The Fight Over Open Source AI, Anthropic's $1.5B Payout, NYC Socialists: Evictions = Violence?

All right, everybody, welcome back.

Episode 282 of the world's greatest podcast. It's your podcast, it's your favorite podcast, it's your mom's favorite podcast, it's you all in podcast. With me again, David's ax to my plan up here, David Freeberg. It was a big week, it was a big week.

The continuing number one story in the world is Kimmy K3, it sparked a debate about banning Chinese open source models here in the United States. And it's gone all the way to the White House last Friday. We talked about it here. China's moonshot AI released Kimmy K3 open source model obviously performance on par on par.

Not six months behind, not 12 months behind, but now on par with models like Opus 4.8 and GPT 5.6, which getting up itself is extraordinary, but about 50% cheaper. And this has created a bit of a panic similar to the deep sea moment that we had here back in early 2025.

The White House, David Sachs has gotten involved. Michael Cratzios, friend of the show, said quote, we have information that moonshot AI distilled and tropics fable for the development of its K3 model. Here's how the Trump administration has reacted so far. Monday, Axios reported the White House was considering banning Chinese open source models.

“A couple of weeks ago, David, I think it was three weeks ago.”

I gave that to you as a hypothetical and here we are on Wednesday, wired reported that Howard Lutton, from our commerce department, friend of the show, does not want to ban Chinese models. So apparently, Palace intrigue, there might be different opinions inside Trump's White House. And instead, they want to incentivize more US frontier labs to develop that our open source

model is polymarked. It says 45% chance US government bans an open source model in 2026. As a brand new market started, it was at 22% a couple days ago, Sachs.

You called it two months ago, our first victory fap of the episode.

I think where it's all leading to is an effort to ban open source models. There's a lot of breadcrumbs leading here. You look at a lot of the rhetoric around how models you have guardrails and that with open source models, the guardrails can be removed and therefore they're dangerous. You see this rhetoric already in an anthropic spot post, any threat that they describe

it kind of go out of their way to take that shot at open source models.

“I think again, they're trying to create ideas or put predicate facts in the public record”

to justify an action later on. I think it's just a matter of time before they feel like they're at a position where maybe they can push for that type of ban directly. All right, there it is, Sachs. What's going on at the White House?

What is the administration's position here? Why are we getting multiple? Is the White House testing and probing to figure out what their position is here? Is it just, this is a super dynamic situation? What's going on?

Well, look, I mean, I have it on good authority that there is no decision by the White House to ban open source models. And I think they want that known. I think there's an ongoing conversation happening around what to do about Chinese distillation and we should talk about that, but no decision has been made.

And the President listens to a course of voices. He wants to get advice from as many people as possible. And I'm confident that if everybody weighs in, that the President will make the right decision.

As he always has with these tech issues, I think his instincts have been absolutely impeccable

on this. He's always supported a, let's say, lighter regulation, more open approach.

“And that's why I think the U.S. is winning the A.I. race.”

So I think that's kind of where things stand. Where do you stand? Where do you stand? Where do you stand, Sachs? That's what everybody wants to know.

Yeah, I think it's important for me to make my opinion known in the spirit of, again, contributing my voice. So the President hears all perspectives and then can make the best decision. Look, I think it would be a tragic mistake. If the government were to take action against the open source ecosystem, that would do

nothing but hurt America's position in this A.I. race, it would backfire badly.

And I think that the key point here is that regardless of what you think about distillation,

you cannot punish American developers for it. So you know, you can't say that American companies and American developers can't use Chinese contributions to the public domain. That's just cutting off our nose to spite our face. I mean, obviously American companies have to be able to use everything.

That's in the public domain because the rest of the world will be using those things. And let me just say, I've said for a while that anthropic is guilty of regulatory capture of attempts to seek government protection. This is a company that is the fastest growing tech company at scale in history.

They started the year at 10 billion of ARR.

They're now over 70 billion of ARR.

This is not a company that needs government protection. This is not a company that is under threat from competitors or whether they're Chinese or otherwise. And yet they have been very successful at trying to panic everybody into thinking that they need some sort of government protection.

And the tell on this, the way that you know, that this whole distillation thing is fake

“is because if stopping distillation, was there primary objective?”

The traffic would push to ban Chinese access to American models, not American access to Chinese models. Yes, they could, and that is achievable. They could block it. So there are the ones in the best position to block it.

If distillation, if industrial skill distillation is a national security threat, there are the ones who need to stop it because that is the place where distillation occurs. You have to stop it at the source. Once you allow Chinese companies to distill, the horses out of the barn.

Yeah, and the reality is that I think that what's happening here is that in their lusts

for growth and traffic has done a very poor job at stopping distillation. I mean, they're saying that distillation is occurring at industrial skill. Okay, if it's industrial skill, it must be pretty obvious to see why you're stopping is waves of accounts being created by students rolled up and sold on the dark web, you know, in those kind of channels, so you got people in Manila in the Philippines, I understand, and

India signing up for all those accounts and then sending them to the dark web and selling them using IP addresses from America. Yeah, so that's the more the more industrial skill it is, the more obvious it is to see. Absolutely.

“It's been saying for a while, why don't you pay why see your customers?”

Exactly. They know that if they pay why see their customers, it'll slow their growth. So instead, what they're saying is, hey, ban our competitors. Well, that's ridiculous. I mean, they're in the best position to stop the distillation.

