Meta Tokenmaxxing, Intel Joins Terafab, Frontier AI vs. China | Diet TBPN

Well, there is a whole bunch of news to run through.

The first story is that meta-employees are apparently token

maxing and competing on an internal leaderboard called

Claude Enomics for status as a token legend.

This is from the information.

Over a recent 30-day period, total usage on the dashboard

topped 60 trillion tokens.

And this sparked a huge debate over how much is meta actually

spending with Anthropic.

Of course, the other big news is that Anthropic just

passed 30 billion in run rate revenue with one of the,

probably, the steepest revenue growth chart in human history,

absolutely legendary.

Yeah, this chasing status as a token legend

reminds me of maybe as a year ago at this point,

you were saying, well, tokens ever become like eyeballs

the way eyeballs were during the Dock combo era,

just optimized for eyeballs.

Obviously, not every eyeball visit to a website.

It's created equally, but people were optimizing for eyeballs.

And now, you know, the reaction to this, I think, has been

generally at least online, like been, I guess reassuring.

A lot of people are saying that Gary Basins says,

you, why? Marty says, good heart's law.

When a measure becomes a target, it ceases to be a good measure.

So who knows what's actually going on internally,

but we do know Zach is pushing the entire company to be

as a non-AI native as possible.

And this guy loves spending money, too, right?

I have a crazy bull case here that I will run through.

Let's get through some of the story.

First, we got to pull up this comic from XKCD in the comments here.

When a metric becomes a target, it ceases to be a good metric.

It's right under the leading post.

There we go.

And says, and the other counterparty says,

sounds bad.

Let's offer a bonus to anyone who identifies a metric

that has become a target.

It is good.

I don't think that's going on here.

Later was texting a friend at Meta,

and sent the post we just discussed on token maxing and said true.

And the person said, yes, it's pretty sad.

But I mean, imagine.

So Meta has been rumors of Meta layoffs for a while now.

Unclear how many, if any, if any have happened.

But if you're sitting there, the company is not

just saying we need to get AI native.

Boss is saying we need to get AI native.

And then suddenly there's a token leader board.

You do not want to be at the bottom of the list.

I will say that, right?

Yeah.

You don't want to be the guy who's having to explain like,

no, well, I've actually getting the most out

of each incremental token.

And the other guy is just like set up an agent that just counts one

to the same thing over and over and over and there's something.

Yeah.

Yeah, I mean, you have to measure the actual output,

the impact on the business.

I mean, fortunately, Meta has been a huge beneficiary

and a huge winner of AI.

The ads are getting better targeting.

They're seeing.

They're delivering more ads and the quarterly earnings

have been strong.

The headline number here that sort of took everyone

by surprise is that Meta staff used 60.2 trillion tokens

over 30 days, which would pencil out to about a third

of inthropics ARR was the number that was thrown out.

But both of these claims are pretty questionable.

And so Tyler did some back-of-the-envelope math

to show that the one third revenue estimate is way, way too high.

And I don't know.

Do you want to take us through some of the reasoning there?

And then we can talk about the knockoff effects of all that.

Yeah, OK.

So 60.2 trillion tokens is the number.

Like, we can just assume that's true.

So basically, I'm going to assume all the employees

are basically just using Opus 4.6.

Yeah.

So then there's basically three numbers you need to look for.

In like the API cost.

So there's like input.

There's a cached input.

And then there's output.

So for Opus 4.6, it's $5 per million tokens on input.

It's $0.50 per million tokens on input cached.

And then it's $25 on output.

So if you multiply that 60.2 trillion tokens

at the highest possible rate, $25 per million tokens,

then you do get like a billion dollars in them.

Yes, which is crazy.

That's not what's happening.

But you have to think about it.

If you're using cloud code or any of these coding agents,

the vast, vast majority of the tokens used is input.

Because so imagine you're working on some coding file.

There's 1,000 lines of code in the file.

Maybe the model's only changing 10 at most.

So that's a very small percentage.

So the output tokens are going to be a very small percentage

of the total tokens going in, right?

OpenRouter publishes a lot of this data.

So you can use those ratios to figure out

what are the actual numbers of the input versus cache versus

output.

So just to get sort of like market standard averages

like baseline benchmarks.

Now Meta could be using these tools differently.

But if we're to assume that the shape of their agent

to coding efforts are similar to the average,

this is what the numbers will look like.

So maybe there is some bad incentive

where people are just saying to the model

like count up to a billion and then do it again.

So then it's like totally skewed.

But if they're doing it relatively normally.

So on OpenRouter, it's about 98.9% of all tokens

are input, and that's including hashed ones.

Because you're stuffing the context window

with all your code base or a huge amount of context.

It's going to be fine.

