All right, everybody. Welcome back.

Episode 282 of the world's greatest

podcast.

It's your podcasters's favorite podcast.

It's your mom's favorite podcast. It's

the All-In podcast. With me again, David

Sax up to you, David Freeberg. It was a

big week. It was a big week. Uh the

continuing number one story in the world

is Kimmy K3. It's 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 6 months behind not 12

months behind but now on par with models

like Opus 4.8 and GPT 5.6 six, which in

and of itself is extraordinary, but

about 50% cheaper and uh this has

created a bit of a panic similar to the

Deep Seek moment that we had here back

in early 2025.

The White House, David Saxs, has gotten

involved. Michael Katzio, friend of the

show, said, quote, "We have information

that Moonshot AI distilled anthropics

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 I think it was three weeks ago,

I I gave that to you as a hypothetical,

and here we are. On Wednesday, Wired

reported that Howard Letic,

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 better open

source models. Poly market says 45%

chance US government bans an open source

model in 2026. Uh that was a brand new

market started just it was at 22% a

couple days ago. Saxs um 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

opensource models. There's a lot of

breadcrumbs leading here. If you look at

a lot of the rhetoric around how models

need to have guard rails and that with

open source models, the guardrails can

be removed and therefore they're

dangerous. You see this rhetoric already

in Anthropics blog posts. Any threat

that they describe, they 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 and probing to

figure out what their position is here

or 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 and

he's always supported a let's say

lighter regulation more open approach

and that's why I think the

[clears throat] US is winning the AI

race. So I think that's kind of where

where things stand. Um

>> where do you stand? Where do you stand

Sax? 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 AI 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 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 their primary objective, Anthropic

would push to ban Chinese access to

American models, not American access to

Chinese models.

>> Yes, they could. And that is that is

achievable. They could block it. So

>> they're the ones in the best position to

block it. If distillation, if industrial

scale distillation is a national

security threat, they're 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

horse is out of the barn.

>> Yeah.

>> And the reality is that I think that

what's happening here is that in their

lust for growth, Anthropic has done a

very poor job at stopping distillation.

I mean they're saying that distillation

is occurring at industrial scale. Okay,

if it's industrial scale, it must be

pretty obvious to see. So 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 that's how it

occurs. But the more the more industrial

scale it is, the more obvious it is to

see. And Tamatha has been saying for a

while, why don't you KYC your customers?

Well, they know that if they KYC 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 that big a

threat, they should use a few points of

their 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 it

seems to me that this debate is all

backwards that the question should be on

Anthropic to explain why it's doing such

a bad job, not on the whole American

open source ecosystem to be punished for

Anthropic's failure. All right, Freberg,

I have a really good question for you,

but before we do that, Shimath, 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, Daario, this pod, other places

talking about, hey, open source is

ready. This is the moment. Get control,

AI sovereignty, etc. They must be

calling you up and saying, hey, okay,

we're ready. Like, 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

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 exfiltrate is essentially

trillions of questions and answers.

And Sax 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.

[snorts] 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 herring. The other thing on

distillation is everybody has at some

point distilled. The question is who is

distilling from whom? And it looks like

that funny meme 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 fine. Apparently, Open AI

distilled from the New York Times.

There's still an ongoing lawsuit. the

Chinese labs have distilled from

anthropic.

>> It's wholesale stealing everywhere.

Yeah.

>> Well, I don't want to call it stealing

because it's not clear who actually owns

the copyright in the first place. But

here should be the important

observation.

These models are getting commoditized

much faster than anybody thought.

And 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

closed 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 a 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 game by the closed 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 the

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 closed frontier labs,

especially when they're mispriced 25 to

50x 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

we can probably play that scenario out.

But 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

would 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 rerated. But

then you look at the people who are

selling those tokens and this is where

anthropic and open AAI need to

understand. If the government comes in

and actually tells you that there's no

open source, their valuation will

crater. 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 a token tax if the

government gives anthropic and open AI a

government enforced duopoly

>> and enterprises are no longer free to

use open source like the rest of the

world. Yes.

>> Yeah. The markets with the cap.

>> We will put ourselves on an island.

Yeah.

