OpenAI vs Anthropic IPOs, Anthropic $3T, Zuck's Price War, China Ends Open Source?, Trump Accounts

All right, everybody. Welcome back. Number one podcast in the world. It's. July Allin episode 280. Freeberg is on a. little vacay. We'll leave it at that. And uh yeah, bestie Brad is here. How. you doing, Brad? >> I'm doing great. I'm do vacay in maybe. Idaho or somewhere. Jal, >> I know. Who knows? Who knows? >> Who know? It could be anywhere. He could. be anywhere. I mean, there's lots of. things. He could be in plenty of places. And uh looks like you are yeah somewhere.

in the northeast. I'll leave it at that. You having a little uh vacay for. yourself this week? >> Very pat I'm in my flag room. Very. patriotic room here. >> Very nice. >> You know where I work on the east coast. in the summertime. >> and uh spent some time in DC this week. >> and uh it's been a great week. Been a. great week celebrating America 250. >> Great. And you're going to be out of. there for the by the by the second week. of August. Yes. So I have it August 10th. through the 30th. I'm good. >> Exact. Exactly. Jason. B&B.

>> Oh, absolutely. >> You You don't know the half of it, man. I am on a summer bender. I'm like, "Where's your Where's your vacation?". >> By the way, where are you? Where are you. right now? >> I am in Paris. I did uh about eight. interviews for at the Rays conference. They'll be coming out uh in the all-in. feed. And of course, tackling from the. factory. Look at him. You're working in. the factory. Chimath Polyhapatia. It's. going to be a hot software summer for. Chimath. How's your hot software summer. gone? >> It's good. Selling enterprise software.

is hard, but it's good. >> Chamat's like, "Man, I was such a dick. to all my CEOs in the SAS period." And. now you know, >> I went to Geneva. Shout out to Markov. I. went to Geneva. He works out of Europe, sees all his European customers, and he. had a dinner in Geneva, which I joined. And then me, Jensen, Brad Smith, Anthony. Tan from Grab, and a bunch of other. folks. were put on this UN Commission for AI. >> that Mark is the co-chairman of. When. you see Mark Beni off in action, man,

this guy is a master. >> Holy. >> He is the empasario of empisarios. Yeah. >> You see how he's built such a ginormous. business. It's impressive. It's. impressive. >> What is a commission by the United. Nations for AI? What is their what is. their uh calling? >> Open source. No, but no, I mean it's. like the United Nations actually do. anything. Do they actually. It's so funny. Yeah. I mean, Anthropic. was there too. Some one of the.

co-founders, Tom Brown, I think was his. name. >> Yeah, >> that's good. >> Was the Anthropic guy running around. saying, "It's the end of the world. It's. the end of the world.". >> No, no, no. He was he was very awesome. Tom's awesome. >> In fairness to him, he wears. it on his sleeve, which is like, "Hey, we really believe we're doing the right. thing, >> right?" and just trust us and I think. the future's open source for all these. countries. >> Well, we're going to get into that. That's on the docket for sure. But let's. start with the IPO update. You know,

there's a trillion dollar IPO rush to. the exits and you know, this was a big. topic of discussion, Brad, at the. liquidity summit last month. And we'd. never seen a trillion dollar IPO. We had. one this year already. SpaceX trading. right about where it went public. So, it. was priced, I guess, to perfection. and theoretically going to see two more. Uh Brad has the inside information, so. I'll try to get it at him. Open AAI and. Anthropic are slated to go out. Let's uh. just go quickly over what happened with.

SpaceX. It ran up to $200 a share. Uh. it's been down a bit. It's at $150 a. share. As I said, that's right at the. IPO price. So, it's trading at that two. trillion market cap. Currently, seventh. largest company in the world. And. Anthropic confidentially filed on June. 1st. I I don't know why they call this. confidential filing when it immediately. comes out. Uh but I guess the. information is confidential. Poly market. says 65% chance Anthropics IPO will. happen this year on light volume 360K.

And uh two weeks ago, Gavin Baker, another bestie, said he thinks they're. going to end 2026 with over a hundred. billion dollars in revenue and very. profitable. He said a couple of us. guests on the program that he thinks it. would trade at three trillion right now. if it went public. Chimath, you made a. great call on the pod. You said, "Hey, good idea for Elon to get out first.". What are the chances here, Chimoth, that. these other two get out this year or.

maybe in like, you know, say 9 months in. the in the first quarter of next year? We'll start there. >> Well, I think that these are all great. businesses. I think the question is what. is the market clearing price? And I. think that's more of a function of. how much appetite. the markets have to absorb new issues. and at what scale. That's number one. And I think that's mostly determined by. price. So I think anthropic and open AI are. probably in two different places. The. last time we heard from OpenAI,

their cash burn was still quite high. just because of the diffuse nature of. their business and more reliance on. consumer than enterprise. I think Brad. mentioned it in one of the pods that. Anthropic may actually be accidentally. profitable. I think he said something. like that. >> Yeah. >> Let me tell you something really. interesting. I sat down with my CTO. today and I said, "How are we doing on. token spend?" And he said the most. incredible thing. He said, "Right now, our token costs are doubling every 45.

days.". >> Okay. >> And I was like, "Gh." And he said, "Yeah." And I said, 'Well, what is the. downstream productivity? And he said, maybe 5% max. >> Okay. >> And I said, okay, so my costs are. doubling every 45 days. My upside is. essentially flat. And he said, basically, and I said, well, explain why. that is. and he said, "Honestly, what. we're finding out is that. you need to use a lot more tokens.

to get to this next. iteration of improvement because we've. effectively already asmmptoted.". And I said, "So, what should we do?" And. he said, "Honestly, we have we have to. figure this out." And so, we're going to. take a step back and try to figure out. what to do. I don't know how many other. companies will actually go through this. reckoning now, but the point is. everybody in the next three or four. years will for sure go through it. So, I. suspect that if you can get out now, you. should get out now before. all of that starts to seep into the.

water table. because I think that's probably what. allows you to get out at a huge price. and and raise a huge amount of money. >> All right, Brad, you are uh well. invested and well known for being. invested in these two uh next IPOs, so. you probably have some good insights. since you talk to them on a regular. basis. chances they get out in the next. six to nine months. Both of them, you'd. say 100% chance, unless there's some. outside event, you know, blockade of.

Taiwan, some black swan event that we're. not anticipating. What do you think the. chances are they're public when we're. sitting here and I'm skiing in Hokkaido? >> Yeah, I think I think it's very high. But let me let me first say, you know, the SpaceX IPO where we were also. investors and we also bought in the IPO. I mean, it was textbook. It was a hugely. successful IPO. They raised $75 billion. at 1.75 trillion. Okay, so it went out. below where we are today. It's up 25%. You know, and let's call it on 35.

billion of forward revenue. So if you. think about that revenue multiple, it's. trading at 2 trillion on roughly 35. billion of of forward revenue. It's an. incredible achievement. I think it was. textbook. I think Anthropic and OpenAI. were watching very closely because. frankly we had not had an IPO of that. size and to Elon's credit and to the. team's credit Brett and Gwen they really. pioneered some really smart and. interesting things as part of that IPO. So, you know, you heard from Gavin.

Anthropics rumored to be, you know, trending over a 100red billion in. revenue compared to the 35, right? If. they exit the year at 100, that means their gap revenue next year. could be well over a 100red. So, based. on the SpaceX success, I think it would. be a blockbuster IPO. And I think SpaceX. has shown them the way on things like. the total raise, pricing, liquidity, inclusion into the indexes, how to do. the lock up. Like I think they've gone.

to school. >> It was a staged release in terms of. getting out of the lockup. It has to hit. certain milestones and some of those are. time. >> early inclusion in the index raise $75. billion like you know. >> the early inclusion in the index. Let me. have you unpack that for a second cuz. people said, "Hey, maybe this feels. >> unfair that they should be forced to buy. it." What's your take on that? Is that. just like. >> haters going to hate or is there. something to that? I think there was. legitimate concern, right? This.

>> is legitimate concern. Yeah, >> the legitimate concern is that a company. that had not been through the process of. being vetted post IPO, there's a lot of. volatility. You've seen that chart Jason. that the the peak to trough draw down in. the 6 months post IPO is 50%. We've seen. a pretty big draw down here from the. peak to trough. >> as well. So you don't want to jam it. into an index at the peak and then have. a 30% draw down on top of people which. often happens in IPOs cuz people get. excited it runs ahead of itself. But. they didn't do that here. There was fear.

that that was going to happen. So both. the the exchanges and the indexes, they. looked at this and they made some. modifications because the the other side. of the argument is it's so damn big and. important that it needs to be part of. the index. Right. >> Right. And so the reason the rules had. previously existed is because most. companies coming public were younger, earlier, less tested, less revenues, less profitable, all the things weren't. as important in the overall scheme of. things. So I think that they pioneered. some really smart things. It's worked.

well. it's traded well and so I think. that that provides a bit of a blueprint. for anthropic but just in in in terms of. the enthusiasm. is an alttimeter is a fidelity as a tro. an enthusiastic buyer of anthropic based. upon the things we know today around. profitability and model improvement and. revenue growth etc. Yes, everybody would. be pig piling in. everybody would be. trying to get into the top of the book. and you know uh the the last I heard you.

know again rumored that they would like. to get out this year on open AI. everybody knows that anthropic kind of. passed open AI on a revenue trajectory. but I will tell you open AAI's kind of. got its swagger and mojo back it's. coming out you know just today with a. whole new set of models we know GPT6. you know there's a lot of talk of that. coming out within the next 30 days a. whole new generation of models. I think their revenue has really ticked. back up. The most recent kind of rumors. I see on Twitter is around $70 billion.

text the year. So just as a reminder 70. billion may not be over a hundred. billion that's rumored and anthropic, but it's still twice uh you know where. where the revenue of SpaceX is at. So. can they get out at over a trillion on. that type of revenue growth being one of. the two frontier premier labs? I think. the answer to that is yes. Um, I'm not. sure there's a huge race between the two. of them to get out first. I think. they'll both go out when it's when it's. time. I think OpenAI has a little bit. more complexity just associated with the.

corporate restructuring that they have. to go through, etc. So, I would be. surprised if they go out before. Anthropic, but the fact of the matter is. I don't know. But today, as I sit here. today, Altimter would be a buyer at. scale and at size in both of those IPOs. at three trillion, are you a buyer or. are you a hey, you know, it's obviously. going to trade up and down and I there's. no rush because you I think were the one. who said on the pot or might have been. at liquidity live when I asked you point.