I think that they're negligent about doing that, or I mean, if they really think it's a big a threat, they should use a few points that are 90% gross margins to do that. What you don't do is then say that American developers cannot use everything that's in the public domain. So it seems to me that this debate is all backwards, that the questions should be on

anthropic to explain why it's doing such a bad job. All right, not on the whole American open source ecosystem to be punished for anthropic failure. All right, free break. I have a really good question for you, but before we do that, Chemoth, can you give

me maybe a little bit of what you're hearing on your sales calls for 8090, you're talking to enterprises, they're hearing all these reports whether it's you, Dario, this pod, other places talking about, hey, open source is ready. This is the moment, get control, AI sovereignty, et cetera. They must be calling you up and saying, hey, okay, we're ready.

How do we get these things on prem? How do we do it? So what's the, what's happening on those calls you're doing with the enterprise? And then can you maybe give people an idea of what distillation is just and why it's so important here?

Let's start with the second thing, distillation is when you fire up a model and you ask it a question and you observe it and you take its output and you use that in training of your own model. Now multiply that behavior by tens of millions and what you expel trait is essentially trillions of questions and answers and sacks is right if you really care about distillation,

you implement KYC, you force people to make an account not just with a username and a password but with some form of identification, maybe with a bounded credit card, there's all kinds of steps that you can take that would frankly slow things down in terms of revenue traction but would solve the distillation problem on its face. So that isn't really a thing, it's a bit of a red hearing.

Another thing on distillation is everybody has at some point distilled. The question is who is distilling from whom and it looks like that funny mean where there's

“like nine Spider-Man all pointing at each other, that's what this is because anthropic has”

distilled from all of these publishers, they just pay a 1.5 billion dollar fine, apparently

open AI distilled from the New York Times, there's still an ongoing lawsuit. The Chinese labs have distilled from anthropic, wholesale stealing everywhere, well I don't want to call it stealing because it's not clear who actually owns a copyright in the first place, but here should be the important observation. These models are getting commoditized much faster than anybody thought.

How do we know this?

Because there is no meaningful sustained advantage once a model publishes their performance

criteria. What you see is literally within weeks, other models, some open, some clothes, some open weight, who are able to match and in some cases exceed the performance. So I think what's happening here is a handful of American companies have realized, whoa, this value that we are seeing today may not be sustainable in a 5 and 10 year period.

“And when you go and present the business model to Wall Street, you need to have that certainty”

otherwise it impacts your valuation. And so I think a lot of what's happening right now, Jason, is a valuation preservation gain by the close frontier labs because if you actually understood how commoditized these things are becoming and the velocity at which it's happening, you see that the real business model is not in the foundational model anymore.

It's at the application layer above and it's in the infrastructure below, whether that's

a cloud or whether that's chips.

And so I think in the absence of regulatory intervention and in the absence of the United States government stepping in to put their thumb on the scale, what will happen is that as people learn about how value is changing, they're going to put more value in the application layer and more value in the infrastructure layer. That is bad for close frontier labs, especially when they're mispriced 25 to 50 x the open

alternative. And so this is an attempt to stop a competitor that is of the same quality but just much cheaper.

“Now, there's another important thing here, which is if the United States government”

intervenes, it will tank the stock market, okay, period, not debatable. Now you can debate which companies get tanked and we can probably play that scenario out. For example, if they said no more open source, American companies cannot use open source, okay, let's just take at it from a stock perspective, let's take an average normal company, Coca-Cola, hey Coca-Cola, you're trying to use AI to improve your business, you know what,

you can only use these two options and those things cost 50 to 100 times more than your other best alternative that you may use otherwise.

That will eventually show up in your costs because AI is supposed to be this incredible

thing that just kind of solves every problem and does everything for you. And so this incredibly important input into your cost model is now orders of magnitude, multiples greater than your competitors that are outside the United States, simply because you're in the United States. So what, what the capital markets do, they're going to say, wow, you have a crazy

cost structure, this doesn't make sense, you're forced to absorb costs that aren't rational nor market-driven, so then Coca-Cola has to get re-rated. But then you look at the people who are selling those tokens and this is where anthropic and open AI need to understand. If the government comes in and actually tells you that there's no open source, their valuation

will create it. Why? Because all of that revenue is artificially being propped up, it's not being driven by market demand, where you're being forced to compete, it's because of regulatory capture, where you now get an artificial constraint, but it only works in one market.

And so anyways, all roads lead to market chaos, love it. Yeah. If anybody gets involved, so we should just not get involved. What it sounds like is you're saying that American enterprises will pay token tax if the government gives an anthropic and open AI a government enforced duopoly and enterprises are

no longer free to use open source like the rest of the world. Don't spit on you. Yes. We'll put ourselves on an island, we'll be on an island of overly expensive AI. You can have Coca-Cola, or Pepsi, or Coca-Cola, or Pepsi.

Yeah. Well, it's not your beverage choice. You have two beverage choices, but they cost 50 times more than Coke outside of America. This is the point. We already have Coke everywhere.

So you can buy 50 cent Coke or 50 dollar Coke, why would you buy 50 dollar Coke when you go buy 50 cent Coke? Yeah. All right. Let's get, let me get free.

I was going to say just just one thing on this. This goes back to my point of these proposals to band open source that are coming from anthropic. They don't solve the distillation problem.

“If distillations are problem, you have to stop it at the source.”

In other words, if you want to band open source in America, the rest of the world will still be using Chinese open models, one of solve that problem. Yes. That means they'll get the data and they'll get the reinforcement learning. Then we lose the AI race, guaranteed, freedberg.

Let's take it from a gram Allison and level up the discussion here. Would be quite provocative to band the Chinese models, how do you Xi Jinping respond to that? How does the CCP respond to that?

This is a crazy chessboard.

It would seem like a pretty escalatory and would be going up the ladder.