>> We'll be on an island of overly

expensive AI.

>> You can have CocaCola or Pepsi or

Coca-Cola or Pepsi.

>> Yeah. Well, it's not your beverage

choices. 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 Coke.

Why would you buy $50 Coke when you can

buy 50 cent coke?

>> Yeah.

>> All right. Let's get Let me get free

here. Yeah.

>> Okay. I was going to say just just just

one thing on this. This goes back to my

point of these proposals to ban open

source that are coming from anthropic.

They don't solve the distillation

problem. If dissolation is a problem,

you have to stop it at the source. In

other words, if you want to ban open

source in America, the rest of the world

will still be using Chinese open models.

We want to solve that problem.

>> Yes. And that means they'll get the data

and they'll get the reinforcement

learning and then we lose the AI race

guaranteed. Freedberg,

let's take it from a Graham Allison and

level up the discussion here. Would be

quite provocative to ban the Chinese

models. How does 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 we'll

be going up the ladder. Yeah, Freeberg.

>> Yeah, I look I don't I don't think it's

as relevant that the open source model

is published by China yet that there may

be security risks, but those can be

estimated and addressed. I think on the

three things that are worth highlighting

on this this issue, I'm I'm very much

aligned with Sax and Chim and I think

the three things are really around

distillation. And I don't think

distillation

is just about AI. You know, 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

maker's car operates and they will use

that to help them design a better car.

You know, at Google in the early days,

we would submit millions of search

queries to Yahoo and Microsoft search

engines to see what the result sets 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 use that to improve

our software.

>> It was called benchmarking, right? It

was benchmark. You can call it there's

been a million terms. Exactly. Right.

And so I don't think that this matters

as much. I think the question around

copyright infringement or IP

infringement

>> Sax is right. There's a terms of service

question here, but that's on the service

providers to fix the terms of service

blocking people from doing this if they

so chose.

>> But 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. And so I do think from a

distillation IP argument perspective,

it's the output, not the process that

matters. So 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? comment on

it is I think a lot of people in the

let's say policym 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 software code that's the code

>> that's the software that's the code and

if Chinese companies were to steal

>> weights proprietary weights from anthrop

ropic or open AI that would be theft.

Okay, 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 and

>> using other people's software to learn.

>> Yes. And it's exactly the situation you

said with like the the Google searches

or whatever. And here's the thing that's

so hypocritical is that OpenAI and

Anthropic have both argued that they are

free to train on all the world's output

regardless of whether the creator wants

them to or not.

>> That's right.

>> That is their current position. That's

like Chimath mentioned the New York

Times lawsuit. The New York Times is

suing suing OpenAI right now

>> for 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 stealing anything. We're taking the

output of the New York Times and we are

deriving our own model weights. And that

is exactly what these Chinese models are

doing is is they are taking the output

of American models and then they're

deriving their own weights. They're

learning from it.

>> Yeah. And so the accusation though, just

so we're clear here, is that

>> there's ethical issues around the

industrial scale covert breaking of

terms of service. That's what the White

House has been terms of service as well.

So just so people understand like there

is a bit of recognition of that.

>> Look, let me let me be clear that I'm

not defending China in this. In fact,

you know, look at my my bonafides. 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 on 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, I was 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 beat China. So, you know, I'm

definitely not someone in this camp that

doesn't want the US to win. I want the

US to win. The question is how. And if

we shoot 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 do a

better job, stop the distillation from

occurring in the first place. If there

are 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 I think

you said you had three points to 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 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 Chimath's

point this is 100 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

that they went public, and they were the

first to do this, and it was super it

was super valuable and profitable. That

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 it

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 acrewed to the

internet. It didn't acrue to the small

number of software providers that

controlled the gate and the portal of

the internet. Basically, everything got

open sourced 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-sourced 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 called AOL and Coffee

Serve like and now 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 acrue 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 the I know that some people that are

listening to this in the government and

that are 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 copyrights, stealing

software, go after them for that. Put in

place trade sanctions. Do all the you

can do to stop that from happening. But

fundamentally open- source AI will

transform the global economy and it will

ensure that the economic value of AI

will diffuse to everyone and not be held

captive by a small number. Why the 1%

that controls open source if they have

it the oligarchs are going to get their

clocks rung and we don't need to have a

wealth tax. Chamathy 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

and it's evaporated in months.