blank, hey, should retail get involved. in SpaceX? What's your thoughts? And you. were like, hey, listen, it's a 4% float, 5% float. It's going to trade up and. down, but you know, a year from now, it. might be trading at the same basic. price. It's it's going to be priced not. to perfection, which it seems to have. been, but you I think your position was. it's going to be priced reasonably. There'll be plenty of time to get in. You don't have to like, you know, panic. about getting your shares. Yeah. >> Yeah. I once a company's valued at over. a trillion dollars, like the get-rich. quick schemes are over, >> right? Like that you and I share a deep.

passion, Jason. We got to get retail. investors. We got to get the citizens of. the United States in on these value. creating opportunities earlier, right? The accredited investor laws are insane. that we have in this country and keeps. people from participating in these. things, but it is what it is, right? So, they're coming public at over a trillion. dollars. I still think there's a lot of. meat on the bone on SpaceX, on. Anthropic, on Open AI, but you're not. going to have things that are I don't. expect that they're going to be priced. in a way where you're going to get a 50.

to 100% durable bounce out of the IPOs. If so, that would mean they were. probably mispriced right into the IPO. But I do think that these things can be. compounders. They're going to compound. at the rate they compound revenue. And I. think all of these companies are going. to compound revenue at well over 30% for. the next many years. >> And 30% a year for just so people. understand that this is high growth in. public markets on very large revenue. numbers already. You know, growing 30%. when you have 100 million revenue is one.

thing. Growing 30%, you know, when you. got a 10 billion or 100 billion, you. know, this is this becomes a different. uh task. So let's talk a little bit. about these two companies, Chimoth, and. what the public's going to perceive them. as. Chat GPT seem to be the. public brand, the consumer brand for, you know, large language models. It's. the AI for, you know, people who are. doing their homework or mom and dad are. trying to fix the dishwasher, whatever. And then Claude took the lane of, hey,

we're going to be the one for corporate. And it did seem like OpenAI got very. distracted with Sora and you know Disney. relationship. We're going to make a puck. with Johnny I everything consumer. Then. they realize oh wow the revenue seems to. be an enterprise first. Is that going to wind up being the the. big mistake when we look at it? they. kind of gave the Google position, the. high growth position to Claude and. Anthropic and they took the Yahoo. position or do you think they'll catch.

up on the enterprise or maybe they. should just go back to trying to be the. consumer version? What how how are these. going to be positioned a year from now? How's the public going to look at them? >> The problem with enterprise revenue is. at some point the person that's spending. it has to see an ROI. I asked Fable five. high. >> and props new model. Yeah, >> anthropics new model. I first asked it, what is the lift of the S&P 500 earnings. per share growth since 2024 from AI? And.

they answered, oh, it's 50%. So then I. looked through it and I said, well, no, you're including the money that Nvidia. makes from selling chips to Amazon. So I. said, okay. I asked a different. question, which is, then what was the. EPS growth of the S&P 493? And the. answer was 9%. And I said, "Okay, well. that's different." And I said, "Unpack. that." And. the overwhelming majority of that was.

from pricing power. sitting on top of inflation. And then the other 3% was from buybacks. And so the answer as far as. all publicly available data was that the. actual ROI was somewhere between zero. and 2%. >> So I don't know. I mean I think that. enterprise looks really good. The. problem is that very smart investors. like Brad and Gavin and others at some. point will start asking companies what's.

your ROI? What's the actual EPS lift? And if the answer is, well, I don't. really know or I'm not sure. and you know, you don't necessarily have. the pricing power to continue to raise. prices. Enterprise is probably a little bit more. brittle because there are fewer buyers. and they're more demanding. Consumer on. the other hand then all of a sudden. becomes an incredible safe harbor.

because you have tens of millions of. buyers and having those two orders of. magnitude more buyers at a much smaller. price point inoculates you from the. vicissitudes of an ROI discussion. >> So it all really depends on what the. actual ROI is of this money being spent. I think that we're in the phase of just. being astonished, as Brad said, about. the scale of the revenue growth. >> Yeah. >> But at some point, you'd have to be an. idiot not to ask, well, who is paying.

you this? And can they sustain paying it. to you? I just don't know what the. answer to that question is. And at some. point, it may not be now, >> at some point, people will have to. answer that question. and you're. spending million dollars a year on. tokens. >> and that million dollar a year is. doubling and tripling and quadrupling. At some point you're going to have to. show an ROI that's. >> above the risk-free rate of return. otherwise you're going to have um some. angry investors on your hands.

>> and our discussion here for the last. couple of weeks on the pod has centered. around that and the industry has. responded on the place where all the CTO. CEOs and capital allocators hang out. which is X.com formerly known as. Twitter. Here's Pine, the CTO of Uber. And so when you ask like how are they. getting. how are they getting the ROI out of. this? People are now bringing that. conversation front and center and. they're explaining it on X and he talked. remember Uber was also the one that ran.

through all their tokens in the first. quarter. So then on the other side of. the business which is legal, operations, marketing, customer support, HR and. procurement which he lists here. He says. in this you know today 99% of our. engineers use AI tools. Okay great right. it's everybody's you know doing vibe. coding and has coding assistance. Uh. more than 70% of pull requests are. attributed to local or cloud agents. Our. engineers have built 200 agentic skills. So how are bringing agentic AI beyond. engineering and what they've decided to. do is essentially he talks about these.

agentic pods and this to me seems. directionally how this should be done. which is you find engineers and you uh. as as we uh talked about forward. deployed engineers fancy way of saying. put an engineer put them into. departments and have them work with the. department heads who understand systems. thinking how their process is done and. um he uh he says he's making basically. long and short of it is they're making. massive massive progress on the. operational side of the business. So.

Brad, you're pretty familiar with Uber. and have been a long supporter of that. This is a company that knows how to. deploy technology pretty well and. they're an operations machine run by an. operations machine. DAR, >> they should report the EPS gains. attributable to AI. >> Yeah. Well, I mean, and this first step. seems like they're really being. thoughtful about this first. Hey, this. token spend got out of control with the. developers. we're going to need to pause. this and look at it. And then second, here's how it's going to lower cost and. create more efficiency. So Brad, >> let's talk about that side of it. Not.

just token maxing with the developers. hitting the slot machine of like, okay, let's see if this pull request and let's. see if if this produces the right code. or not to these departments in a more. strategic way. It's not just the person. who works in HR, you know, using cloud. code or perplexity or whatever and. trying to vibe code something. This is. hey we're sending engineering in to work. with your top systems architect and. we're going to you know try to find that. ROI. Yeah. >> Yes. I you know first I would say. Chimath is right. The only question is.

on what time frame. There's no doubt. that there there's a lot of money being. spent today that is in the experimental. bucket right where I I think there. probably isn't direct ROI Chimat to your. point but I think we're so early nobody. cares. I think we're so early in terms. of enterprise adoption. Remember the. total addressable market here is every. single small, medium, large company on. the planet. And so we've never seen. revenue growth like this because we've. never seen a TAM like this. And if you.

look at the distribution of revenues. across these businesses, it's not like. it's concentrated with four or five. customers. There are millions of. customers independently economically. making the decision that is rational for. them every day that it makes sense like. Pine at Uber and of course they're. trying to find things on both right now. mostly the cost side cost takeouts to. justify the investments that they're. making in you know in tokens but I think. we're on the verge of breakthroughs in.

intelligence that's going to. dramatically change the revenue side of. the equation for a lot of these. businesses breakthroughs in life. sciences breakthroughs in in product. innovation etc where they could not. divorce themselves from this even if. they wanted to. For example, Jensen Hang. has talked many times that all of his. design work all of his design work now. at Nvidia is using AI to design the next. generation chip. The machine is building. the machine. So you can't get rid of.

that even if you wanted to. and tiny. intelligence advantages at the frontier. where he sits are required. Like there's. no way I don't think that Jensen is. going to use anything but the best. models that he can to build out those. capabilities. So I just think that we're. not going to see that in the next few. years. You're going to see it under the. hood, of course, but that occurred at. Snowflake. There was tons of. optimization that occurred at Snowflake, but the revenue continued unabated. their revenue growth continued under. beta because they further penetrate.

penetrated use cases f further. penetrated the enterprise. So let me be. provocative here. If these guys end a. year over a 100red billion, I think that. they're on a revenue trajectory that. they could 3 to 5x again next year. We've never seen anything like this. Never. >> You're saying 100 to 300. 100. And Jason, like you and I have talked. about this. Our minds were blown. If a. company could go from 100 million Yeah. to 300 million, we're talking from a 100.

billion to 300 billion. 200 billion of. incremental revenue is incomprehensible. in the history of Silicon Valley. Okay. And just the fact that we're even the. world in the history. >> Yeah. In the history of the world. So. the fact that we're even talking. anywhere close to this tells us. something different is going on here. I. think the thing that's different is that. intelligence is the largest TAM we've. ever seen in the history of the world.

These guys are penetrating it. So yes, the super sophisticated companies, the. 8090 and Chimath are helping optimize. their token spend that are early. adopters. 100% that's occurring, but. it's not really changing the trajectory. that the Frontier Labs are on. >> Yeah. And one of the interesting things. about this technology that's really. unique, we talk about intelligence on. demand. When you would make a piece of. software or you had some technological. innovation, it would typically acrue to, I don't know, one group of people in an.

organization. You know, maybe two groups. of people, right? Excel comes out. Okay. Yeah, the accounting department's having. a field day with it, but it's not really. affecting human resources or marketing. Okay. Yeah, maybe it trickles down. eventually. Every single person in every. single organization is playing with. these tools. So if everybody's playing. with it, everybody's trying to apply it. all at the same time. It's kind of like, you know, you got a thousand person. organization. People are spending 200 a. month. Okay. Yeah, Chimath, they double. it every, you know, x number of months. Okay. Yeah. Now they're spending $400 a.

month per person. Okay. They're spending. $5,000. Well, if the average salary is. 100 150k at this organization, it's only. an incremental 3, four% on top of their. salary. So the way I look at it is did. it make that person three, four, five. times more effective at their job? And I. think the answer is yes. So that's why. there's so much token maxing going on. And it's also a bottom up type product. You can just get into this product for. 20 bucks a month and you know no CIO or. CTO is like oh no you can't spend 20. bucks a month at your corporate card for.

this technology. So it when a bottomup. technology hits everybody at the same. time that's what would explain this. revenue ramp that we're all having a. hard time adjusting to. It applies to. every single person like who is it. impacted by the technology is my. question to you Chimoth like in what. organization you're working with with. 8090 is there a department that says. yeah the intelligence on demand not for. us we don't need it. >> well it's less it's less about being. dismissive that way it's more that. regulators and other people won't. necessarily allow to use it the way you.

want. >> okay so finance HIPPA yeah there's HR. data you're not allowed to to to put. that to work just yet what I'm finding. is. once you start using this and getting. some gains it's very addictive and we. were sitting here Brad I don't know. maybe in January and I got that open. claw bug. >> and then you know I started playing with. this Hermes Hermes agent which is not a. French company by the way they just use. you know French names is Nuvo research. or whatever it is I started playing with.

that it's a very peculiar piece of. software but it's very open piece of. software so I went to open router I got. my own keys I've been playing with GLM. Then uh I talked a little bit about. BitSensor on the program known as Tao, dollar sign TAO. It's a it's a crypto. project. Somebody who is creating a. subnet that is putting GLM 5.2 and other. models available at really cheap prices. So I all of a sudden experienced because. they gave me an API key having my token. cost go down 95%.

