0 agenda as hard as it is and stay away from the Steve Bannon agenda and the grifting. Those are the things that will take this all apart. So that's my appeal to them. I told everybody I'd give a letter grade. I give them a B so far. Could do better, but pretty good. Less of the meme coin, less of the drug. We have to make sure that we're not dragging dishwashers and teachers and people

who've been here 20 years out of the country. And it's going to be a very deft, important approach here if this is going to be sustained. And I think it's a coin toss if he will be able to maintain his popularity. And what he did today with this, like, I don't know if you saw the Pete Buttigieg, he was attacking him over this tragedy. That's the kind of stuff people don't want. Less of that, please. More of the doge. That's my little rant. Can we talk to Travis about Waymo now? Travis, can I ask, have you taken a production Waymo? Yes. What do you think about it? And do you think that's the future of transportation? And how does Uber play into the self-driving car business now i mean look it's funny because as you guys know back in the back in the day 2015 16 17 we had our own autonomous vehicles out there and i remember the first one of ours that i took and i got in the back and all i had was a stop button a big red stop button that i could push if things got weird and i remember this is in pittsburgh where we had our robotics division and autonomy division at uber and i got out of that car and literally it's like i got off a roller coaster ride like my legs were i could not stand straight like i was like a little wobbly

because i was so freaked out and the adrenaline was pumping you get in a waymo today and it's like you're not even thinking twice you're just like it's all good you just get in you get out now part of it's just the normalization it's like it's just working and it that normalizing matters in terms of the psychology around it is we're just there. So it just works. Now, is it a optimized experience for ride sharing? No. Like the cyber cab is sort of the ultra sort of destination for what it means to get transported across a city in a vehicle that is not meant for a human to drive. No steering wheel, you know, folks potentially even facing each other, just a whole bunch of different formats. The technology works. We know that there are different ways to get to the technology. I think that probably the most interesting thing that we should be, or one of the most interesting things to be thinking about, maybe there's a few.

in this regard because obviously there was the cruise you know a person got hit by a regular car they dragged it the whole thing imploded we had uh at uber the um the tragedy in arizona where somebody was playing candy crush when they were a safety driver you know what is your outlook on this stuff rolls out and somebody gets hurt and then that you know tens of thousands of cities that you brought uber to how receptive are they going to be towards this and what do you think

the regulatory framework will be like you know i think similar to how you get normalized it's like you're used to getting in a car. It's normalized psychologically and in the sort of public sphere, the public mindset, you get used to it. So like we're getting to a place where these vehicles are provably safer than human driven vehicles. So yes, there are mistakes, but they're just provably safer and people are just getting used to it. And that's a big part of the cycle. So I think we're getting out of the hysteria and we're getting into like, yeah, it's just great like talk to people who are using it and they feel safer from uh of course like i i feel like we're going to get in less accidents but also i feel safer because there's like there's less chance of like an interpersonal problem that does happen especially you know late at night you know when people are out partying and things like this there's just like there's a level of safety on many different aspects to these vehicles.

Yeah, for the driver, yeah. For the drive, no, it's for the, yeah, there's like, there's safety aspects across the board. Sure. Right. What do you think about BYD and like you sort of mentioned everybody getting to autonomy at the same time? Obviously, Waymo's got the biggest lead, Tesla's behind them, BYD, and about 10 other providers are out there doing this. Does, you know, do 10 players get there at the same time? And then it's just who can incorporate these into their network? and what do you think of the strategy that uber's doing of hey we've got these eight partners we'll take everybody into the network and we'll manage people vomiting in the back of cars cleaning them and charging them so look i think the big issue you have with anything chinese is will you be allowed to bring it in the us just period like you maybe kind of can now what happens with tariffs will there be blocks and bringing this kind of technology into the us what happens there i think that's a whole thing.

the bet that uber makes is that whether consciously or subconsciously that's like will ai will cheap democratized ai happen and if so does that make cheap democratized autonomy then you've got to line up your physical sort of hardware partners the car manufacturers then you've got to say okay is the electricity where it's at and are there other bets to make to make sure that i can charge my cars so like there is a huge real estate play here and fleet management play of like how do i electrify these plots of land known as parking lots and also set them up so that robots can clean cars in sort of a very very efficient way there's like a whole when we talk about that's super interesting travis that's like it's almost like the idea that we all talk about today is data centers and data centers need their own power substation yeah in order to meet the power demands but if if we do see a world of robotics automation generally and we've got these kind of moving robotic systems in our world they need to have a similar sort of like power demand met that probably looks like hey they all go into their their recharge building and they get recharged whether they're a car or a humanoid robot or a food delivery robot on the sidewalk

or whatever, or drone, and they just kind of get recharged, huh? Robots need actuators. Do you know what you need for an actuator? A permanent magnet. You know what you need for a permanent magnet? Rare earths. Who's the rare earth king? Ex-China. Greenland. Greenland, let's go. So guys, I think there's a couple interesting things. One of them is going to be how are these companies thinking about real estate, electrifying that real estate in urban environments and roboticizing that real estate so that they can do the servicing maintenance etc look i guess it could be manual for a while can i can i put you

2.9% in terms of inflation. Any thoughts on where we're at with the Fed deciding to not cut?