>> No, I got this is an area where I

disagree with you guys.

>> Evaporate is strong term. It it does

look like it could slow down or it could

or or it could plateau.

>> Go ahead, Sax. Make your argument and

I'll give you my argument.

>> Yeah, but let me pull up the anthropic

revenue chart before you go there, Saxs,

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 uh in the

last couple of months. And it seems and

and this is third party tracking.

So it's it's not perfect data, but we do

see that this is a a clear headwind. And

then do you have the second chart I had?

Um I talked on the pod just uh it was

last week or the week before when we're

having the discussion about open source

and like I think it was um Brad

Gersonner uh from alimter was talking

about hey tokens are still growing. Well

there are routers that track open

router. the better an open source model

does and the easier it is to implement

on your own servers and take it in-house

etc. 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 to do

them. And here you see that now well

over 50% and um a lot of these are

coming from Chinese.

>> By the way, Sax, 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

price is 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

year 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 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 cloud.

It's going to the infrastructure. So, by

the way, there's another cohort of

people that don't want to see the end of

open source because 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, Sax? Is

it both open? We're going to just see a

proliferation. I mean as far as I'm

concerned there is an unlimited appetite

for ondemand intelligence and there's

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 be better which then the thesis

would be yeah it's a commodity and the

prices keep going down but consumption

keeps going up. What's 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, etc. Sax

where do you think this is going? Then

we're going to go to our second story

which is the IP story. Third story is

going to be the markets and Google

specifically and Tesla and SpaceX.

>> Look, there's been a lot of violent

agreement on this show so far. So, let

me just make the counterargument. 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 committee K3,

there was 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 just steal our weights." Right? 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 details 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 was 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 battleground

for front-end coding for web

development, but that's just one test.

That's just 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. Moreover, you

still have stuff in the labs by

Anthropic and Open AAI that is way ahead

of this and the reports are that Sam is

going to Washington 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

>> Sam's going to go see daddy and what is

he going to ask for? I think there's

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 6 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 open AI 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 in

anthropic. Listen, their internal

forecast was to 10x this year from 10 to

100. We're in the middle of the year.

They're already over 70 billion of ARR.

They're easily going 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 open AAI, if

you superimpose the OpenAI chart on

this, they have reacelerated over the

past month. So I think that if you were

to add Open AI,

>> Codex is excellent. Codex is

>> 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

forecast 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 open AI and

anthropic and looked at them together

and you were basically just to say that

you know let's call it the frontier

model duopoly in the US you do not see

any slowdown 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 deep seat 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 um you

know what do you call it uh in

basketball when a player flops you know

that you did a foul flop or whatever.

>> Yeah. It's a flop. Yeah.

>> Well, or you you basically act super

dramatic after a foul in order to draw

the charge. You're foul baiting when

you're trying to get a foul and then

you're flopping which is just making

like an exaggerated thing like LeBron

does

>> and that's exa Yes. It's a LeBron

>> it's a flare flop, you know, whereop

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

Chamas, 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 to that would be that if they

can lure the government into giving them

a government protected duopoly, then

that would be incredible.

>> The best answer is what you gave and

anthropic and open AAI 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 already done

>> I know, but they've done it in this way

which is a little ham-handed in some

cases,

>> but they're excellent at it. these

enduser 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 in my

own applications. How about that?

>> Yeah. Well, that would be

>> that's the real answer. That's

anti-competitive.

>> This No, it's not. They're allowed to

build a model and not release it and use

it for themselves.

>> Hold on. Hold on. Let me answer that. it

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 talked to, and they're

paying a ton of money or you're 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 cuz we're

going to compete with your company."

They would stop using it 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 uh the last generations models

and people are moving them local.

They're hosting them themselves. This is

I think a nonzero chance that this is

going to derail anthropic and open eyes

uh IPOs and

>> they're going to they're going to

they're going to be fine. They're going

to be fine as long as No, hold on. Let

me finish guys. I'm making my point.

Shut the 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 startups are the future.