That freeberg? Yeah. Look, I don't think it's relevant that the open source model is published by China. I get that there may be security risks that those can be estimated and addressed.

“I think on the three things that are worth highlighting on this issue, I'm very much aligned”

with Saxon Chema. I think the three things are really around distillation. I don't think distillation is just about AI. Distillation is a process whereby you look at the end product that someone else has produced in thinking about and learning about how to engineer your product.

It is a common technique that is used across every product category in every industry. One car maker will look at how the other car makers car operates and they will use that to help them design a better car. At Google, in the early days, we would submit millions of search queries to Yahoo and Microsoft search engines to see what the results were and we would compare our results against

their results as a way of improving our search engine rankings and our algorithm. It was a very common technique. It doesn't mean we were stealing their algorithm. We didn't go into their servers and steal their software. We looked at the output of their software and used that to improve our software.

It was called benchmarking, right? It was banking. You can call it.

It has been a million terms exactly right.

I don't think that this matters as much.

“I think the question around copyright infringement or IP infringement.”

That's our strategy. That's our strategy. There's a terms of service question here, but that's on the service provider's to fix. The terms of service blocking people from doing this if they so chose.

The copyright argument, the IP argument is really about, did they steal the software? They didn't steal the software and they just looked at the output. That's not IP infringement, that's not copyright infringement in the classical sense. I do think from a distillation IP argument perspective, it's the output not the process that matters.

The question is, are they taking copies of copyrighted software and using it, or are they looking at the output, and so I think output not process of engineering is what you really need to assess here. Can I insert something free between comment on it? I think a lot of people in the, let's say policymaking community don't understand this distinction,

but I think everybody in tech does, and I think it's a big part of why there's a disconnect on this, is there's a huge difference between model weights and outputs, right? So the weights are the, it's the file of numbers, it's the numerical parameters in the core code, that's the software, that's the code. And if Chinese companies were to steal, that's the weights, proprietary weights from

anthropic or open AI, that would be theft, that's right. But that's not what we're talking about here, because no one's accused that, what we're talking about here is taking model outputs and then trying to learn from them using other people's software to learn. Yes, and it's exactly the situation you said with like the Google searches or whatever.

“And here's the thing that's so hypocritical is that open AI and anthropic have both argued”

that they are free to train on all the world's output, regards of whether the creator wants them to or not, that's right, that is their current position, that's like Jamoth mentioned in the New York Times lawsuit, the New York Times is soon suing open AI right now, if you're going onto the New York Times website, in violation of the New York Times terms of service, scraping all the information and training on it, and open AI's argument

is look, we're not sealing anything, we're taking the output of the New York Times and we are deriving our own model weights. And that's exactly what these 200% are doing is they are taking the output of America models and then they're doing their own weights, they're learning from it. Yeah, and so the accusation they're just so we're clear here is that there is ethical

issues around the industrial scale, covert, breaking of terms of service, that's what the White House has been. In terms of service, yes, well, yeah, just to people understand, there is a bit of recognition to me. Yeah, look, let me be clear that I'm not defending China in this.

In fact, you know, look at my, my bona fides, I was the first administration official

to even talk about distillation, I did it in January of 2025 when Deep Sea came out, I went to Laura Ingram, and I think I was probably the first person in the government to even explain this concept publicly to people. And moreover, you know, as a co-author of the winning the AI race report in which the whole premise of it was that we want to win, we want to be China.

So, you know, I'm definitely not someone in this camp that doesn't want the U.S. to win. I want the U.S. to win. The question is how, and if we should ourselves in the foot by banning open source, which is to say, not letting all of our American companies take advantage of open source, when the rest of the world is able to, then that is a huge problem.

Now, I'm fine with anthropic and open AI enforcing their terms of service. They need to a better job, stop the distillation from recurring the first place. If there's things that the government can do to help them, okay, but I'm not sure what those things are, what needs to happen is those companies need to do a better job enforcing

Their terms of service.

Yes. Okay.

“Now, freeberg, you had, you said, I think you said you had free points for make.”

I think you made one. I want to get the other two out of you. Yeah. so the other one was just on the free speech argument, which is, look, what is an open source model? And I think the audience needs to understand this if you're not from the software industry.

But open source is a downloadable package of software. You can think about it as downloading a text, a book. You just got all the code. Once you get the code, you've got it on your computer. You don't have to be connected to the internet.

You can just run it and use it. And I think part of the challenge that's going to be faced here, if there is any attempt at restricting open source, it's going to open a can of worms on how do you actually enforce

restrictions on open source because you're basically telling people once they've downloaded

and gotten a copy of this free publicly available software, they're not allowed to use it. And that becomes a real challenge. I don't think we have a lot of great precedent for that.

“It's going to be very ugly to try and stop open source.”

I do think there's a question on like copyright action. But if there is, there's a legal due process to go through to make that case and stop that open source from being available. And then my third point is just open source is better for the world to jump off point. This is a hundred times cheaper.

That is better for the industry, for enterprise, the beneficiaries are going to be the economy, the consumer, fundamentally. If you look back on the internet, in the early days, Netscape made a proprietary browser and a proprietary server software, the Netscape software. And they went public and they were the first to do this and it was super valuable and profitable.

And the company ended up getting crushed because of open source. The Mozilla foundation was formed to create an open source web browser called Firefox. And then Google ended up hiring everyone and made a Chrome, but it was still open source. The Apache foundation set up the first HTTP server as an open source product rather than having to pay Netscape or Microsoft or Oracle for their server software.

Anyone with a computer could download the Apache software and make a web server and be on the internet and create a website.