And when you have unlimited tokens as an. exercise, which is going to come to. everybody, eventually everybody's going. to learn how to drop the price by 95%. And it's going to happen as well because. people like rock with inference. This is. all inference, right? This is what. people are using. They're they they're. they're using. inference to do this. Well, inference is. being impacted like three or four. different ways. The software is getting. better. Open source at the same time. you're going to have distributed. networks like Tao and uh you're going to.

have better you know chipsets from Grock. and Cerebras etc. All that's happening. at the same time once I got down to 95%. cheaper I started setting my agents. instead of doing daily runs to doing. hourly runs then I took my agents from. doing one task and I broke them up into. three agents and have them doing three. different things on the hour. And when. you start doing hourly tasks and then. you wake up in the morning and like 14. jobs have been done, you're like, "Wait. a second. This is completely different.".

As one example, I have it has all the. all-in episodes, all the This Week in. startups episodes, and we set these. crown jobs to go find what the new. trends are in technology. I have a trend. spotting agent running every hour, >> informing me of the top three or four. trends, and I just give it words. Really. does change your thinking. when costs go. down, what do you think the tokens are. going to cost, Brad? And you know, next. year, >> yeah, we've se we we we've seen 90%. reductions in the price to tokens for.

each of the last two and a half years. We've talked a lot about Jeban's. paradox, which I think you you're. referencing here, which is you're going. to use a hell of a lot more when it. happens. I think the central debate. right now in AI is the one that Chimath. keeps pointing us back in the direction. of which is for 18 months since the. deepseek moment right when the deepseek. moment happened the markets fell 40%. And there was a reason for that. Many. started arguing that the frontier models.

were screwed, that open- source was. going to kill them, that they were. closing the intelligence gap, that model. routing was going to make it easier. easier to route these tasks to cheap. tokens. But despite all of those. arguments, and now we're 18 months into. this, and I had this back and forth with. Gurley a lot. I love open source. I want. all the competition in the world. Let's. be very clear. But despite all of those. arguments, the facts in the field are. just the opposite. The share of economic. value, right? There's this quote,

there's this tweet this week from Jesse. Zang that we ought to pull up here. You. know, the economic value, the share of. wallet is actually increasing to the. Frontier Labs while the share of tokens, these commodity tokens is obviously. going up, you know, to the other guys. And I had a little back and forth this. week with Nikesh on this kind of trying. to sus out why is that the case, right? Because what people would have thought. is, oh, cheaper, pretty damn good. 90%. is good enough to do all these tasks.

that you're talking about, Jason. So, nobody's going to use the anthropics and. the open AIs of the world. But despite. that, it looks like their share of. wallet has gone up. >> I think it's not that. I think it's more. that when the iPhone was a novelty, everybody would keep upgrading because. you expected that the new price was. worth it. And then at some point there's. a moment and you can debate when it. happened where people said, you know. what, I'm just going to keep the old. phone cuz it's good enough and I just. don't see the difference. And I think. that there's going to be a moment like. that. Like when I use Fable 5, the.

problem is that it's nerfed on a bunch. of things that I would normally. research. You know, I was with somebody. this weekend and he was telling me about. some health thing and I put it into. Fable and I was like, it won't answer. you. I'm like, okay. So, I think that. everybody will get to a point, they'll. get to it at different times where they. just say, you know what, like it. shouldn't really matter what model I'm. using. If I get an answer that I think. is reasonable and I can kind of go about. my day separately. I think when the. corporate CFO gets involved, it'll be an.

entirely different conversation. altogether. I think that what I can tell. you after this UN commission that I. joined with Ben off and Jensen and Brad. Smith, there is not a single country in. the world that is not trying to figure. out its own sovereign AI strategy. And I. don't think they believe using a closed. source American model is the answer. And. so, you know, we I think we have to keep. in mind there's trends. One is just. geographic penetration of humans and. there are still many many many more. people that don't use it than do which.

is an upside and an opportunity for. everybody. >> Mhm. >> And then the second is there is going to. be the experimentation as you said that. needs to transition to ongoing. repeatable usage. and then the third is that all of that. then needs to plug into the existing. regulatory infrastructure that we use as. societies to run the world. And I think. when you put all of these things. together, it's not clear to me who wins. except that you're going to have a lot. of diversity of choice. Certain.

countries, I can tell you after this. week, >> have no desire to subjugate themselves. to any technical risk and so they're. willing to spend the money to have their. own. Now we can argue and debate whether. that country has any chance but they. would rather take an open source model. like Nvidia's actually and stand up. their own stack soup to nuts for their. own people and their own companies. inside of their own country. >> and if the models are 99% as good or 95%. as good there's going to be a claim that. some countries make which is it's just.

good enough. >> That's the question. That's the. question. And then separately there are. companies who will not have the earnings. growth to justify this without going on. some long protracted carveout of cost. And most companies, you know this, they just don't do it. They don't have. the nerve to do it. They're not capable. of it. You know, you wrote that famous. essay to Zuck. He was pressured into. finally doing it. Absent to very few. companies, most people just allow the.

problems to compound. So, I just don't. see a world where when you get clobbered. over the head, you don't look at other ways of just. displacing cost. And if it's like Coke. Pepsi kind of a thing and Pepsi is 1/. 1,000th the cost of Coke, I don't know. I just think it's a it's a risk that I. think has to be managed in the. perception of the market participants. and the underwriters. To add to that, uh, Brad, just open source is very hard.

to implement when compared to just. firing up Claude and having Claude. already approved in your organization. The number of steps it took me in order. to, and I I'm pretty familiar with. technology. It took me hours to. configure my new setup to get onto this. bid sensor network to get open router. going. And to your point, Jimoth, it. does dynamically route now. So, I'm. dynamically routing and I'm, you know, GLM 5.2 too. And then if I fall back to. Claude, but which Claude am I going to. fall back to? And here's another piece. of evidence to your point, Schmoth.

There are some organizations that just. aren't capable of this. They don't have. the the team that, you know, does this. naturally. We just talked about the CTO. of Uber. Now, let's talk about another. CTO. Andy Fang is the CTO of Door Dash. Shout out to Stanley. And so he, as you. can see here in this uh tweet, I a lot. of people listening to All-In over the. last couple weeks are coming out and as. I said explaining what they're doing to. address this exact issue. He says, "Hey, with our internal coding benchmarks, we're able to confidently in introduce. openweight models into our AI code.

review without degrading code quality. Have the frontier model fable from. anthropic to do the hardest work, delegate lower level work to Kimmy 2.6. and they are now releasing their. benchmark." So another group releasing. their benchmarks and saying hey we know. this is an issue the CTO has been. charged to your point Chimath again CFO. says hey make sure this is profitable we. get the ROI they put that on the CTO. here's another CTO from another leading. tech organization that knows how to.

implement this yeah. >> the really interesting thing we have to. forecast right now is what happens in an. earnings miss. and I think what happens in a in a. moment where for whatever reason maybe. there's just an externality that there. are a series of earnings misses. >> Where are people going to look? And I. just think that people find it very. difficult to lay off other people. I. think it's much much easier to cut other. costs. And I think that the more. successful these companies get in a very.

quick amount of time without really. proving the ROI, I just think the bigger. the risk is. It's complicated. the game. on the field when you're working with. these enterprises and just trying to. explain it to them is I think that. they're they're getting smarter quickly. is what I would say. >> I would just say I I I think that. Chimath's absolutely right about the. sovereign uh stacks that are going to. get built around the world. This is not. either or. We are going to have open. source and we are going to have frontier. intelligence. Um, the preponderance of. the tokens today are already shifting.

toward cheaper, lower uh uh uh lagging. models out of open AAI or lagging models. out of anthropic or or the other. frontier labs that are out there. Obviously, we you know, we talk about. those two. SpaceX has released an. incredible model, you know, in the last. two days. Meta's out with, you know, a. terrific model today. So, Gemini is. still in the hunt. So, there are lots of. choice. The meta thing was really. intense because I thought okay you know. we talked about the game theory which.

was Mark should scorch the earth with. open source. I think they flubbed that. play. >> but then I think he is now said he's. going to create a price war and so if. you look at the tweet or the quote there. was a post Jason I don't know Nick if. you can find it. >> I got it. >> announcing it he was basically like hey. guys I'm going to give you the same. quality at like 1/100th of the cost. Now. again, >> there's a lot between here and there. There's a lot of enterprise distribution. that's required and you know this. there's been a couple of misfires.

before, but I thought it was interesting. that the vector of challenge was on. cost. >> Yeah. Here's the Mark Zuckerberg tweet. Just sorry I queued up for you there, Brad. And he's at D, that was his old. handle back when he was in college, fd. And he's done more tweets today over. this Muse Spark announcement than he's. done in his history. So he's getting. into the X.com conversation. Quote, "Today we're releasing new Spark 1.1, a. strong agentic encoding model at a very. low price. It's available through our. new meta model API and in meta AI." So.

he's coming out saying, "Hey, we got the. strongest agentic tool here. Please come. use it." He also wants to have his own. essentially, you know, he he wants to jump into not. the hosting space, but he wants to. provide tokens as well. So again, I. think we're going to have a tremendous. amount of selection. The competition is. great for America, but I think if you. look at the things people are doing, let. me give you an example. The premium. workload, Jason, you talked about.

summarizing a document may take 20,000. cheap tokens to do. Of course, shoot. that to a lagging model or an open. source model, but if you're talking. about replacing a software engineer for. 2 hours, that may take 2 million. expensive tokens. And the consequence of. using something that's 95% as good is. really high, right? Because you have a. longunning task and if the task breaks. early or it breaks in the middle or. breaks at the end, there's a huge cost. to that. So. >> you still burn the tokens, right? You.