The startups are what eventually the

enterprise copies. I think you're wrong,

Sax. Go ahead. [screaming]

[laughter]

>> Well, I'll come back, but let your mouth

respond. Raise your hand.

>> You're wrong. You're totally wrong.

>> I think you're wrong. I think they have

caught up for 95% of the jobs. This is a

crazy head. I'm not saying that the IPOs

are off, but I think that their market

caps and the headwinds are coming.

There's a non-zero chance 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

okay. And by the way,

>> that's exactly right, Chimath. I agree.

>> It's also okay 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 cyber security

business. That's where they can capture

as Saxs 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 a 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. Open source

is going to be a spec a headwind to

these companies specifically because

because

all of their best customers and I talked

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 you know

six months ago they have all moved on

mass GLM52

making their own models the cat's 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

Plexity Computer. Not not a paid

partnership or anything. It just happens

to be the best harness that I found. And

I start with Grock, Neotron, GLM52, and

I also put it into Claude and the

results are as good or better. I in

other words, I can't even tell the

difference between these.

>> Let's superimpose the the OpenAI numbers

on top of the anthropic numbers because

I think it supports the the point I'm

trying to make.

>> These are estimates, by the way. This is

not like literally from the companies.

Just want to make sure people know.

>> So according to this company that I mean

look, who knows how they derive 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 is out there saying

they got their mojo back. They're going

to have their best 12 months forward

looking ever. And look, Anthropic 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 everything. There's

just no Yeah. There's just no way to do

things.

>> But anthropic, I mean, look, if any if

anybody had

>> if anybody had said Anthropic would be

at over 70 billion in the midpoint of

the year back in January and they're at

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 is what I'm trying

to say. And moreover, Jamas, 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 you know,

this idea that they need to race to get

government protection because of a

competitive risk that might happen in

the future, I think is just kind of

unseammly 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." Great argument.

>> Not just our Chinese competitors, our

American competitors, our potential

future competitors.

>> They should hire Lena Khan. Okay. And

frankly, it's gross. And just let me

give a couple of examples cuz 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. Ma Maratti, her new model,

>> thinking 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, Kim K 2.5. Now, if you

say that Chinese model is based on IP

theft, what is thinky? It's a derivative

work off a model that anthropic is

trying to taint as being IP. By the way,

there's been no evidence of this.

There's no evidentiary 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 2. They were able to

post-train that model using Kimik 2.5 on

their own proprietary coding data. 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's going back to

China. An American company has taken

open- source contributions in the public

domain, made it their own, and then

developed 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 Anthropic wants because

they do not want to have the

competition.

>> Freeberg, maybe you can uh close this

out here and then I'll put my

>> I'll just zoom out for a second and I'll

say it. Think about

the strategy as well for China. If you

think about the global economy of the

last 50 years, the US has acrewed 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 derive trillions of

dollars in GDP. Meanwhile we outsourced

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's

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 US 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 terowatt of electricity

production capacity in the US and

they're on their way to having eight. We

have about 10 billion square ft of

manufacturing capacity. They have 200

billion square ft of manufacturing

capacity. So they have 20x the

manufacturing capacity, 8x the

electricity production plus all of their

other sources of energy. And I think

that's the the long game for China over

a decade, two, 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 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 cars,

>> 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 surmount

advantage that's going to make them the

core dependency for the world. That's

what I think is 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 Anthropic 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

>> that's actually very interesting the the

more work part there Sachs is super

interesting like 3 to 6 months ago it

was so much work to stand these up and

Now there's so many intermediaries

building the harnesses that default to

it that that 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. Uh if you do want to

implement this inside of your

organization, please make a call to 8090

and try the software factory. Use the

promo code JAL [laughter] to get a free

consultation at 8090. All right.

Can they get a free consultation?

>> Everyone's talking their books.

Everyone's talking their books actually

including I'd say the anthropic and uh

open AAI investors. It's amazing how

many of these

>> Brad was on the show two weeks ago when

you on the episode Brad was LIKE LET ME

TELL YOU WHY this is going to he's

holding on he's holding on to this

actually

>> he's like

>> I actually give Brad a lot of credit

because I do 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 STOP

LIKE THEY'RE CHINA HOGS. EVERYBODY

WANTED TO SELL THEIR CHIPS.