And just you put it on the docket here, Chamath. Any wider thoughts there? I would just say that the long end of the yield curve is basically telling us that there's still a chance for inflation. So I think that the question is these next 30 or 60 days from the administration, I think are basically, they're critical. And I think if Doge gets to the 3 billion a day number quicker than people thought, there's going to be a lot of room for, I think, the president to make a very valid argument that rates are too high for where they are, And that we're going to be able to have a lot more cost control in the expenses, which means that there'll be less need to spend. It doesn't solve the problem that Yellen created. Yellen and Biden on the way out the door, the biggest problem was that they put America in this very difficult position because they issued so much short-term paper that is extremely expensive.

And as all of that rolls off, we have to go and finance a ton of this debt at now 5%. Nearly 30% of the debt is going to get refinanced this year. And then it's like, what are these auctions going to look like, guys? This is the thing. We all got to breathe. The last auction barely had 2x coverage. And I think that that could take a lot of the energy out of the market. Watch the Dalio interview because this is exactly the topic he covers. You know, as we end up needing to refinance this debt, the rates climb, the appetite isn't there, and it becomes a spiral. That's why we have to cut fast in terms of the deficit to basically attract the market.

Now, you know, the market's moved a little bit, right? So on January 13th, the 30-year Treasury peaked at exactly 5%, and it's come down today. It's at 4.77, so a little bit of relief. that peak as kind of the administration's gone into office and actually taken action. But as more of this action is realized, if people do appreciate and Doge is successful and the court's adjudication does allow reduction in spending, which I think is the intention, I think we could see this rate drop from 4.78 much more significantly than where it is. And that'll create a great deal of relief. And Dave, it's like, it either does that or it really, really doesn't.

or it does like the exact super nasty really bad that's right i got a text from someone who is pretty senior in capital markets thinks this is going to go to five and a half percent before it goes down so they think that there's going to be a little bit more of a turbulent run ahead but it's like but the thing is it's like that whole thing of like it's going to get to five and a half before it comes down it's like by the way it spirals on itself it's like You got to print money to then get to that place, and then the printing drives it. You get to that spiral. The problem is if we go to 5.5%, that's not 80 basis points.

What you really need to think about is the total tonnage of actual dollars that need to get repaid back. And if you look backwards, that's effectively like 10% rates from 2000. Could you imagine what the economy would have done if you had brought rates to 10%, 11% 20 years ago? It would have crippled the economy. So we don't have a lot of room here where you can walk rates up to 5.5%, 6% without a lot of things starting to break. This is why I actually think Doge will be successful because as people internalize all of these things where every single congressperson, Freeberg, that may have wanted their own benefit for their community, they'll have to take a step back because the broader optimization for America just needs to take priority.

But Shamath, it just doesn't work like that, man. My thing is, I agree with the notion, but I just don't believe that any individual congressperson will take responsibility in this way. No, they won't. They won't. But the question is, can they block it? Yeah. Or put another way, again, the executive branch can slow roll spend in a lot of different ways. Except you cannot with Medicare and Social Security. discretionary spending is like 20%. The mandatory spending, Social Security, Medicare, Medicaid, these are the larger outlay. And this where we come back to the fact that this will never get addressed until it has to be because of the political suicide that arises.

I just think this is where I think Elon's fame can be helpful. And I mean very specifically this following idea. That famous Sputnik comment where NASA spent millions of dollars trying to engineer a pen that could write upside down, and it turned out that in Sputnik, the Russians just took a pencil. That is what we need to do to the US government, because I suspect even though there's a lot of mandated spend, the real question that nobody knows the answer to is, is that spend useful? So even though it's appropriated by Congress, there has to be a feedback loop that says, you can just use a pencil. You don't need the upside down writing pen. And I think that if there's anybody that can broadcast that to the world, it's him. And this is where I think Trump gets enormous leverage by having Elon in the West Wing, but nobody else could give him. The rest of us would just be chirping into the darkness. Yeah. This is the naming and shaming of government waste that's actually going to work. And the Doge account on Twitter is doing it. They're basically saying, hey, we're giving foreign aid for this project, for that project. Is it going to be perfect every time no but you show an empty office space you show people not coming to work you show