and back to this analogy I was using, they're pulling the slot machine and you. lose. >> and the time and the compute. So if an. AI agent is replacing a $200 an hour. consultant, right? Take that as an. example. So, three consulting firms, they're competing. They need the. smartest consultant. It they're charging. 200 bucks an hour. The difference. between spending three bucks on a cheap. model or 15 bucks on an expensive model. to replace a $200 an hour consultant,

it's just irrelevance. That inference. cost difference is irrelevance if you're. getting something that's bulletproof for. 15 bucks. And so, I think that's what. we're seeing play out. The best evidence. for all of this is just revenue growth, >> right? We can sit here and speculate all. day long as to revenue, not from. Anthropic and Open AAI, but from their. customers. >> I'm no I'm talking about what is. anthropic revenue growth compared to. OpenAI compared to the open source. models. Millions of independent actors. are choosing every single day. The open. source companies are growing, right? But.

they're growing selling something that. is really, really cheap. And there's a. there there's room in every single. market for premium products, for. mid-tier products, and for commodity. products. And I think we see a lot of. this token growth. People are. speculating that the that the. intelligence gap between that commodity. stuff and the frontier stuff is going to. collapse to the point that people won't. pay for the frontier stuff. There is no. evidence of that on the field today. It. may develop over the course of the next.

couple years, but it's not on the field. today. >> Yeah. Yeah. And just to give people an. idea, we we keep mentioning what. sovereigns are doing. To give you the. specifics on that, the UAE very famously. has their own. uh Abu Dhabi Technology Innovation. Institute shipping Falcon. You probably. have heard about that. The Saudis have. Humane and they're doing their own. models that are Arabic LLMs. And then. this week, Japan is investing$6 billion. dollars in a consortium. It's called the. Neoterra.

Neoter. Neo T r a consortium and they're. doing that and skipping ahead to. physical AI i.e. robotics. Okay. Joining. the conversation here, the one, the only. Saxy Pooh Sax bringing you into the. discussion talking a little bit here. about the debate that we started here on. the podcast getting ROI from tokens. Where are the tokens going to acrue to. open source versus the frontier models? Bunch of CTO's chiming in on X this week. in the last couple days. is in fact.

talking about how they're managing. intelligent routing first to open source. models then falling back to Fable and. the Frontier models. How do you think. this is playing out? And if you're an. investor in the space, how do you think. about the frontier models and their. growth when you have uh you know CFOs. coming in and saying hey justify this. cost and do you have a cheaper solution. and what is that cheaper solution? Well, look, I think that enterprise CTO's.

would like to shift their token. consumption to cheaper models for the. obvious reason that that would be more. efficient and they are seeing their. compute cost or their token cost is. skyrocketing right now. So, everyone's. trying to figure out how do we put the. brakes on this or at least control it, you know, make sure we're getting ROI. You also have the AI sovereignty issue. that we discussed last week that Alex. Karp talked about where they're worried. about giving up the secret sauce or the. alpha in their business to a frontier.

lab that may one day be competing with. them. So there's no question that. enterprises would like to diversify. They would like to get off of these. frontier models when they can. The. problem is I think in most cases they. don't have the technical ability to do. it. I mean Coinbase figured out how to. do it. Door Dash figured out how to do. it, which is to say they built a token. routing system, a layer of middleware. that allows them to sort of send. frontier task to frontier models and. non-frontier task to more mundane.

models. But I don't think your average. enterprise has the technical capability. to do that. So I think this is a case of. the spirit is willing but the flesh is. weak. I mean they are willing they would. like to diversify off of these closed. models but they are unable to do it and. so this is why the share of wallet of. closed models it actually increased. I. think that opensource went from 19% last. year to 11% this year. So open source as.

a share of enterprise spending is. actually decreasing. Now I don't think. that means that usage is decreasing. I. think usage is skyrocketing in both. these categories. It also may be the. case that because the whole point of. using an open model is you just pay for. the compute cost. You don't have to pay. a lab. So it may be the case that it's. hard to measure that usage in terms of. spend. But nonetheless, I mean anyone. who's saying that these closed models. are gonna lose or are somehow losing,

you're just not seeing it in the data. Like Brad's saying the revenue is. skyrocketing and I think the most you. can say is that enterprises that are. technically capable would like to. gravitate towards hybrid architectures. but at the same time it takes technical. expertise and it is just phenomenally. convenient whether you're a developer or. an enterprise just to go with the. frontier labs and that's why their. revenue is skyrocketing. >> It is the easiest choice. It's the most.

refined Yeah. most refined product's. there's Yeah. And there's one other. thing here as well and this was. discussed in a really interesting blog. post by the founder of Decagon which is. enabling. AI powered customer support for. enterprises and what the founder said is. look open models are great when you know. exactly what you're trying to do why. they're smaller cheaper models but you. have to do post training you have to. have the data set and you have to know. exactly what you're going to use them. for. Totally. But if you don't know.

exactly what you're going to use them. for, you want the most powerful general. intelligence that you can get. Right? So. what he said is that for mature use. cases, yeah, you want to go open, but. for immature use cases, which are all. the new things people are discovering. right now, you're just going to want to. use the most capable general model that. you can. And then once you figure out. what the workflow is and what the. workload is going to be and exactly what. you're trying to accomplish, then you. can use a small highly trained model. And I think he said.

>> optimize in the post to get the game. >> for customer support. Your model doesn't. need to know physics, you know, for. example, >> and so you don't need that capability, but enterprise are still trying to. figure out exactly what all these. workflows are going to do. So I think. that's another factor which is to say. that you know it depends on the use case. and how mature that use case is and you. really want the most powerful frontier. models that you can at the discovery of. all the potential for the technology.

>> Yeah. >> And then let me just wrap up then. there's one other interesting post that. I saw was by Nesh Aurora who also said. that what he's seeing is yeah. enterprises would like to diversify. They would like what he called model. fungeibility. They would love to. commoditize these models, right? And. just hot swap them. >> Yeah. Headless is the term being used, right? Yeah. >> Yeah. That'd be ideal for enterprises is. you sort of swap out the model for the. cheapest one that gets your task done. But then what do you do about memory? What do you do about context? What do.

you do about history? And what he said. is no one's really figured out a way to. abstract that stuff away from the model. yet. And again, this goes to the. technical challenge of creating this. middleware layer that would do the most. efficient token routing. It's well, you. know, it doesn't work unless you can. make all of that context and memory and. history fully portable to the cheaper. model that you want to basically hot. swap to, >> which means you have to have some. technical ability sachs. And the people. with technical ability, the tip of the.

spear, the 1% of people deploying this. technology are starting to figure that. out. Here's another proof point and some. more evidence. This is Ali the founder. uh of data bricks I think a company. you're very familiar with Brad and what. he realized when you start taking apart. the harness and you start looking at the. skills you look at the memory and all. this acruant that you put around your. tasks he said we find that the same. model using the same model not using. open source versus open AI or or claude.

we found that for the same model the. choice of harness can significantly save. costs by about 2x. So they found with. GLM 5.2 that this performs extremely. well and that their tasks literally are. getting cut in half using the same model. but with a different harness. And that. rings true to me. I once you've built. one of these agents and I was talking. about one earlier I'm running every hour. on the hour to find trends. I asked it. to please start optimizing it. And when.

I optimized it, it was like 80% less. token use. And now in these apps, you. can go to your analytic stacks and you. can actually see your token use by hour, by job, and across which models you're. using. This is really sophisticated and. hard for for a consumer to do of the. technology, but it's definitely a trend. >> So with that harness that he was using, is that something they built in house? >> Yes, I think it's um. >> Yeah. >> Okay, got it. So they they basically. creat.

>> Yeah. in front of these and that it can. multiplex different harnesses and models. for different tasks. So he's not only. routing to the right LLM, he's routing. to the right harness and people don't. even know what skills are. People don't. even know what the memory is at this. point there. That's all abstracted into. the claw product or the perplexity. product etc. Yeah, there'll be a massive. business. There already is. All these. inference clouds, you know, the base 10s. of the world, the fireworks of the. world, every single hyperscaler in the.

world is going to do this. They're all. going to provide, you know, tools that. allow you to achieve some level of model. fungeibility. The big question is at the. end of the day, we're going to have it's. going to be very heterogeneous, but what. is the mix between these two? I again. think the TAM is so damn big here that. you're going to have huge open-source. use cases, sovereign use cases, etc. You're going to have plenty of room for. the frontier labs. I Let me throw. something out. I'd like to get your. opinion on. you know to a certain extent. there's this implied assumption in the.

world that uh there's going to be this. convergence of intelligence right and if. you look at the benchmarks today seems. like everybody you know on the. benchmarks they are converging but yet. if you look at the revenue distribution. it's not converging at all one of the. questions I have will the model router. itself be smart enough to overcome David. the inherent intelligence advantages of. the generalized of the frontier labs the. non One consensus argument might be that. intelligence is not converging at all.

that c super intelligence becomes fully. self uh uh uh you know recursive and as. it becomes recursive you actually extend. the lead because the smarter your model. gets the more revenue you get the more. compute you can buy the more compute you. can buy the better the model is that you. can build so I think there's a chance. that over the course of the next 2 to 3. years as we take on much more complex. agentic tasks asks that the distance. between the frontier and everybody else. doesn't converge. It actually extends.