>> How about disclosing first whether

you're on the cap table of anthropic?

Okay.

>> Absolutely. Are you guys on any of these

cap tables?

>> No, I'm not.

>> Not directly.

>> No, not directly. Yeah, that's

indirectly. Maybe got a little access.

You know what it's like, Chimat? It's

like when you you 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." [laughter]

All right. Here we go.

>> I love open source. I love I love this

open source AI stuff.

>> I think it's so awesome.

>> The value punk rock.

>> It's it's just like there's so much to

be done with it. It's just exciting and

awesome and yeah, Chimoff's 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 rappers and support and

all these other tools for your

employees, buy Anthropic or OpenAI or

Gro tools or Gemini, like just make sure

you have a good partner,

>> use the promo code Jal. You get a Zoom

call with your mom. Okay. [laughter]

A Zoom call with A ZOOM CALL WITH YOUR

take a selfie with him on Zoom.

>> I'm sorry.

>> Anyone's going to sign a $10 million

contract with 8090, you get [laughter]

to have uh three of the four of us for a

fiveminute Zoom call.

>> Absolutely. You get to call

10 million. You get to GUESS WHO'S ON

THE POD.

>> And anyone ready to make a pre- purchase

on a million dollars of potato seed, you

also get to have [laughter]

>> use the promo code Sax Poo. Yes. And if

you'd like to guest host, the first

person to put a $25 million check into

Launch Fund 5 gets to guest moderate an

episode with your boy J Cal. All right.

Uh Promo City this week. All right.

Anthropic Copyrights. Here we go.

Anthropic has settled their AI copyright

lawsuit for 1.5 billion

billy on Monday. Largest copyright

settlement Freedberg in the history of

the United States of America.

First major AI training lawsuit to

settle. There are many more in the

pipeline. Anthropic downloaded 7 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 a book. 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 p

fap of the episode. Content providers as

a group need to get together and fight

for their rights in unison. New York

Times Met for the right to party.

>> No. Fight for the right to get paid and

to survive. [laughter]

TBT 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 newspapers need to what's that?

>> You're going to get steamrolled.

>> It's possible. YouTube is a great

example. That's what's going to happen

here. There'll be a settlement where

they are going to be able to claim their

I will bet any amount against your your

your premonition here Jal. This is like

>> I am going to go with for my biggest

winner for

>> training data owners like the New York

Times, Reddit X, Twitter, YouTube etc. I

think what we learned in 2023 was that

the language models are starting to hit

parody very quickly and that the real

value is going to be in and it may even

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.

Did you do a picture and picture of me

just be like go Jac

did we make a bet here? Did we make a

bet? I don't know. He's gone.

>> Well, actually, this I'm this settlement

I don't think quite proves exactly what

you want it to prove. Jal,

>> go ahead.

>> Explain. Can I can I make a nuance here?

>> Of course. Of course.

>> So, okay. Look, and you know, 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 [laughter] what Let's

just be very clear about show anytime,

Daria.

>> Yeah. Let's just be very clear about

what this judgment was and was not. So,

okay, 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 cuz 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 Jal

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

Anthropic's position and it's OpenAI's

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. It's completely hypocritical.

And actually, if you go back to

anthropics blog post in February where

they defined this concept of industrial

scale dissolation attacks for the first

time, they coined 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 a

anthropic op. No one used the terms

distillation and attack together until

Anthropic wrote that blog post.

Distillation was simply an industry

standard practice. But then Anthropic

coined this idea of industrial scale

dissolation attacks. In any event, if

you go to that blog post, search for the

words IP theft. It's not in there.

Anthropic did not claim even though they

were trying to coin this new concept and

brand this idea of industrial scale

dissolation attacks. They did not have

the hutzbah to claim that it was IP

theft.