“And what ended up happening is the value accrued to the internet.”

It didn't accrue to the small number of software providers that controlled the gate and the portal of the internet. Basically, everything got open source and Google took off and eBay took off and Etsy and Amazon and all the millions of small websites and all the millions of small businesses. And everyone that benefited from an openly accessible open source internet.

If the internet was closed and there was proprietary software gates and portals throughout the internet that everyone had to pay to get through. The internet would not have taken off and the economy wouldn't have grown. And all these jobs would have been available. It was called AOL and copy serve.

Exactly. And now, when we look at this analogy, the analogy here is if open source AI takes off, then all the worries that Bernie Sanders and Elizabeth Warren and all the socialists are harping and larking about are not going to be the case anymore because you're not going to see all the value of AI accrue to two or three or four companies and their small group of billionaire

shareholders.

What will happen is AI proliferates and a million AI integrated enterprises all over the

world will benefit. Everyone will benefit. The economy will grow. Jobs will be created and AI becomes a power for good for creating an open economy. So I know that some people that are listening to this in the government and on the other

side are going to say, but, but, but Chinese open source versus American open source let it all proliferate. And frankly, if the Chinese are violating copyright stealing software, go after them for that, put in place trade sanctions, do all the sh*t you can do to stop that from happening. But fundamentally, open source AI will transform the global economy and will ensure that

the economic value of AI will diffuse to everyone and not be held captive by a small number. One percent that controls open source, we have to make that the oligarchs are going to get their clocks wrong and we don't need to have a wealth tax. Chamathi, we're going to add to this.

We have to acknowledge that it's incredible how fast the value capture at this segment of the market has basically evaporated.

I've never seen it in my 25 years in Silicon Valley where a sector of the economy can absorb

hundreds and hundreds of billions of dollars. And then you think that there's going to be economic pricing power many decades into the future and it effectively evaporates in months. Months. It took off in months.

Remember? Remember to begin with. And it's evaporated in a month. No, I got it. This is an area where I disagree with you guys.

It evaporated strong term. It does look like it could slow down or it could or it could plateau. No, it's actually make your argument and I'll give you my argument. Yeah, but let me pull up the anthropic revenue chart before you go there, SACS because we can this will help mitigate it here and educate the audience.

So as you can see here, we got a little bit of a stall in Anthropics revenue in the last couple of months and it seems and this is third party tracking. So it's not perfect data, but we do see that this is a clear headwind.

Then do you have the second chart I had, I talked on the pod just last week o...

week before when we're having the discussion about open source and like I think it was

Brad Gerser from Altimeter was talking about, hey, tokens are still growing. Well, there are routers that track open router. The better and open source model does than the easier it is to implement on your own servers and take it in house, et cetera. Those are dark tokens.

They're not recorded and you're not going to see them show up on a revenue chart anywhere because they're free essentially, you just need to have servers and energy to do them. And here you see that now well over 50% and a lot of these are coming from Chinese. By the way, so I want to be clear before you give the counter. I'm not saying that these companies won't make money.

That's not what I'm saying. But what I am saying is that markets are very savvy in looking through current earnings and asking a very specific question, which is what does this revenue look like 10 years from now? Does it go up?

Does it go down?

“Is there more competition or is there less competition?”

Is it effectively monopolistic or is it more of a commodity? If it's a commodity, how many people can price this good at what prices the market clearing price of that good in 10 years? And all I'm saying is, normally those variables get exposed. Those cards get turned over relatively slowly.

And so you have 5/10 years cycles to transition from being an exclusive provider of a good to effectively a commodity provider of a good. And all I'm observing is it's so unique that only technology could create a market where that cycle could get compressed into a few years because it is very hard if you're an allocator of money to sit there and look at this data and not wonder to yourself why it's not a commodity

in 5 to 7 to 10 years. And when they get to that conclusion, which every capital allocator will, because it'll be pretty negligent to not, it's very hard to assign huge future premiums. And where the real money is going, by the way, and we saw it in Google's earnings, which I'm sure we'll talk about.

It's going to the infrastructure. It's going to the infrastructure. Yes. So by the way, there's another cohort of people that don't want to see the end of open source.

They want to serve the cheapest models possible because they know that's where all the margin capture is. What's your, where's this going, Sacks? Is it both open, we're going to see a proliferation? I mean, as far as I'm concerned, there is an unlimited appetite for on demand intelligence.

And there is going to be, I don't think there's an upper bound for how much intelligence you can tap as long as it's continues to get better, which then the thesis would be. Yeah, it's a commodity. And the prices keep going down, but consumption keeps going up, what your thoughts on.

“You have to assume that this is exactly the example that you guys used.”

It's a web browser. And in a web browser, it's a mechanism to get to a place. And so the apps that are actually the places are where the value is captured.

And I think if you assume for a second that intelligence becomes completely ubiquitous, it's

widely available. The marginal cost of it is effectively zero. The energy to generate it is effectively zero, which I think is an accurate assumption. It's very hard to make the case of why this isn't like the browser. And it becomes just gets subsumed into the Amazon web services cloud businesses, Elon's

web service, et cetera. Sachs, where do you think this is going to go to our second story, which is the IP story, third story is going to be the markets and Google specifically in Tesla and space. Look, there's been a lot of violent agreement on this show so far. So let me just make the counter-argument.

I think that both open source and closed source will be big winners in this. I think the market is huge and they each serve their purpose. What happened is with the introduction of Community K3, there's a little bit of a panic in which everybody said, "Oh my God, all the Chinese models have caught up and they're giving them away for free."