people wasting money well yeah if that's even real you know there's going to be a bunch of you know back and forth here but overall if you keep naming and shaming each of these projects and then you know they were talking about blockchain whatever and supposed to report elon is at like the government building working on leases at the moment like this stuff is going to be extraordinarily popular because you can just take the number of 330 million Americans, and whatever you just saved, you can just divide it by that number and tell every American how much they just paid less in taxes or how much they just saved individually. The naming, shaming, and doing the back of the envelope math for every American is going to work. Do we want to wrap maybe a little bit on this tragedy in DC?

Okay. What are your thoughts? We were talking with our friend Sky Dayton, who is very involved in aviation, and he's got a lot of blog posts he's done recently, and he's got a company he invested in to do pilot training. I'll share two things. One is anonymous. It's from a friend of mine gave it to me and said I could share it. This is a commercial pilot and I posted this, so I'll just read it. Honestly, DCA is the sketchiest airport we fly into. I feel like the controllers there play fast and loose, hence the periodic runway incursions. I've said to every first officer in my threat briefings that we both need to be on red alert at all times there. DCA calls out helo traffic, helicopter traffic, and vice versa all the time, but it's borderline impossible to see them when you're bombing along at 150 miles per hour. I mean, that's from a pilot that I don't think he has any incentive to sugarcoat things. And then I just wanted to read a message from Brian Yutko, who's the CEO of WISC, who's building a lot of these autonomous systems. He said, first, auto traffic collision avoidance systems do exist. Right now, these aircraft will not take control from the pilot to save the aircraft, even if software and systems

on the aircraft know that it's going to collide. That's the bit flip that needs to happen in aviation. Automation can actually kick in and take over, even in piloted aircraft, to prevent a crash. That's the minimum of where we need to go. Some fighter jets have something called automatic ground collision avoidance systems that do exactly this when fighter pilots pass out. And it's possible for commercial. And then the second, he said, is we need to have better ATC, air traffic control, software and automation. Right now, we use VHF radio communications for safety and for critical instructions. And that's kind of insane. We should be using data links, et cetera. The whole ATC system runs on 1960s technology. They deserve better software and automation in the control towers. It's totally ripe for change. The problem is that attempts at reform have failed. So I just wanted you guys to have that, one from this commercial pilot, and then two from Brian Yuko, who I think understands this issue really well. There's so much opportunity here to make this better. This should have never happened. Our other friend, And Sky Dayton has been pushing really hard for the U.S. government to do advanced pilot training.

One of the things that he says constantly is just that a lot of the pushback is just union rhetoric around what they perceive the right thing for their constituency is. And hopefully this starts this conversation because I think guys like Sky, guys like Brian are working on this next level of autonomous solution that can just make flying totally, totally safe beyond what it was. the crazy stat is that we haven't had a commercial airline disaster in the United States in almost 25 years. Isn't that incredible? I think it was 15, yeah. It's looking like pilot era here. And there also seems to be some question of why these Apaches are flying around this really crowded airspace. And it seems like they're shuttling politicians around. And maybe that's not the best idea in this really dense area, as your pilot friend was referring to, Chamath.

so god thoughts and prayers and all that stuff for the um for the families of the people who died it's just terrible tragedy terrible tragedy yeah it's just it's really just this is an area to invest money and use the private sector and all this incredible innovation that's available to upgrade these systems and infrastructure this has been another amazing episode of the Well, in podcast, thanks, Travis, for joining us. Thank you, TK. Thanks to the czar for coming in. That was a lot of fun, guys. First time. This is my first time on a podcast ever. Yes. You did a great time. Get right in. You were great.

Come back anytime. You were great, man. You were great. I appreciate it. Appreciate it. Very based. That's what you're going to like. Tell us what you think. Totally. And we'll see you all next time. Bye-bye. Love you, boys. Bye-bye. We'll let your winners ride. Rain Man, David Sacks. And instead, we open-sourced it to the fans and they've just gone crazy with it. Love you, Westies. I'm the queen of kinwaf. I'm going all in. Besties are gone. That's my dog taking a notice in your driveway. Sex. Winning a bitch. Oh, man. My habbitasher will meet me at what it's like. We should all just get a room and just have one big huge orgy because they're all just useless.

It's like this sexual tension, but they just need to release somehow. Wet your feet Wet your feet We need to get merch I'm going all in I'm going all in