We shall see. But, you know, I think. there's this implicit assumption in all. the arguments today that everything's. converging. I'm not I'm not sure that. we've really run that to ground. Another. piece of evidence to put in uh to this. mix. I interviewed Anton, the CEO of. Lovable. Lovable is an app that or a. service that allows you to vibe code, you know, different pieces of software. They've got a really interesting take on. that. They went from 100 to 600 million. in revenue over the last two years. They. went from zero to 350 in the first two.

years of the company. Products been out. I think roughly for like 30 months. Then. I also spoke to uh the CEO of 11 Labs, Matti. And I asked both of them point. blank, are you guys uh you know your. major customers of you know the the. Frontier models? Yes. They're spending. tens of millions of dollars with those. frontier models. I asked them, hey, are. you concerned about data leakage and. them compete, you know, releasing. competing products? 11 Labs is doing. voice and obviously Claude code, you. know, is an obvious competitor to.

lovable. Are you going to make your own. models? Both of them said that they're. working essentially on their own models. Those are major customers of the. Frontier Labs who they want to get off. of the Frontier models and they want to. have their own proprietary model. The. the ability to create verticalized. models is getting easier and easier. every six months or so. So that's going. to be another trend to look for is these. verticalized models for voice, verticalized models for building code. And uh we're going to see uh people stop. using the Frontier Labs and these are.

major major eight and nine figure. customers. I think they're going to just. run for the hills and only use the. Frontier models. >> But Jason, the counterpoint there is 11. Labs. I love Maddie. >> Yeah. >> Do you really think he's going to use an. inferior model? He's got to be have the. best voice voice agent in the world. And. if the best voice agent in the world is. given to him by using the Frontier Labs, can he afford in a competitive. marketplace to say, "I'm going to use. the cheaper version, the thing that I.

built for myself, even though it's not. as good as the other thing." If he. builds something better, I totally agree. with you, which is what he believes he's. doing. He believes he's making a better. version. Yeah. So that's the question. that I just, you know, put on the table. whether or not you're going to see this. convergence, whether it in fact is that. easy. I don't think it's that easy, but. we shall see. >> Okay. >> It may come down to how discreet and. sort of predictive the use is. So like. Decagon, the customer support AI. company, they said that 90% of their.

usage now is being sent to open models, but those are open models that they've. had the opportunity to post train on and. do a huge amount of customization based. on all of their learnings and all of the. data that they've gotten. So again, it. comes back to maturity of the use case. If you know exactly what you're trying. to do, it's probably easier. But, you. know, I don't think that's most. enterprises, though. And maybe there's. going to be a pattern where, you know, all the immature use cases, which is to.

say, all the things you're figuring out, you're just going to want to use the. most powerful model possible. And then. once it gets really well defined, maybe. you start moving some of those workloads. to post-trained open models, >> purpose-built models. Yeah. >> Yeah. Purpose-built. Yeah, it could be. something like that. >> That's kind of what's happening with the. people who are the tip of the spear. They're working on the routing of the. jobs. They're working on the harness and. they want to be independent and have. that AI sovereignty we talked about last. week. Speaking. >> well, but just to take on Brad's point.

for a second, I actually agree with what. I think you're saying, Brad, which is. the market today seems to be pushing. towards duopoly or it has become a. duopoly. Certainly measured in terms of. revenue. If you're to look at market. share based on token revenue, there's. only two companies making meaningful. revenue. Anthropics at what 60some. billion ARR open AAI at 40ome billion. ARR. I don't know if anybody else even. registers and it may be the case that.

the more tokens. that Anthropic and OpenAI produce, I. mean we got to remember every token that. they're serving up is on behalf of a use. case, right? So they themselves are. learning from that and they're getting. better at then providing whatever. offering that is and so who knows like. the gap may be growing. A year ago it. seemed like we had five major labs you. know now it seems like there's a top two. and then everybody else. So I mean look. I could see AI easily becoming another. tech market that becomes a duopoly.

>> which which by the way is the trend. The. historical trend is like monopoly or. duopoly in most tech categories for. better or worse. >> Yeah. In this case though, however, we're using revenue as the metric to. determine the winner. Keep in mind when. you're doing open source, those are dark. tokens. Those don't come up as revenue. So, we don't know the utilization that's. occurring at Door Dash when they're. using an open- source model. We do know. their fable and their anthropic spend, right? And because we see that in the.

anthropic revenue ramp, the more they. deploy these things on their own. hardware, using commoditized hardware, using the NeoClouds, you don't see that. It doesn't come up as revenue. It comes. up as free. The only thing you're paying. for there is the hosting cost, you know, and that's that will come up on Nvidia's. balance sheet. So the gains you'll see. there will be Cerebrris, Neoclouds, Caruso Cloud, etc. So keep. just keep that in mind when we're having. this discussion. Let's talk a little bit. back to sovereignty here. The CCP.

said that they might or there's a report. out according to Reuters. Reuters. generally does a good job of this. They. dropped a couple of anonymously sourced. reports about AI in China. And these. were published about 15 minutes apart. the big scoop that CCP officials, Chinese Communist Party, are reportedly. considering restricting overseas access. to China's top models. So two Chinese. regulators met with Alibaba, Bite Dance. and Z.AI. They are the ones who are. doing GLM 5.2 that we keep referencing. They're discussing limiting access to. the top open and closed models outside.

of China. Why are they doing this? Well, they're they're making uh any theft or. leaks of AI research a national security. offense and they want to control who can. fund Chinese AI AI labs. And we saw this. with Manis which was a Chinese company. tried to go to Singapore. the CCP pulled. those employees from Singapore back to. China. And so here is their main. concern. The quote is that they're. concerned about Mythos. Chinese.

authorities are deeply worried about the. potential for Mythos to exploit software. vulnerabilities and that Washington. might deploy a model against Chinese. interest. Saxs, last week I proposed the. reverse to you in your previous position. as Zar of AI. Do you think the United. States should be banning those models? Now we have the opposite. China saying. potentially according to these reports. allegedly that they might restrict them. So explain the game on the field here. If you're going to look into what. China's thinking, why would they want us. to not have those open source models and.

and how is this chessboard development? >> Well, last week I explained why it would. be harmful to the US to ban open models. So if you're China and you want to harm. the US, maybe you would want to. I mean, it does kind of make sense. >> because our our companies are benefiting. a lot from all this R&D that they're. doing. Now, at the end of the day, I. think the story is probably a little bit. overstated. I think there are a few. Chinese models that were open source. that have gone closed source, but I.

don't think they're all I'd be. surprised, let's put it that way, if. they all went closed. So, for example, the number one model in China, as I. understand it, is bite dances model, which is already closed. That's kind of. like their chat GPT equivalent and it's. always been closed. Then you've got. Alibaba's Quen, which was open and now I. think is going closed, and ZepO, which. has GLM 5.2, too, which we've talked. about a couple weeks ago because it.

seemed to be catching up to what was. then commercially available as the. American frontier at certain tasks. They. I think are going closed too after. having been open. And so this is I think. the tactic is you stay open until you. catch the frontier or you get close to. it and then there's a really compelling. incentive to go close because you want. to capture all the value for yourself. >> which by the way is exactly what Sam. Alman did famously at OpenAI. Not only. did they go from a nonprofit to a. for-profit, they went from open models.

to closed models. So, it's exactly. paralleling what Sam realized 3 years. ago. Yeah. >> I mean, in a way, that was what I think. Meta's original strategy was was that. Llama was going to be open, but then. they actually they've sort of backed. away from open a little bit. But this is. kind of an obvious strategy, right? is. is that if you want to catch up, you go. open. Because by the way, you're not. going to make any meaningful revenue on. on closed anyway because you're not. close enough to the frontier. So why. would anyone buy your product, but if. you go open, you get the developer.

community on your side. So. >> and you get utilization, more people use. it, which in AI gives you reinforcement. learning. Yeah. Sex. >> Well, having having spent some time in. DC this week, I and and and talking with. both the White House and Treasury, etc. on this topic. What I can tell you is. while there may be some, you know, debates about regulation of US models, the one thing there's absolute agreement. on is doing everything to stay ahead of. China. And, you know, and and the.

president all the way up to the. president very interested how far are we. ahead of China? What are the things we. need to do to stay ahead of China? It is. a unifying force in Washington. And the. idea that we were going to kind of take. our frontier labs off the field, off the. playing field while letting Chinese open. source models run free, you know, and on. top of that distilling our models. I. will tell you GL GLM 5.2 has watermarks. from mythos all over it, right? So we. know they were distilling, etc. And I. think the US government's going to take. steps against distillation, which they.

should do. So I think that you know. China doing this in some ways I don't. think it hurts the United States. The. United States can spin up open source. models. We've got Reflection spinning. one up. Obviously we got the good work. going on at Nvidia with their open. source models. The labs I've talked to a. couple of the frontier labs about open. source models. I said why aren't you. guys making open source models? They're. like there's not a lot of demand for it. If there was a lot of demand for it we'd. make it. And so I think the US is in a. good position. And I think this is. probably more chess playing by China.

than actual threats because it would. hurt them a lot more than it would uh. hurt us. >> Yeah. And then to just back up your. point, Saxs, about when you're behind, go open and then once you catch up, start tighten things up. That's exactly. what they did with Android, right? Google released Android. At a certain. point, they were like, in order to use. Android in the license, you have to. include Google Search, you got to use. Google Drive, you got to use Chrome. and. they started tightening it up. So, it's. not really an open- source project at. this point. >> Just, by the way, I think the absolute.

best thing that could happen. >> for America in terms of winning the AI. race against China is if China somehow. sprouted their own doomer community. >> Yes, >> we need uh like a Chinese yud over. there. >> We got to get their poom up. We got to. get their poom up. >> Exactly. We need a lot more people over. there freaking out about, you know, job. loss or RSI or whatever. >> Yeah. >> That'd be the best thing that could ever. happen to us is if they start cracking. down on their labs in the same way that.

the doomers want to do over here. >> Yeah. >> Brad, let me just say just one comment. I mean, look, I I agree with you that. >> from the president on down, everyone. wants to win the AI race. And in fact, that was, you know, in the big AI policy. speech the president gave about one year. ago. That was the whole thrust of the. speech was declaring that we were in an. AI race and America had to win it. I. think the big risk is more that and this. would not be at like the top level. You. know, I think if the president could. make every single decision, it'd be.

perfect. The issue is at a lower level. in the bureaucracy, do people somehow do. things that are counterproductive? Maybe. they think it's going to help us in the. race against China, but they end up. doing something that's hamfisted, they. just like ban something or without, you. know, really truly understand all the. implications of it. So, I think there's. no question that the administration. wants to win the AI race. The president. definitely does and at the top levels. they will all make smart decisions. The. question is whether at lower levels of. the bureaucracy, you can get mistakes.

being made. And then you have the. influence of Congress, whatever they. want to do. Those guys, they're more. responsive, I think, in a way to like. the doomer community that's creating a. lot of political pressure right now. >> Well, and the throttle, you know, paradoxically, to all of this might not. be the software, might not be the chips, it might be energy. Yeah, Chimath. I. mean, when you look at your data center. projects and the other ones that are. going out there, if we need more tokens, if people need more inference, we have a. gating factor in the United States, which is which is energy. There's a an.

analysis that my team put together which. I think is quite staggering. If you just. look at the load growth that's expected. between now and 2050, we are about three entire California's. worth of energy short. And that's just. assuming regular consumption of devices. and cars and fridges and televisions and. computers. So yeah, we have a we have an enormous. problem in the United States with. respect to electrons.