And they're going to destroy our leading American frontier labs. And anthropic and open AI are running around saying, "Listen, we can't continue to invest billions of dollars if Chinese companies can distill our weights." So that's the argument that they're making that government officials are responding to.

The truth of the matter is that, "Look, when Kimmy K3 first launched, I was concerned

“about it because I was like, "Oh, has China caught up?”

Are they now able to produce a much cheaper frontier model?" Then the detail started coming out. So Ben Thompson on his blog went through some of the cost numbers and it turns out that Kimmy K3 is not that much cheaper to run. There's not a significant cost advantage to it.

So that's point number one. Point number two is that China has not caught up. It's true that Kimmy K3 scored really well on the arena battle ground for front end coding, for web development. But that's just one test. This is one dimension.

There are areas where it scores really well, but there's lots of other areas where it doesn't score that well. So it is not a clear advance or a clear catch-up to the leading American models.

For over, you still have stuff in the labs by Enthropic and OpenAI that is wa...

this. And the reports are that Sam is going to wash it over the next week to go talk about GPT 6.0, which is blowing the doors off. So I don't believe that China has really caught up. I think there's--

“So it's going to go see Daddy and what is he going to ask for?”

I think there is incredible unreleased models in the pipeline and we need to let our horses

run here and not slow them down with a bunch of unnecessary hoops. And if we do that, I think we're going to be just fine. I don't believe that China has caught up. I still think we are six months ahead. And then just the final point on this, if you look at revenue, which is the test of real

usage in the real world, Anthropic and OpenAI are blowing the doors off. They are by far the fastest-growing tech companies at scale that we've ever seen. Jason, you showed this chart that supposedly shows a hiccup and Anthropic. Listen, their internal forecast was to 10x this year from 10 to 100. We're in the middle of the year, they're ready over 70 billion of ARR.

They're easy again to get to 100 billion. And we don't really know what this little blip is here. I think one thing it might be is that OpenAI, if you superimpose the OpenAI chart on this, they have re-accelerated over the past month. So I think that if you were to add OpenAI codex is excellent.

Codex is excellent. And I think they're taking a little bit of share. And Sam is out there tweeting that we've got our mojo back. And they're taking their forecasts up.

“I think they were expecting to end the year at 60 billion of ARR.”

And I think they're forecasting more like 75 billion of exit ARR. So my guess is that if you were to superimpose OpenAI and Anthropic and looked at them together and you were basically just to say that, you know, let's call it the frontier model toopoly in the US, you do not see any soda, you don't see any blip. They're taking their forecasts up.

And the reality is that if distillation is going on, it's been a thing for, you know,

again, I pointed it out back in January of 2025 with Deepsea. So it's been a thing this entire time that they've been growing exponentially. So I just don't believe that these guys are actually suffering in any way. I don't think they need government protection. I think they're growing exponentially still.

This is a little bit of a case of, you know, what do you call it in basketball when a player flops, you know, you do a flops? Yeah. We try to flap or whatever. Yeah, it's a flop.

Yeah. Well, or you, you basically act super dramatic after a foul in order to call the chart. You're foul baiting when you're trying to get a foul and then you're flopping, which is just making like an exaggerating, like LeBron does. And that's exact.

Yes, it's a LeBron, it's a flare flop, you know, where these guys are trying to, they're trying to draw the foul. They're trying to get the government to intervene. Now, why are they doing this? Because they're in the middle of road shows right now.

And Tramoth to your point, I do think they get the legitimate question about why won't you be commoditized over time by open source. And by far, the best response that would be that if they can lure the government into giving

them a government protected doopily, then that would be incredible.

The best answer is what you gave an anthropic and open AI should own this because they're good at it, which is they're going to go up the stack to the application layer. Well, they are done, like, I know, but they've done it in this way, which is a little hand-handed in some cases, but they're excellent at it. These end-user apps are really good, and they should just own that.

And that should be their answer to Wall Street, which is guys, we have the best model. We will eventually go up the stack. And if I were them, I'd actually practice the following answer. There may be a version of a model that I don't release and just keep for myself and I'll just use my own applications.

How about that? Well, that would be. That's true. That's true. That's a competitive idea.

That's true. They're not to build a model and not release it. It would use a control. Hold on. Let me answer that.

It would be anti-competitive in the eyes of their customers. It might not be in the governments. But if you are using them as a customer and you're lovable, which I talk to, and they're paying a ton of money for your 11 labs and you're paying them a ton of money. And they say, hey, we got our latest and greatest.

You can't use it because we're going to compete with your company. They would stop using and they go to open source.

“I'll tell you why so I think you're wrong on this issue.”

I think open source is having its moment. I work with startups. They are all moving off of these and they're using open source and they're using it at much cheaper rates because a lot of the jobs don't need the latest models. They can use these, the last generation models and people are moving them local.

They're hosting them themselves. This is, I think, a non-zero chance that this is going to derail anthropic and open as IPOs and they're going to derail them. They're going to be fine. They're going to be fine.

They're going to be fine. They're going to hold their lane. I'm making my point shut the f*** up for 30 seconds. I believe that this is going to derail their IPOs. I'm taking it from the top.

It's going to derail their IPOs. It's going to be headwinds against it because I think that they're going to have massive margin compression. I believe they're spending so much money that I think they're going to get caught in a trap.

I think this could be a trap for them.

They overspend, they don't have the same profitability and it doesn't pencil out and start up are the future.

“The start-ups are what eventually the enterprise copies, I think you're wrong, sacks go”

ahead. Ah! I'll come back. I'll come back. I'll let you out the response.

I'm going to jump it. I'm going to jump it. You're wrong. I think they have caught up for 95% of the jobs. This is a crazy habit.