That's changing every time so you can cache it.

So then that's like 1.1% is output.

So basically, if you basically get all the numbers,

million tokens is going to be $2 and around 26 cents.

So that'll get you to something like $136 million

a month for the $60 trillion tokens, right?

So that's way less than the 900.

So that would be 1.6 billion a year, like run rate.

Still huge.

But that is still in the max.

Assuming they're in the top.

Yeah, that's assuming that OpenRouter,

the breakdown of how they're using the tokens

is the same as OpenRouter, which I think it's not.

If we see in that, that's $4,500 per engineer.

If there are, I think, 30,000 engineers at Meta every month,

$4,500 on tokens.

$4,500.

That's actually in line with what I've

heard a lot of other people spending

in terms of their token budget.

Yeah, that's not absurd.

That's not absurd.

If you're trying to incentivize people to use that.

Yeah, not at all.

But so you can actually see the breakdown on OpenRouter

of how people are using tokens.

So 17, the biggest plurality is OpenClaw, which is 17.6%.

And then CloudCode is 16.8.

So I think if you think about CloudCode,

you would imagine that in CloudCode,

there's the percentage of cash tokens

is going to be higher than in OpenClaw.

So I think Meta's usage is actually

going to be more heavily based on the cash tokens.

So if you do it just based off CloudCode usage,

you'd actually see a higher percentage of the input tokens

be of the total tokens, so it's only like 0.8% is the output.

So then if you get all those numbers through again,

it's only like $55 million a month, which

would be $669 million a year, and each engineer

would be like $1800.

Yeah, that's actually pretty low.

Which is like, I think, very reasonable.

John Chu, over a coastline, says Plenty,

of my metaphors told me, folks have been building bots that

just run in a loop burning tokens as fast

as they can due to this policy.

It's an absolutely stupid policy

and is similar to how Meta uses lines of code

to measure engineering output.

Managers are supposed to use it as a proxy

and dig in to understand where complexity,

but plenty of managers are lazy and just don't.

Thousand response to Christina over at linear saying,

ranking engineers by token spend is like me ranking my marketing

team by who's spent the most money.

Yeah, we may not have had our KPIs,

but Joe spent 200,000 on a branded blimp that only flies

over his own house, so he's getting promoted to VP.

I'm pro-branded blimp, though.

I like that idea.

So my take on this was that, yeah, it sort of ties

with Jensen Wong was talking about a GTC.

He was saying that an engineer that's making $500,000

might soon command something on the order of $250,000

a year in token budget.

Under Carpathia had a similar line.

He said, it's all about tokens.

He said on a podcast last month, what is your token throughput

and what token throughput do you command?

And so Meta actually has two different harnesses internally.

They have a version of OpenClaw called MyClaw.

And then they also, of course, acquired Manus,

but it appears that they're running a clawed,

maybe Opus under the hood to actually generate the tokens

that come through those harnesses.

The interesting thing is that at 250K AI budget per engineer,

you're at like 20,000 a month.

And so based on Tyler's math, this feels like, OK,

there's going to be another maybe four

acts to get to Jensen's prediction.

I think it makes clearer the strategy

with Meta super intelligence lab.

Because if you're looking at, it's

clear that they're spending hundreds of millions of dollars

on this just for internal code gen tooling,

like running their business.

They are going to spend an inordinate amount

of money on frontier inference.

And so training a model there, they

will be able to amortize the training

cost of the next model that they build,

not just over, can they get a product out that goes viral

and becomes its own stand-alone chat app that people pay for,

or maybe it's ad-supported, just on the internal usage,

they could be running a multi-billion dollar token bill

that they would have to pay another lab.

And so if they develop that internally,

it's pure vertical integration.

And then you also have everything that's

happening on the actual ad targeting and content delivery

side.

And when you add up all of those, all of a sudden,

the big question has been, does Meta

is Meta going to be able to launch an entirely new AI product,

like Vibes or something like that?

And this is a data point that, to me, says they don't need to.

Just from a pure vertical integration story,

the investment in MSL can pencil out.

I just want you to get to your Schizophrenia theory.

What's the Schizophrenia theory?

This whole token-maxing thing is like a barrage

while they distill the model.

Oh, oh, yeah.

I mean, there is a world where, if you're generating

trillions and trillions of tokens of a frontier model,

Meta is really burning through a lot of tokens.

And you have it generating everything.

Oh, we're just token-maxing.

Yeah, I mean, there's another story about distilling

we'll get to later in the show.

But there is a question about if I have a ride in essay,

and then I have a model rewrite it.

Those tokens, they are from that model provider.

They buy them.

They become mine.

Can I train on them?

That's probably out of terms of service.

So you would think, no.