>> Yeah. And if you put Taiwan into the mix. here where the chips are coming out of, I had a really big wakeup call and there. was a Wall Street Journal article about. this. The amount of LNG, which is what. Taiwan runs on, is like they have two or. three weeks of it. China decides to. blockade Taiwan, they're going to run. out of energy immediately. So this is. energy both in China and Taiwan and in. the United States. It's all dependent on. that. We have to get nuclear running,

more solar running, more batteries, more. of everything. And uh that is obviously. a regulatory challenge here in the. United States. All right, let's talk. about your time in DC. Brad Gersonner. went to DC, everybody. And uh huge. huge congrats, Brad. you've been uh. harping on about this um you know uh. accounts now called Trump accounts, the. Invest America accounts and um tell us. what happened in DC this week cuz I.

think you finally have the number one. app in the world Trump accounts is the. number one app in the world. Congratulations and a bunch of. announcements. So what what what's the. contours of the announcement and uh. maybe you could take us behind the. scenes. There it is. Trump accounts, the. official app number one in top. downloads. Your kids can invest in the. future. >> This has been, you know, a four-year. mission in the making thanks to you. guys. You were early supporters, backers. We talked about it on here. And, you know, founders are crazy. And.

you guys probably looked at what I was. working on and and and thought, you're. nuts. You're wasting your time on this. And so, you know, when it got signed. into law last year, that's a huge moment. in a founder journey that it's like. getting your first round of funding. maybe like, okay, we actually this thing. is going to happen. But on July 4th of. this year, the app went live, right? So. that means millions of accounts got. created, the accounts got funded. And to. celebrate that and to really kind of. take the next step forward,

you know, we designed a joint bell. ringing first in history between the. NYSE and NASDAQ from the Oval Office. That was incredible. We had hundreds. CEOs there, kids there, families that. were impacted. And the president really, you know, kind. of laid out that this is much bigger. than just a program to give a few people. some accounts. This is really about. making every child a capitalist. In. fact, the president suggested that we're.

going to autocreate uh accounts for all. 50 million kids or upwards of 70 million. kids under the age of 18. So he called. on us to get the accounts open faster. for more people to have more impact to. make sure no child is left behind. >> Brad, just slow down because a lot of. people don't even know what a Trump. account is. Just explain the what it is. and then you should contrast it to like. a 529 account and some of these other. things. >> Great. So, as you guys know,

the idea was very simple. $1,000 for. every child at birth that could compound. for their life in a privatelyowned. investment account. So you're born, you. get a social security number and you get. an investment account. And if you do. that, you start with $1,000 and somebody. matches that and you save 10 bucks a. week, that's $50,000 at age 18. And the. idea. >> and that's invested in the S&P 500. >> S&P 500. So when these accounts are. created, all that money goes into the S&P 500.

There's no cost. It's a free account for. the lifetime of the recipient. And that. was packaged into the Invest America. Act, which was passed into law a year. ago as part of the reconciliation bill. So that's what actually occurred on July. 4th of this year. All those accounts. were created for all of these kids. That's the reason the Trump account app. is number one in the app store because. parents started hearing about this and. saying, "Whoa, I need to go download and. get this set up for my child." We had.

over a million and a half counts created. in the first 24 hours after the launch. of this. We had over a billion dollars. of deposits. So, I was contributing. money into the accounts of my nieces, my. nephews, my kids, friends, kids. Every. account h app has a QR code. Jason, so. somebody can just send you the QR code. for your kid. You double you Apple Pay. on your phone, double click and you send. them 25 or 50 bucks. So that is kind of.

the the most essential part of it. But. we also had a bunch of announcements. around philanthrop. when you're 18, 19, 20 years old and. start putting it towards school or you. can roll it into your IRA, >> Roth IRA, I guess your your your. retirement account. Obviously, Michael. and Susan Dell were the were the anchors. here. Over $6 billion, $250 for each of. 25 million children, primarily lower and. middle inome kids. SpaceX's president,

Gwen Shotwell, she joined the party, put. $350 million in her SpaceX shares, uh, and for children of lower income. communities. So, with this, there's a. device or some way to do it. So, you can. target specific communities by geo uh, or by, I guess, their net worth. Um, >> no, it's it's just zip code and age. Zip. code and age. >> Zip code and age. Okay. And then Micron. put in 250 million up to a,000 per. employee. So that seems to be a really. interesting way to do this. Like you can. do an employee I'm sorry, an employer. contribution. >> And Brad Brad did it for all kids in.

Indiana, I think. Right. >> Correct. All kids. >> Brad, this is a big number here. I This. is a big announcement. Brad, the guy who complains when we make. him buy in for 10K after 10 p.m. at the. poker game and who like rage quits the. game when he loses $6,000. Somehow Brad dropped $100 million. I mean, oh my god. Let's get a round of. applause and a golf clap. Brad, this is.

I mean, I I've never heard of you doing. any philanthropy. Like, sometimes you. show up with a bottle of wine to the. game, but this is a big number. This is. a big decision for you, huh? Well, I think this will become the. largest direct philanthropic platform in. the history of the country. We told the. president, we think we can raise a. hundred billion dollars in the first 12. months. And so the scale of the. philanthropy, the nature of the. philanthropy directly to America's kids. without a charitable middleman that's. directing who gets what and and how it's.

distributed. So you think about the. people who now are, you know, we're 10. billion or a h 100red billion. How do. they give that money away at scale. effectively? Now we have a platform they. can do that with. It goes directly into. the accounts. The money can't be taken. out until the kids are 18. for. >> there was a bunch of noise about how. some people won't do it because it's. called Trump accounts. and that some people said, you know, this is going to create this weird class.

divide by people who. had TDS and refused to give their kids. because I think your website or. something said something like 13 million. bucks by the time they're 50. And you. know, I tweeted something to the effect. of that is an irresponsible amount of. money to not give a kid because you. don't like the fact that it's called a. Trump account. It's it's it's patently. insane. >> If you go on Blue Sky, which is like the. open- source uh lib TDS um social.

network, people are like just put one, you know, y'all trust those Trump. accounts. I sure as hell don't. And so. there's a bunch of people. >> Speak to that. Yeah, speak to that for. one second. Mike. >> So, I would say this, you know, it was. the enabling legislation is the Invest. America Act. Um, a lot of people, a lot. of Democrats call them Invest America. accounts. They're officially Trump. accounts. And the facts on the ground. are that parents aren't listening to. that noise. The parents who are signing. up for this are across the income. spectrum, across the economic spectrum.

They're across the political spectrum. They know and understand that their. first responsibility is making sure. their kids have a connection to the. American dream, have savings for their. life. But yes, they are called Trump. accounts. And I I've I've read some of. that blowback. But the president. himself, let me just make this case very. strongly. There's nobody who I've talked. to about this over the last two years. who cares more about every child getting. an account than the president himself.

In fact, that occupied a lot of a lot of. our conversation over lunch. He said, "How do we get more people autoenrolled. in this faster? I want every kid to have. the shot to have this. I don't want. anybody being left out and left behind. because their parents are too busy. working two jobs or because their. parents may have an issue with it being. called a Trump account." So, the. president is pushing us very hard and. the Treasury Secretary,

he gave you instructions. He gave you an. order that he wants you to autocreate. the accounts. This is a brilliant move. He know we know the social security. numbers of people who are under 18. He. told you get to work and automatically. create the accounts. Are you going to do. what the President Trump has commanded. you to do, Brad? Are you going to. autocreate them, Brad, or are you going. to disobey the president? >> We we we our intention is to get all 50. to 70 million accounts created over the. course of the next 90 days using all of. this data. But you know, listen, we got.

to work through Treasury, the White. House, Social Security, etc. They're. definitely. >> You also got to get through Elizabeth. Warren and Bernie Sanders and Roan who. are going to try to stop you. Are they. going to try to stop you from doing. this? Are they giving you blowback. because they don't want to give Trump. the win, which is totally but. >> No, listen. I I I I'll give credit where. credit is due. You know, Cy Booker's. come out and supported these. And Gavin. Newsome, Governor Wes Moore, you know, John Federman, Senator from. Pennsylvania. So there are plenty of. Democrats who are able to get over that.

hurdle. But you bring up a good point. and I said this on CNBC yesterday. On. the one hand, you have Bernie and. Mandami. They want to take and tax all. these corporations. They want to control. all that money in Washington and decide. who gets it. Right? It's a very. dependent on Washington model. On the. other side, you have the president in. this administration and frankly a lot of. Democrats who are more in the orthodoxy,

closer to the center, who say, "No, let's set up a private account for every. kid in America. Let's fund them. Let's. not make them dependent. Let's make them. independent of the government to build. wealth on their own, financial literacy. on their own, more likely to graduate. from high school, start a business, buy. a home." Those are two very different. worldviews for America. And I think the. antidote to more socialism is more. capitalism. And as I told the president, this is more capitalism. >> Saxs, if this succeeds, and Brad does as.

he's been instructed by the president, we're going to go from 50% of people. owning equities in the country to as. much as 70 maybe even 75% of the country. having access and for the first time. being part of equity nation. What's your. thoughts on this, Sachs? Look, I think. that's a great thing and I think that. this is a tremendous new philanthropic. platform and that's really important. especially in this time of growing anger. and backlash and populism against.

billionaires and people questioning. whether the system is rigged and whether. they can be successful in America, whether they will be able to be part of. it. This is a really important antidote. to that. But I almost think that the. philanthropic aspect maybe has gotten. almost too too much attention because. people are naturally attracted to the. freebies and the part that I think. hasn't gotten enough attention or all. the the comments I saw on CPA Twitter, you know, where all these accountants. were talking about what an unbelievable.