>> The coahjones the hypocrisy the kutzbah

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, so Jal, 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. Okay. 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

guard rails. So they were making a

different kind of of argument. That

argument never that argument though

never found purchase with policy makers

because I think that they could see that

yeah look guardrails are important but

you know 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. And Jimoth, like you

mentioned, the New York Times is

currently suing Open AI for basically a

industrial scale distillation attack. I

mean, Open AAI went on the New York

Times website, used 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 AAI won't publicly

admit that what China is doing is IP

theft because they are doing it

themselves. It's 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 um and

obviously this is still being litigated

as we've discussed. It's 150 major

cases. New York Times is one of the

music industry.

>> So you write this book. Okay.

>> Harper Collins

>> and you opt to not submit it to AI

because there's a restrict. You keep it

closed. No one can read your book.

>> We did for Google search. You can't be

on Google.

>> No one can read your book. You're not

letting anyone read your book. you want

to pay for your book if you want to read

it

>> 10 bucks

>> and someone pays $30 for Genule the

great American novel and they read it

and then they write a review [laughter]

and they publish their review on the

internet now on the internet the

reviewer talks about your book and

describes your book gets webcrolled by

an AI engine and the 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

Um,

>> so the book 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 copy

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 stars, timeless advice from

an angel investor turned 100,000 into

100 million. [laughter] These reviews

would then be the basis of the AI. So I

guess I would have to be okay. But this

like, you know, this eloquently brash

blueprint for angel investing, that

verified uh review. Yes, I would be fine

with that

>> fivestar review being in there.

>> Really?

>> You now have no knowledge. You now have

no knowledge of the above

[laughter]

1498 reviews did you not write? Three.

Uh, actually, I'll tell you the secret.

When you guys actually get asked to

write a book or any of you have the

capability of completing a book. Yeah,

because I because I'm 97 years old

living in the

>> What AI agent did have [laughter] you

used to what bot what bot did you use in

2017?

>> Now we know where he pointed that stupid

open source AI slop cannon that he's

built. [laughter]

>> I verified the purchase too.

Freeberg, [laughter] you make a great

point. You make a Oh, there it is.

Jennifer, great American novel.

Practical wisdom for mastering ambition,

building resilience and winning at life

work and innovation.

>> Master virtue signaling master virtue

[laughter] signaling.

>> Incredible. Incredible.

>> That's beautiful. That is beautiful. But

JL, I mean, this is my point. Knowledge

can't be contained. It's diffuse. And so

the form of copyright is very clear. The

case law and copyright's very clear. I

cannot lift text out of your book,

reprint it, and claim it as my own. That

is a violation of copyright. But my

reading of your book, my reading of the

reviews of your book, the diffusion of

the knowledge that arises from your

book, that is ultimately going to lead

to some abstract transformation of

knowledge into a new output that someone

might read. And I think it is very

unlikely that we will find ourselves in

a place where the idea that knowledge

transferred digitally, processed

digitally, and turned into other content

is going to end up violating copyright

in I understand your position. There are

workarounds. Obviously, we've always had

cliff notes, right? So, if a book became

good enough, somebody could write the

cliff notes of it. You can't stop that.

There's a four-part test for this. We

we've talked about this for three years

here on the pod. What I'd say is

American companies should take 10% of

their revenue, if they're building these

models, and do splashy cashy and do

settlements. And that's exactly what's

happening. If you're a copyright owner,

you should study what the music industry

does. They are raid dogs and they will

fight tooth and nail and keep you in the

courts until you submit and make a

settlement and agree that you're

licensing it and then that gives them

that case law and that settlement to go

to the next person and the next person

and the next person and that's why

they've been able to successfully defend

it and then if you're competing with me

that becomes the issue. So if you said

hey what's his book about and what do

people think about it what are the best

parts of it and that comes from the

reviews okay fine fair enough. The

problem is and I and I'll I'll share

with you there's been some other

lawsuits here that are making the way

through courts. What's going to be the

problem is the application level layer

that you talked about Shimoth as they go

into the application layer and they use

this. There's a there's a big court case

here. Obviously you know about some of

these but there are now other cases.

There are music cases. There's a New

York Times case. The one that's kind of

interesting is Thompson Reuters versus

Ross. This is a uh final judgment on AI

uh training copyright. There's a company

called Weslaw. They're like Lexus Nexus

and people have been trying to claim

that they can train on the outputs of

something like uh Westlaw. And when

you're in the same business as me that

has a special place in copyright law

because I have you're you're infringing

on my ability to use my copyright.