I'm not saying that the IPOs are wrong. But I think that their market has and the headwinds are coming, I think they answer such chances that they're going to get slowed down.

I think the answer is slightly different.

It's not that 95% of the bleeding edge tasks can be done by everybody. It's that 95% of the tasks can be done by many different models. That's the actual answer. And that's OK. And by the way, exactly right, Jamoth, by great.

It's also OK for anthropic to say, you know what? I have this next generation class of model. I'm going to instantiate, I don't know, a life sciences program, a cybersecurity business, that's where they can capture as Sachs was saying before, over time, trillions and trillions of enterprise value because I do think they have excellent models and they have excellent

engineers and they have momentum. But if you're going to build the business model that tries to ascribe this layer as having

“a lot of terminal value, I think that that is a mathematical mistake.”

That's it. You can't do it. That's a headwind to these comments specifically because because all of their best customers and I talk to them, whether it's lovable or 11 labs or the startups that were spending hundreds of thousands of dollars with them every quarter, just last six months ago, they

have all moved on mass, GLM-5-2, making their own models. The cats out of the bag, they are going to start losing a lot of customers to open source and Google and AWS and Elon Web Services are going to host them and how do I know this? Every time I do a job, I'm using Proplexity Computer, not a paid partnership or anything. It just happens to be the best harness that I found.

And I start with Grok, Nemotron, GLM-5-2, and I also put it into Claude and the results are as good or better. In other words, I can't even tell the difference between these. Let's superimpose the open AI numbers on top of the anthropic numbers because I think it supports the point I'm talking about.

Yeah, these are estimates, by the way, this is not like literally from the companies, just want to make sure. So, according to this company that, I mean, look, who knows how they drive this, we don't know that they're totally true.

They're basically showing that OpenAI's run rate, which is ARR, it rose from 33 billion

in May to 41.3 billion in July. So they're seeing acceleration, like I said, I mean, Sam was out there saying they got their mojo back, they're going to have their best 12 months forward looking at ever and look and thropping is still growing really fast. We've talked about this on a previous show.

It's not physically possible to grow 10x year over year forever. You'll run out of compute, you'll run out of energy, you'll run out of every pulse. Yeah, there's just no way to do that. But anthropic, I mean, look, if any, if any, if anybody had said, and thropping would be at over 70 billion in the midpoint of the year back in January and there are 10 billion.

Nobody would have said it. You would have said this is the fastest growing tech company of all time. The idea that they're at risk of getting their entire franchise destroyed, it's not in the data yet. It's what I'm trying to say.

And moreover, Jamoth to your point, it's not only about the model, it's also about the harness, it's about the connectors, it's about the enterprise agreements. There's a lot of things here that you need in order to grow a business like this. And this idea that they need to race to get government protection, because of a competitive risk that might happen in the future, I think it's just kind of unseemly and gross.

I mean, this is literally the most successful tech company of all time, and they're racing

“to the government to basically say you need to protect us against our competitors, aren't”

just our trainees. No, our potential. Our future can come out. Potential future. Yeah.

They should hire Lina Khan.

Basically, it's gross and just make a couple of examples because I know people don't have

a lot of sympathy for Chinese companies. That's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example, Muram Moradi, her new model.

Making machines, thinking machines, they currently have the best American open source model. You know how it was trained, it was bootstrapped. It was distilled off a Chinese model, can make K2.5. Now, if you say that Chinese model is based on IP theft, what is thinking? It's a derivative work off a model that anthropic is trying to tank.

As being IP, by the way, there's been no evidence that this is no evidence-free process. They are simply trying to paint with a very broad brush here and say that now, that model is tainted. Let me give you another example, so cursor rolled out its new product composer, too.

They were able to post-trained that model using K2.

Okay, so think about this.

“They started with a Chinese open source model and then they used their own data and they”

came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. It is open weights that are freely available to anyone.

It's a file, okay? And you take that, you fork it, you run it on your own hardware in an American data center. No packets are going back to China. No data is going back to China. Nothing is going back to China.

An American company is taking open source contributions in the public domain, made it their own, and then develop their own model. And if you say that American companies can't do that or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem.

“And that is exactly what inthropic ones, because they do not want to have the competition.”

Freeberg. Maybe you can close this out here and then I'll put my thoughts on you. I'll just do that for a second. And I'll say, think about the strategy as well for China. If you think about the global economy of the last 50 years, the US has accrued so much value

by being at the core of the knowledge economy and effectively a services economy. And in that sense, through the development of intellectual property of IP of knowledge, and then the conversion of one bit to another bit, we've been able to drive trillions of dollars in GDP. Meanwhile, we outsource manufacturing and created a sleeping giant in China where they have

this incredible manufacturing capacity.

And at the end of the day, if you think about the course of like human technology evolution and human prosperity, it's largely driven by our capacity to convert molecules from one form to another and use the least amount of energy possible to do that. That all of technology ultimately leads to that simple equation, molecule conversion, making that beautiful couch behind you at the lowest cost possible, making materials, making semiconductors,

making all this stuff, everything in our world is driven by molecule conversion. So at the end of the day, if the knowledge economy and the services economy gets compressed, much like AI and open source AI in particular, effectively flattens that value. Because all of that value is now open source, it's free and it's simply a function of turning on a switch and running it.

The value of the U.S. and the Western economy has been largely degraded. And what's left is the value of the molecule economy, the ability to convert molecules and use energy to do that. When you look at the juxtaposition of China versus the United States today, we have one terawatt of electricity production capacity in the U.S. and they're on their way to having

eight.

We have about 10 billion square feet of manufacturing capacity.