I guess you could say estate planning. strategy this is or basically. >> less advantaged. Yeah. like a wealth. management technique, whatever you want. to call it, like planning for the. future. And there's never been anything. like this before. They were basically. saying this is like in the top three, you know, there's certain things that. you just have to do, like if your. employer offers a matching 401k, you. have to do it because otherwise it's. just you're losing out on free money and. if you don't do a health savings account. or you don't max out your Roth IRA, there's just certain things you have to. do because they're so tax advantaged or.

you're getting free money, right? And in. this case, you're getting both. There is. the opportunity for, frankly, the free. money for your kids, right? But also, the tax advantage is huge. So, let's. just go through this, and Brad, correct. me if I get any of this wrong. So, you. can donate up to $5,000 a year to your. kid as long as they're under 18. And. it's not just you, it's any friends and. family or others can contribute as well, which is new. And then they get taxfree.

compounding till they're 18. And your. employer can contribute up to $2,500. taxfree. So at a minimum, you should go. to your employer and say, "Sign up for. this and if you have to take $2,500 out. of my salary and make it a donation to. my kid's Trump account because then. that's a huge tax savings, right? Neither side has to pay tax on it." So, you know, like Brad said, this is. basically like an IRA. You get taxfree. compounding. Then when the kid turns 18,

they can get access to it and they can. do a a rollover into an IRA or into a. Roth IRA, which is even better because. when the Roth IRA matures, you don't pay. tax on the money that gets distributed. out of it. Where whereas with a. traditional IRA, all the taxes get. deferred until the end. The difference. is that when you do a IRA to a Roth IRA. conversion, you're supposed to pay taxes. at that point. And I saw one really. clever CPA say that well the best way to. do this is wait till your kid is.

actually not a dependent anymore. Like. so maybe they're in college or they just. graduated from college and they're in. like the 0% tax bracket because they're. not making any money and then do the. conversion. And so you'll be able to. convert the Trump account very cheaply. into a Roth IRA and now they're going to. have $2 to $300,000 potentially in that. account that they can then do tax-free. investing for the rest of their life or. they could potentially start a company. with that. Other things you can do with. an IRA is you can use part of the money.

on a down payment for the first home. purchase or if you get into a health. emergency, you can use money for that. So, there's all these things. You're. allowed to distribute money out of an. IRA without incurring a penalty. But. generally speaking, the point of an IRA. is to save for retirement. And this is. where I think it gets really amazing is. because if you start with $200 to. $300,000 at age 18, you'll be at $10. million plus by age 60 if you just let. it compound. I mean, there there's.

ranges. >> Nepo babies we're creating here. We're. going to have a lot of rich kids with. trust funds. >> Yeah. So this is like this is all you. have to do to make sure that your kid is. protected for retirement is if you and. your family and your friends and your. employer can just contribute to their. Trump accounts. >> Like that that's like that's way better. than social security. >> Brad, I have an idea. I have to go sell. some enterprise software so I have to. leave. But I'm I'm really proud of you. I think this is incredible. You should. convince OpenAI and Anthropic to give.

the equity of those companies if this is. going to be as big as you say 100. billion, 300 billion, zillion, trillion, put it into the uh accounts of every. kid. >> Can you just explain how that works. against the $5,000 limit? >> I got to go. Love you guys. See you. later. All right. Good luck on the sales. call. >> Yeah. Always be closing. Chimath. Always. be Chimath closing. APC. >> Chamath always be closing. You know, again, David and Jamant, as we build out. the platform at scale, so imagine now.

you have 50 million accounts that are. opened, we do we I I've said on CNBC, you know, I've obviously talked with Daario and. Sam and Elon and others about making. those donations. I I don't like this. idea of shaking down our companies, taking their shares, and then putting. them in some government slush fund that. perhaps Bernie or AOC or somebody's. going to control in the future. I've. said I it's got to be voluntary and. number two it should go into citizen. accounts right privately held in citizen. accounts at Capound for their life and.

so you asked the question David how does. it happen given the limits that you have. you know the $5,000 per child that's why. you have to have so you know 50 million. accounts opened right because then you. can take uh dollars in at scale but we. can also set up a poolled account David. where it can be distributed over time so. you distribute it to all the kids. subject to the limits that you have. today and then any remainder you can. distribute to the 3 and a half million. kids that are going to be born next year. or the 3 and a half million kids born.

the year after that or the three and a. half million kids born after that. We. are on a trajectory now that we're going. to have over a 100red million of these. counts set up over the next decade. Okay? So we could have 70 million today. and then you're going to add 3.7 million. a year. So you're going to be at a 100. million private individual accounts that. are compounding for people's lives that. anybody can donate money into that the. people themselves. I think one of the. things that gets lost is moms and dads.

or somebody working their summer job put. in 10 bucks, put in a hundred bucks, put. it, you know, into these accounts. They. get to see it on their phone. You know, this is when we started this, my sons. and I designed this app and it's. basically what we ended up with. It's a, you know, Joe and. >> shout out to Vlad at Robin Hood helped. you with it. Yeah, >> Vlad and and Joe have implemented a more. elegant version of this, but every kid. owns a little bit of Nvidia, a little. bit of Microsoft, a little bit of Apple. Imagining opening up that account,

David, in middle school or high school. to the money page, and now you're. getting excited that you're seeing, oh. man, I'm in the game. I have ownership. And while you reference what it could be. for families who can contribute $5,000, obviously Michael Dell and I and Gwen. and everybody else, we're focused on the. 50% of Americans who feel left out and. left behind who would otherwise have. zero. If you do the math on this over. the course of the next 15 years, you. could have somewhere between two and.

four trillion dollars added to the. accounts of families and kids who would. have otherwise had zero. We talk a lot. Go ahead. >> We we we talk a lot. >> See, the philanthropy piece is it it. basically the way the the philanthropic. aspect works is that other people. philanthropists can contribute towards. that $5,000 per kid, right? Is that. >> So, you know, when Gwen Shotwell. contributes 2 million shares of SpaceX. to 2 million kids, each kid's getting a.

share of stock. >> 150 bucks. So now. >> that's counting against their $5,000. limit. So that's what makes it compelling is. okay look every every family that can. afford to do the 5,000 should because. it's just like so compelling from a tax. and saving standpoint but then even for. families who can't. >> there are going to be beneficiaries of. philanthropists who just want to give. this type of direct giving and it seems. to me this is so much more efficient and. so much better than the whole NGO.

industrial complex where. >> absolutely where they take% for their. offices than their salaries. >> Yeah, they're just drifting. >> Yeah. >> One of the numbers I saw was kind of. amazing is again, it just goes back to. the power of compounding is that if a. Trump account had been maxed out and you. have the standard market rate of return. that we've had for say the past 30. years, then by age 28, that kid will be. a millionaire. >> Incredible. >> That's right. That's right. All the. numbers you hear me quote, the $50,000.

and the $200,000, it doesn't assume. maxing, you know. That just assumes. people are adding $50 a month because. I've been focused as Michael and others. have really on the families who who. don't have the capacity to save today. We're getting all of them into the game. And the president directed us. He said, "Listen, we have 529 accounts that. already help the top 10%." That's not. who we're focused on. This is about the. main street agenda. This is about all. the families that he ran for that feel. left out and left behind and we're.

reconnecting them to the American dream. through uh universal ownership. They all. have their own account. They all have a. private account on their phone. Um it's. a gamecher for the country. It's the. largest change to our social contract. since 1935 and social security. And. importantly, I think it couldn't come at. a better time. You know, we have this we. have this fight for. >> just every employer should be signed up. to be, you know, employer that can. contribute because again you could take. that $2,500.

and hopefully look it's additive and. that it's not just a substitute but even. if it's just a substitute and JCAL your. employer takes $2500 bucks out of your. salary and puts it in your kids Trump. account then you it's reducing your. taxable income so it's a no-brainer. >> if you're a profitable company your. employees are going to love you yeah. >> yeah but I think every employee is going. to want to and every employer should do. it because it's the tax savings for. both, right? So,

>> the tax savings here is huge. >> Yeah. So, just off of the mechanics of. it, I just want to maybe level up here. for a second. >> Yeah. I have been. often critical. I call balls and strikes. and I can tell you in detail the things. that I have a problem with this. administration and their actions they've. done and I have done it here on the pod. I want to address the people who are. negging this and specifically negging it. because it has the name Trump accounts. on it which I told you at the poker game. call them Trump accounts. I don't know. if that was like an obvious thing or I.

was the person who told you to do it. I'm not taking any credit here but I. remember that conversation where I was. like just call him Trump accounts. Like. if whatever criticism you have of Trump, however valid you may feel it is. This. has nothing to do with Donald Trump and. how you feel about him. Put your TDS on. the side. Put your valid criticisms on. the side. In this country, we have a. K-shaped recovery going on. We have. immense tension between the halves and. the have nots. We to the point at which. people actually believe that socialism.

and communism is a better operating. system than the best operating system. humanity has ever created, which is. called democracy plus capitalism, right? And kids love love capitalism. They love. building businesses. But we are in an. existential moment right now. If these. kids believe, young kids, and there's a. couple of generations of them right now. who do not believe in America anymore, while we're sitting here on the 250 50th. anniversary of this amazing experiment. known as America, this is the most. American thing you can do. So, put aside.

your TDS, put aside your valid. criticisms and embrace this and give the. flowers to Brad, to the people donating. like Michael and Susan Dell and Gwen. This is beautiful. This is the most. beautiful. gift I've ever seen to a country and. this could be something that's a. unifying principle that brings us back. together as a country that everybody. gets to participate in capitalism and.

this is the number one way to do it. which is to let kids on their smartphone. instead of saying you know what mandami. is right I should get a free bus ride I. should get a free I should get free. pizza and we should take Ken Griffin's. and and sees his, you know, penthouse. and pay out of ter. all that, you. know, and we have we have CEOs getting. shot and and their homes firebombed. Well, you know what? If you're one of. those CEOs, you've done incredibly well. There was something called the giving. pledge where they pushed, you know, affluent people at the TED conference.

for decades, Bill Gates and everybody, Warren Buffett, everybody was pushing. for this. This is like the perfect. version of the giving pledge because. you're not just saying, "I'm giving away. my wealth by the time I die." You're. very strategically saying every single. person in America gets to be part of the. best part of America which is. entrepreneurship and everybody will be. part of the equity nation. And my final. point is one of the happiest countries. in the world is Australia. If you've. ever gone to Australia, everybody feels.

safe. And we have a a large number of. people in this country who do not feel. safe. And the reason they don't feel. safe is because they don't think their. kids are safe. to the point at which. people do not want to have kids in this. country because they feel the system is. just too hard. This could change that if. people feel, hey, kids have a shot and I. don't have to worry about my kids. I I. worry about my kids and I'm affluent. I. can't imagine being a single parent and. what anxiety you must have as a single. mother or father and you're and you're.

making minimum wage and you're behind, you know, the eightball for your entire. life and now your kids are set. That's. all people want. That's the only thing a. parent wants is to make sure their kids. have a better future. That was the. promise of this country and somehow it. went off the rails for the last two. generations. This puts it back on the. rails. This is super annuation funds in. Australia. In Australia, people are. extremely happy. The reason they're. happy is they're forced to put 14K a. year or whatever it is 12 or 14% I think. of their income into essentially a 401k.

that they get to direct to a certain. extent. It's forced savings. This does. the same thing. >> at at a a very basic level. This could. replace social security. This replaces. the giving pledge. And I just want to. say Brad, you know, a lot of my friends. got involved in politics. Some of them. on this very program, a lot of people. It's very divisive. You threaded the. needle here. It was a master class in. balancing these two. crazy parties and and the divisiveness.

in this country. I just want to give you. as your friend your flowers. This is. just absolutely outstanding what you did. and and you have been incredibly humble. in your approach to this. This would not. have happened without you, Brad. This is. this is your legacy of everything you've. done in your life. Lots of success and. I've seen it up close and personal. This. is. a million times x everything you've done. in your whole life. You'll be. remembered for this. This is. architecture. >> Should be as big as social security. I. mean, it's a new platform. It's like an.