And your argument I think Fraber holds

up that it wouldn't be it wouldn't stop

somebody from buying the book. But the

second you are actually competing with

me like directly that's when these

things have problems. And that's why I

think the music industry is going to win

and and some other places are going to

win. But listen, this is

>> brand new territory. These lawsuits are

brand new territory and IP law does not

>> actually have the nuance yet. So we're

going to as a society have to make a

decision here on what is fair. I suggest

just like the self-regulatory group that

we talked about last week, all the AI

companies should get together, take 10%

of your revenue, put it in a pool, and

keep paying the people and getting

permission from them so you can get

updates on the content so you get the

next book so you get the next New York

Times story, the next Reuters story.

>> 10% is not going to satisfy the rabbit

dogs, let me tell you. They're going to

go for 100%. Now, JK, let me here's a

question I want to ask you. Yes. Given

that the fair use doctrine is not a

decided matter yet, given that anthropic

and open AI are embroiled in huge

lawsuits against very well financed

content creators and those communities

and the outcome is indeterminate and

there's billions of dollars at stake,

maybe even their entire product at

stake. Do you think that they have

potentially made a fatal mistake by

arguing that distilling content against

the wishes of its creator is IP theft?

>> Do you see what I'm saying?

>> Yes.

>> Like, is this potentially a fatal

mistake? See, here's what they could

have done.

>> Well, you would bring that to the

Supreme Court and you say, "Hey,

listen."

>> But here's what they could have done.

What Anthropic could have done is they

could have said, "Listen, we have these

Chinese companies are creating fake

accounts and they're using proxies to

basically use our product in violation

of our terms of service." Now,

>> using those model outputs is not IP

theft because it's fair use. However,

it's a deceptive business practice for

these guys to lie about who they are

when they set up accounts at scale. And

so, they're engaged in a deceptive

business practice. and we're going to do

everything we can to stop that, but we'd

like the government's help in stopping

that, too. However, we not we're not

saying anything about IP theft.

>> Yeah.

>> Wouldn't that be the more nuanced

approach? Of course, because I think

that they're on the verge of being

hoisted on their own petard here.

>> Yeah. I mean, it's a cell I think that

kids call it a cell phone, right? Like

you basically

>> it's just a classic cell phone. And you

know, in most of these cases,

settlements happen. So again, if you

just look at the music industry, the

newspapers, the magazines, and some of

those folks and book authors, they've

tend to be very meek. There's a new

trend happening now, Friedberg, they're

a lot of content providers are saying to

Google, take us out of the index because

Google has one bot and that bot does the

Google crawl and that bot also does the

AI crawl. And what the industry is

saying is, hey, split that up. I want to

be in Google, but I don't want to be

indexed in AI. So people are now saying,

hey, we'll take you out of the index.

which Rupert Murdo got right. If all the

newspapers said collectively, "Do not

index us, Google. We're no indexed, that

would have made Google come to the table

and give them a royalty and give them

some money for being indexed."

>> I did that, dude. There was a there was

a deal that happened, but it didn't it

go the way you're describing.

>> Well, cuz they didn't have a united

front. Now, I think

>> these guys wanted they wanted Google's

user base. So, they ended up doing a

deal where they had this like payw wall

like exclusion rule whereas like you

could show a certain number of free

articles. There was a whole negotiated

settlement. Well, I'm talking even long

before that when the first index

happened. But here's I you know I I I

think we are on the cusp of a some type

of a settlement getting done here. Uh

and I think that would be good for

America to take a leadership position in

that because you do want to keep getting

that. But all of these content

companies, they should be meeting with

each other, the music industry, the New

York Times, all of them to stop their

content from getting used without their

permission and from competing with them.

That's my point. You know, you you only

get a settlement when both sides can

agree. And it seems to me that if you're

one of these content creator lobbies and

you see that Anthropic has just told the

government that training on a creator's

output without their consent is IP

theft.

>> Yeah.