So they have 200 billion square feet of manufacturing capacity. So they have 20 x the manufacturing capacity, eight x the electricity production plus all of their other sources of energy. And I think that's the long game for China over a decade to three decade process is by compressing the knowledge economy and the services economy, commoditizing it completely,

they are left holding all the value in the global economy because they can make stuff. And they can make it cheaper than anyone because they have the most electricity production. That's a very simple rubric for kind of how I look at the long game that they're trying to play here. You believe they're trying to commoditize this very important space.

Just like they did for global knowledge and global knowledge and global services. The creation and movement of bits gets commoditized and what's left over is the creation of electricity and the creation of molecules, both of which they have this very difficult to surround advantage that's going to make them the core dependency for the world.

“That's what I think it's kind of the long game here.”

And just so you know, this data comes from reports in places like the information or other sources or leak numbers and they try to just make charts based on it. Yeah, and by the way, I, you know, I have my own sources too. I've talked to investors in these companies and I'm just telling you that both inthropic and open AI are taking their estimates up right now, their forecasts up.

So, I mean, look, I think in the future, it may be the case that open source takes share. Fine, it's because the market's so big.

And there is always a market for open because open is more controllable, it's more customizable.

You can own it. You get the data sovereignty, you get the sovereignty, but it's also more work. So there are different use cases, there's different parts of the market. And that's actually very interesting, the more work part they are sacks is super interesting. Like three to six months ago, it was so much work to stand these up.

Now there's so many intermediaries building the harnesses that default to it ...

is getting worked out.

“But that has always been the issue with open source for sure is the amount of work it takes”

to implement. If you do want to implement this inside of your organization, please make a call to 8090 and try the software. You used to promote a fake app to give you a free consultation at 8090. All right.

Can they get a free consultation? Well, everyone's talking there, but I'm not actually including, I'd say the endthropic and open AI investors.

It's amazing how many of these investors showed two weeks ago.

You on the episode, Brad was like, let me tell you why this is going to, he's holding on. He's holding on. I actually get Brad a lot of credit because I didn't think that he's objective about public policy or as objective as you can be given that he does own all these companies.

But look, let me just tell you that, you know, I see a lot of folks who are suddenly China hawks and saying, we need to stop China. We've stopped. We've stopped. I have a disclosing first, whether you're on the cap table of anthropic.

Absolutely. Are you guys on any of these cap tables? No, I'm not directly. Not directly. Not directly.

Yeah, the center. Yes. Indirectly maybe got little access. You know what it's like? It's like when you, you've got that great flush or straight and you're like, please don't

pair the board. Brad's like, don't pair the board. Please don't pair the board. All right. I've here we go.

I love open source. I love, I love this open source, say I love it. I think it's so awesome. The value. So punk rock.

It's just like there's so much to be done with it. It's just exciting and awesome and yeah, too much point is exactly right. Most of the models can do 95% of the tasks. And if that's the case, then it's not like everyone needs to scramble to get the best open source model.

You just need open source to do 95% of what you want to do with AI. And then the other 5% you get specialized or high value or you pay a premium.

“And by the way, if you're a big enterprise and you need to have wrappers and support and”

all these other tools for your employees by anthropic or open AI or grockstools or Gemini, like just make sure you have options. Make sure you have a good partner. Use promo code Jcal. You get a zoom call with your mom.

Okay. Zoom call with your mom. You have a zoom call with your mom. Take a selfie with your mom. I'm sorry.

Yeah, anyone can assign a $10 million contract with 8090. You can have three to four bucks for a five-month zoom call. Absolutely. You get to pay $10 million. We're all going to pay $10 million.

You get to guess how he's on the pod. And anyone ready to make a pre-purchase on a million dollars of potato seed. You also get to have the best. You want to promote a sexy poo. Yes.

And if you'd like to guess toast the first person to put a $25 million check and

to launch on five, guess to guess moderate an episode with your boy Jcal. All right. From the most city this week. All right. Anthropi.

Copy rights. Here we go. Anthropi can settle their AI copyright lawsuit for $1.5 billion. Billy. On Monday.

Copy rights settlement, Friedberg, in the history of the United States of America. First major AI trading lawsuit to settle there are many more in the pipeline and thropic, downloaded seven million books from pirated websites to train Claude. And that alone, it may or may not be a crime. This has been adjudicated a little bit in the courts.

They had ruled previously that AI on copyrighted books is legal under fair use, but there's going to be some future cases. So this is a settlement. They didn't go to the bat.

Lawyers getting 101 million authors get 3,000 above 500,000 books were covered in it.

Thus far, 91% of the covered authors have claimed their share. Tons of other ones are on the way. And here's your second victory path, fat of the episode. Contemporary voters as a group need to get together and fight for their rights in your sense.

Fight for the right to party. No, fight for the right to get paid and to survive. Can you go to the chat, TVT and say, as a group either give us these terms or don't index us, they are interfering with their ability to leverage their own content is profoundly unfair.

“And those magazines and new spy predictions, too, what's up?”

It's possible. YouTube is a great example. That's what's going to happen. They'll be a settlement where they are going to be a no claim they are going to claim. They're not claiming.

I will bet any amount of money. Let's go back. Let's get back. You're your, your, your premonition here, J. Cal, this is okay. Let's make a bet.

I'm going to go with for my biggest winner. Now, 2024 training data owners like the New York Times Reddit, X Twitter, YouTube, etc. I think what we learned in 2023 was at the language model, so starting to hit parody very quickly. And that the real value is going to be in and it may have become commodities and open source

may win the day. So then I think the winner is folks who have the training data, you know, the best thing

About this is watching Jason's reaction to Jason.