entire new. >> It's not because it's philanthropy, but. it's also. >> retirement savings. I mean, right? And. everything in between. >> and this is not static. We This is. dynamic. >> We can add to this. There could be other. features. >> I'm seeing a lot of people in the. comments say, "Why stop at age 18? Why. can't you I mean, you have the Trump. >> account roll over into a IRA or Roth IRA. after age 18, but why can't you keep it. going and then people can keep that. $5,000 contribution going? And you know,

it doesn't mean we take away. >> exactly. >> retirement benefits that are owed to. current social security recipients, >> but sunset it. But at a certain point, you could just say that, hey, the next. generation is going to be on this. platform rather than the old one, and it. would be a lot better. >> A lot more efficient than government not. running it, right, Sax? >> Yeah. >> We don't want the government running. this. >> Let me ask you a question about this, Brad, because I I do see one thing that. people say, which is what if your kid. turns 18 and then they just want to blow.

the money, >> you know? How do you trust? How do you. trust that they're going to put it to. good use, you know, as opposed to. >> I don't know, you know, >> yolo. >> yolo and whatever. >> As you know, these things are always. political trade-offs and balances. And I. wanted them to have to compound until. they were 30, right? Because I figured. by 30, you were a little bit more, you. know, uh uh mentally uh developed on on. financial issues. But, you know, the. argument ultimately came, you're old.

enough to vote, you're old enough to. fight a war. if I if by 18 we don't. allow you to have control of your own. money. So that's where a political, you. know, uh consensus was built, David. But. the other thing, remember, is they can. only take up to 25% out to buy a home, start a business, go to college. The. rest rolls into an IRA, and there are. built-in penalties for early withdrawal. in an IRA. So they're disincentives for. people to pull out. But let's be clear, we have to do a much better job in our. education, our public education system,

leveraging this as the platform. You. know, if a kid doesn't have any money, it's hard to get excited about learning. about money. But if a kid's in the game. and has 12,000 bucks in the seventh. grade, now you got my attention. I own a. little bit of Nike. I own a little bit. of Apple. I own a little bit of Nvidia. Let's talk about that. How did it get. there? How did it compound? If I added. 50 bucks a month, what does it turn. into? All of these things will now be. present on every child's phone in. America. 37 states require financial. literacy. Every state should build this.

into the curriculum. We're working with. a lot of states on that. You know, we. haven't talked about that. We have about. 25 states who are going to add money. into the accounts of the kids in their. states. So, you got. >> states are going to do it. >> States state action. Oklahoma, West. Virginia, you know, Indiana, etc. So. that's also sweeping the country where. the states are looking at programs they. already have where they're spending. money for kids that are ineffective.

and they're saying instead of continuing. to spend money on these things that. aren't working, why not just block grant. the money directly to the kids. >> because we. give the kids the money more likely to. graduate, more likely to, you know, to. buy a home, start a business, etc. So, I. think that we're, as I said in in the. oval, this is day one, and I am fully. committed to the next decade, as is my. partner in crime on this, Michael and. Susan Dell. I appreciate your guys's.

comments on on on the legacy of this. It. has been the most profound work and kind. of honor of my life. and standing in the. Oval Office with my two sons who are. really my two co-founders on this. We. draft, you know, we made the sketch of. this at our kitchen table in at the in. the fall of 2020. That's where the. conversation started. Lincoln's been. with me in every single meeting with. every congressman, senator, president, former president, etc. The president. shouted him out uh you know, again when.

we were there. That journey as a father. with my kids. >> has been like the payback has been. really extraordinary. Other thing that's. notable here and again like you got to. call balls and strikes and give credit. where credit is due. Joe Jebia joined. this administration. A lot of people in. the tech industry are like oh you know. oh you joined the Trump administration. whatever you know. Okay there's some. criticism. He's an incredible worldass. designer. I was talking to producer Nick. our producer here also happens to show. the same last name as me. He signed up. for this right? He's doing well but you.

know his his wife signed up for it. The. software is fantastic. Let's pause for a. second. The American government has made. exceptional software and this all got. done in Trump's first 18 months, immense. credit for this. This is like of all. the, you know, challenges this. presidency has had and the Iran war and. other issues. We made great software. The American government because of Joe. Jebia makes kickass software. Like just. also major shout out to him and you know.

he could be doing whatever he wants. He's, you know, he's done incredibly. well as the co-founder of Airbnb and. he's doing this like that. That's a real. patriotic thing to do. I I I'm just over. the moon with this. I think it's. fantastic. >> The dream team you had like Michael. Dell, myself, Vlad Tennv, Joe Gabia, >> the Treasury Secretary, Luke Pettit at. the Treasury talking basically every day. for the last year. And our objective was. not we want to build the best thing that. that the government's ever launched. We.

wanted to build one of the best consumer. products period that's ever been. launched. Mission accomplished. >> and there's any Silicon Valley consumer. company would be thrilled with the. numbers that we're seeing, the ratings. that we're seeing, the engagement that. we're seeing. So, >> you know, it's been fun doing it with. that incredible team. And, you know, everybody's in this for the right. mission as well. And so, I agree with. you, Jason. It's rare that government. recruits or embraces uh you know, that. that that mission. And I think the.

tent's getting a heck of a lot bigger. It is bipartisan. It's bipartisan in support. You know, this is important. What Governor uh uh. Moore from Maryland said yesterday. He. said, "Republicans and Democrats have. been trying to do something that looks. like this, feels like this for 40 years. This guy got it done. Give him credit. This is great for America, great for our. kids, and especially on the 250th. anniversary. You know, you're standing. in the Oval Office looking at the.

original Declaration of Independence and. you realize what people laid down for. this experiment and then I I read this. chatter in my feeds about Mandami and. others literally wanting to set this. great experiment on fire. >> Yeah. >> Right. Wanting to burn the place down. because they they think they have a. better formula. No, the answer is. evolving and doubling down on the. formula that has worked for 250 years. And rather than making all these kids.

socialists, we get them all into the. game of capitalism, they become owners, owners and shareholders in America. So. that's what we got accomplished and uh. >> appreciate the chance to talk about it. >> Listen, incredible Brad and um you know, just amazing to watch you do it. And if. you if you if you if you really think. about it, the tech industry I needs to. win and capitalists and creators and the. makers, the people who build stuff. This. is our chance to say here's an example.

of something that helps the people at. the bottom, right? And I talked a bunch. about um the minimum wage here. We got a. $7 minimum wage. Like we we need to. address that as well. These are the. things that if we address what people. are scared about, what people who are. who don't have what we all have here, uh. if we have empathy for those people and. we actually care about them and we give. them a path to believe in the American. dream, they will take that path.

>> we have to give them a better path than. these socialist lunatics. And this is so. much of a better path. Let's do it. again. Let's do another one of these. things. Let's keep growing this spirit. of getting everybody in the country to. have equity uh in these great companies. That's that's why the entire world is. trying to replicate what we do here. Every single country I go to wants to. recreate Silicon Valley. >> We're not we're not stopping here. And. um David to your point where you know. whether it's the AI companies uh or.

frankly whether it's the Intel shares or. whether it's the Tik Tok fee I now have. a a place where all of those wins. achieved by this administration can go. they ought to go directly to all the. citizens you know the country into their. accounts and compound for a lifetime. And then as far as people over the age. of 18 there's certainly a lot of talk. about that as well. um not again as. social security is a sacred promise by. both parties. Nobody's going to change. that. But there's a huge opportunity to. have a supplement here. Why shouldn't.

people, you know, between 20 and 30 or. 20 and 40 also have a Trump account that. they can begin on a supplemental basis. adding dollars that they own and. control? Remember the big difference. between this and social security. Social. Security takes 12.4% 4% of my W2 income. and puts it into something akin to the. black hole of government. I don't own. it. I don't control it. If I ask a room. of 3,000 people how much they've. contributed, they have no idea. If I. die, I don't have title. It doesn't pass.

to my heirs, etc. So, it's really not. mine. But if we created a supplemental. IRA, it doesn't even require new. legislation, I don't think. It's just. expanding the age. These these are IAS. after the age of 18, right? then people. could start building supplemental wealth. and participate in these gains. And so. there's a lot of conversations going on. about that as well. And and so we're not. done, but uh it was a hell of a. milestone on the 250th birthday of. America to ring the bell in the oval and.

to to watch all these kids get their. accounts lit up. It was pretty special. What I think is really cool about the. Trump accounts, I'm I think it's an. amazing philanthropic platform, but in. addition to that, it's an amazing. platform for middle class family. planning. That's the point I'm trying to. make is all the CPAs that I'm seeing. talking about this are saying this is. like one of the greatest things ever. And if I could only tell my clients to. do one thing, this would be the one. thing. >> Finally, something for the middle class, right? This is what people have been. asking for. Hey, let's get something for.

the middle class. Let's get something. for the, you know, >> Yeah. And I I think the market gap, bra, correct me if I'm wrong, but basically. the the market gap that was created here. is that you can't get an IRA, which is. basically a tax advantage uh savings. account until you have your first job, right? And get earnings, >> which would be for most people at age 22. plus. So for that first 22 years, >> you're not your kids can't have an IRA, right? >> Correct. And you're effectively giving. every child at birth correct IRA.

>> You know, it's a Trump account has. certain rules. It's actually it's better. than an IRA. >> Better than an IRA. >> It's better than an IRA because with an. with an IRA, your employer can't. contribute 2500 bucks taxfree, can they? I mean, >> I don't think so. and philanthropists. can't contribute to it and moms and dads. and but the most important thing you. know like I I I say this you know. Buffett's like the secret is to find a. really small snowball on a really long. hill okay but the size of the hill in.

this country we've cut off the the first. third of the hill forever nobody saves. anything until they're 25. >> okay the easiest compounding in the. world the the easiest compounding in the. world is between zero and 5. All right. Listen, this has been amazing. >> Yeah. Because their dependence, frankly, they're still on mom and dad. >> Exactly. So, you you you pick up the. first third of life. >> Incredible, right? In in compounding. And so, it's a. >> it's really remarkable. Let's go. Uh I.

mean, amazing job. All right. We'll see. you all next time. Bye-bye. >> We'll let your winners ride. We open sourced it to the fans and. they've just gone crazy with it. >> Love you. Queen of. >> your. besties are gone. >> That is my dog taking notice your.

driveways. >> Oh man, myasher will meet me. We should. all just get a room and just have one. big huge orgy cuz they're all useless. It's like this like sexual tension that. they just need to release something. else. >> Your feet. >> We need to get merch. >> I'm going all in.

I'm going all in.