>> They have now basically confessed to

their entire product being stolen. And

it seems to me that why wouldn't the

content creators now assert that they're

entitled to own 100% of anthropics

revenue? It seems to me that this could

be a bridge too far that you know that

that they're so good at regulatory

capture. They're so good at making these

arguments and getting the government

involved to create new regulations to

protect them. But I wonder if this was

just a little bit too cute. And again,

if they just positioned it slightly

differently, if they said, "Look, these

Chinese companies are creating fake

accounts. That's a deceptive business

practice. We're not saying this is IP

theft, right? But instead they said IP

theft and now the whole startup

community is activated. You saw that you

know Gary Tan and 200 startups wrote

that letter. Why? Because they know that

if this IP theft thing sticks that all

derivative works of Chinese models are

tainted now too. So that means the whole

startup ecosystem is now at risk.

>> Yeah.

>> So I just wonder if these guys have just

gone it's just all a bridge too far. I

mean, if you go to Washington,

>> Yeah. and you lay down with the dogs,

don't be surprised if you wake up with

the fleas. Like, you they decided to

engage in this, you know. So, they they

may have poked the tiger. Um I think I

think it's pretty accurate. Oh, by the

way, uh the publishing schedule for uh

2027 was released. We have some new

books coming. You heard mine, Jen, you

flecting coming to you now. Ferrari on

my wrist. How to win at life and afford

a [laughter] $250,000 watch from David

Sax.

>> Oh my god.

>> This is Pompic Sachs. [laughter]

>> We're going to get need to get that

done. Here it is. The fight to save

America: Destroying Socialism, Shrinking

the Debt, and Winning AI by David.

>> Yeah, it's a pretty good one. I think

this is our new all-in uh here it is.

Chama polyatina, [laughter]

a sexual Italian summer.

It's a romance novel. This is the only

person who [clears throat] decided to do

fiction. This is fiction.

>> It's fiction. It's fictional. Chimat,

[laughter]

>> I got Traumat's uh non-fiction novel

also.

>> Oh, you have his non-fiction as well.

Here it is. Here it is. [clears throat]

Enterprise sales. Chimat dystopia. How

my software startup [laughter] affects

my Italian summer.

>> There you go.

>> It's great. This is great. Oh my god.

Wow. That's coming from the allin

>> the IT guy in Milan.

>> Absolutely. This is This is coming from

Allin uh books. It's our new publishing

label coming in 2027. We'll also have

the Brad Gersonner, Bill Gurley, Elon

Musk, and other titles coming. So, we'll

have those on future episodes. More more

titles coming. Breaking topic here.

Google and Tesla shared their results

today. Had a lot of talk about capital

expenditures. Google blew the doors off

of their um

>> blew the doors off. I mean,

>> it was insane and outrageous. And they

were down like 7 to 10%.

Google Cloud growing

>> because of their cash%

year-over-year.

>> Yeah, because of the cash flow numbers.

And now is on a hundred billion dollar

run rate. That's but one business.

Tesla's capex surged 140% year-over-year

and they expect 25 billion in capex.

Google's capex forecast from 195 to 205

billion this year. So next year will be

even higher. Tesla down 14, Google down

7% of taping. Who knows? Um but both

reported negative free cash flow. In

other words, the amount of cash in the

bank went down instead of up. And for

Google, that was the first time ever.

IPO update, uh SpaceX down 30% from its

day one closing price, now trading 1.5

trillion. A lot of pressure on the

stock. We'll talk about that as well.

Obviously, they went public at 2

trillion. Got a big pop, uh the Elon

pop, and um there could be uh more

downward pressure or it could have found

a bottom. You know, you never know with

these things. This is unprecedented

territory. We've never had an IPO this

big, but some lockups. Here's the chart.

Bunch of lockups are are happening at

different staged intervals. So, let's um

Chimath

talk a little bit. Here's your SpaceX. I

guess capex chimoff is being built out

obviously for AI and there is the case

of open AI spending on capex in order to

provide their service but then there's

also Google which is making these capex

investments to resell it as part of

Google cloud incredible product and then

on the other side they're using it for

their own obviously infrastructure and

their business is just growing like

crazy whether it's YouTube or Google

cloud or even search is still growing So

I looked at this and I said, "Well, this

seems like a really good use of capital