Jason. Why did you take your picture of me? Just be like, oh, go, J. Cal, free birthday. We make a bet here. Did we make a bet?

I don't know. Thanks God. Well, actually, this settlement, I don't think quite proves exactly what you want it to prove, J. Cal. Good.

Can I make a new answer, okay? Of course, of course. Okay, look. And obviously, I'm not a huge fan of Anthropics.

“I think they're potentially destroying the whole ecosystem for their own purposes of regulatory”

capture. But let's just be very clear about what? Let's just be very clear about how many times are you? Yeah. Let's just be very clear about what this judgment was and was not.

So what Anthropic did is they pirated all these books from Libgen and they trained

on them and the reason why they got in trouble is because they basically took stolen books.

They didn't even pay for one copy of them. But if they had paid for just one copy of each book, they could not have been nailed for piracy. They would have been potentially under fair use, which I understand J. Cal is still being litigated in the courts, but that would have been their defense.

So the reason why they got nailed with this $1.5 billion judgment is they wouldn't even buy one copy. It is still Anthropics position and it's opening eyes position that they should be able to train on all these books under fair use if they buy one copy. And that issue has not been resolved yet.

“Now, you should be able to see the total hypocrisy of their point of view, relative to”

the previous issue, which is they believe they should be able to train on every creator's output in the world, you know, as long as I guess they bought one copy of it against the will of those creators, whether those creators like it or not, they believe it is fair use to train their models and derive their own weights based on fair use.

However, they say that the one type of content that you should never be able to train on

is their output. That is currently their position is completely hypocritical. And actually, if you go back to Anthropics blog post in February, where they define this concept of industrial-scale distillation attacks for the first time, they coin that expression. And this is, you know, I worry that people in the government policy makers don't understand

that this is all part of it. And Anthropics op, no one used the terms distillation and attack together until Anthropics wrote that blog post. Disilation was simply an industry standard practice. But then Anthropics coin this idea of industrial-scale distillation attacks and any of that.

If you go to that blog post, search for the words IP theft. It's not in there. Anthropics did not claim, even though they were trying to coin this new concept and brand this idea of industrial-scale distillation attacks, they did not have the Hutspa to claim that it was IP theft.

The Cohones, the hypocrisy, the Hutspa to claim that it was IP theft. Why? Because they maintain that it is their right to train their models on all the world's output even if the creators don't want them to. IP for we, but not for thee.

Exactly. So J.K. I don't even want to get into whether you're right or not on the fair use question. Maybe you are right. I don't know.

But my point is about the hypocrisy and they themselves never claimed that this was IP theft

by the Chinese companies. What they tried to claim was that it was a national security threat because what would happen is these Chinese companies would distill off them, create their own models, and those models would not have barred rails. So they were making a different kind of argument, that argument never found purchase with

“policy makers because I think that they could see that, look, guard rails are important.”

But it never really found purchase until anthropic started claiming, oh, this is IP theft. But they have not been willing to make that argument publicly because they know that it would poison all of their fur use lawsuits that are happening. Which Moth, like you mentioned, the New York Times is currently suing open AI for basically a industrial-scale distillation attack.

I mean, open AI went on the New York Times website use scrapers, slurped up all of their information at a scale that no human could achieve, and then they used that as training data and reverse engineered the model weights effectively. So my point is that even anthropic and open AI won't publicly admit that what China's doing as IP theft because they are doing it themselves is totally hypocritical.

And I don't think policy makers should be making arguments that these companies themselves won't make because they know that they will lose all these court cases. Freeberg any thoughts here on an obviously, this is still being litigated as we've discussed as 150 major cases New York Times is one of the music. Let me ask you a question, Jika, let's say you have a question for me.

Let's say your book, you're a book, I don't know, let's call it genuflecting ...

The great American novel. It could be angel in 11 different languages, so you write this book, okay, at your hopper counts. And you opt to not submit it to AI because there's a restrict, you keep it closed. No one can read it.

We did Google search, you can't be on one set, no one can read your book, you're not letting anyone read it.

“You want to pay for your book, if you want to read it, at someone pays $30 for”

a genuflect the Great American novel, and they read it, and then they write a review. They publish their review on the internet. Now, on the internet, the review where it talks about your book and describes your book gets web crawled by an AI engine, the me AI engine learns from that, learns about your book, and now there's some commentary made about your book when someone asks a question about

your book in the AI engine. Do you feel like your copyright was violated in that sense?

So the AI never ingested your book, it ingested metadata about your book, it ingested reviews

about your book, it ingested third party analysis about your book, all of which was on the open internet, and it didn't just pop you that stuff, but it used it to learn about your book. So you're saying these 1500 reviews for Angel, how to invest in technology SARS, time was advised from an angel investor turned to 100,000 into 100 million.

These reviews would then be the basis of the AI, so I guess I would have to be okay, but just like this eloquently brash blueprint for Angel investing, that verified review. Yes, I would be fine with that five-star review being in there, okay, so then you have no knowledge. You have no knowledge, you have no knowledge, you have no knowledge of morphology, how many of those 1498 reviews did you not write three, okay, so I'll tell you the secret when you guys

actually get asked for right a book, or any of you have the capability of completing a book. Yeah, because I'm 97 years old living in the United States, what bottom did you use? What bottom did you use? It's 2017. Now we know where he pointed that stupid open source AI slot can and that he's building. [laughter] I'd burn by the purchase too.

[laughter] I'd burn by the purchase too. I'd burn by the purchase too. I'd burn by the purchase too. I'd burn by the purchase too.