But you sort of wind up in this ship of Thesias world

where if Meta pays anthropic $100 million or $1 billion

to go rewrite every line of code, every email, every slack chat,

every internal message, like basically

map the entire organization, rebuild it.

They wind up with an incredible training

corpus that they can use for their next model.

But I would imagine that they can't.

And I imagine that the enterprise contracts go both ways.

The lab can't train on the corporate information.

That's standard in all of the enterprise contracts.

And I would imagine that the opposite is true as well.

Although it is this fuzzy ship of Thesias world

where if you're using coding agents

to upgrade your infrastructure, and then you

want to run and train some model on your infrastructure,

do you have to pull out the tokens that were revised

by the AI lab that you don't have the right to train on?

It's all very interesting.

Apparently startups that have gone out of business

are able to sell their corporate histories

for something like a million dollars

to data brokerage firms and AI labs now.

Have you heard about this?

Yeah, heard about it.

Not skeptical.

I'm skeptical.

I mean, certainly there's a market for it.

But basically all the code needs more data.

But a company built over a few years.

Maybe they really code, but also usage

with a different enterprise.

Yeah, all sorts of different stuff.

In other news, Intel is joining TerraFab.

Yes, let's talk about it.

Intel is proud to join the TerraFab project

with SpaceX XA Antesla to help refactor Silicon Fab technology.

Intel says our ability to design, fabricate,

and package ultra high performance chips at scale

will help accelerate TerraFab's aim

to produce one TerraWat a year of compute

to power future advances in AI and robotics

and throwing up a post of hanging with Mr. Musk himself.

Let's go through the Wall Street Journal's coverage

of this.

Elon Musk is partnering with Intel

on his ambitious TerraFab project, which

aims to build specifically designed

chips for SpaceX and XAI as well as for Tesla.

In an announcement Tuesday, Intel said

it would work with the companies to design, fabricate,

and package ultra high performance computing chips

at scale.

The company shared a photo of chief executive lip

Bhutan shaking hands with Musk CEO of SpaceX and Tesla.

The partnership is a win for Tesla, which

has struggled in recent year Intel,

which has struggled in recent years,

leading the company to cut production capacity

when demand was surging for data center chips

and when competitors like Nvidia and AMD have thrived.

That was always a just such a tough pill to swallow

when you would talk to the ASIC companies like Siribras.

And you would say, like, you're doing something new.

You're not doing Nvidia chips.

Is there any way you could get off of TSMC?

And they're like, no, we still need to be in Taiwan.

Obviously, there's a huge geopolitical component here.

We can get into all that.

But last year, the Trump administration

reached a deal to acquire an equity stake in Intel

for around $9.00 to help secure the American chip makers

business.

The US government held 8.4% of Intel shares

as of March 20th, according to security's filings.

The figure doesn't include warrants that could increase

the government's equity stake in Intel.

TerraFab represents a step change in how

Silicon logic, memory, and packaging

will get built in the future.

Tesla and SpaceX confirmed the partnership in post on X.

Musk unveiled the plans for a single facility in Austin,

Texas to make chips to be used by SpaceX and XAI,

which merged in February as well as by the publicly traded Tesla.

He pitched the project as an opportunity

to quickly experiment on chip design by designing

and manufacturing the chips in one facility.

The fab will make chips for use in Tesla's robotaxies,

which they're already fabbing, I believe, at Samsung,

although they do have NVIDIA dojo chips,

or I think that are TSMC, the optimists will also need chips

and they are planning to use Intel for that as well.

So these are two areas of priority

for the electrical vehicle maker, as it chips

that spoke us to artificial intelligence

enabled products.

It will also make chips optimized for use in space,

where SpaceX is planning to deploy huge numbers

of satellites capable of handling and computing tasks.

Who else do you think they need to get involved here?

Because just the two of these got, you know, Intel and Tesla

coming together, it's good to have more involvement,

but still I think the entire project.

We've seen a few of those like AI leader gatherings in DC,

where you see Tim Cook and Sundar and Sam Altman and Dario

and all the leaders are together.

And I was always hoping that at one of those dinners,

they would say, okay, everyone's

going to try and say the biggest number, but this time,

it's going to be how much you're committing to Intel,

and how much you'll buy from them if they come online

with a competitive product.

Because the demand side has always been a big problem

for Intel, that they have the capability,

they have a plan to build the two nanometer, three nanometer

plant, like a frontier plant, leading edge fab.

But every other company has been so tied to TSMC.

But we, I think everyone now acknowledges the TSMC

is not investing super heavily in CapEx.

They're not going, you know, they're not scaling up

as much as the industry would like them to.

And so lots of folks have sort of signaled towards

a chip bottleneck coming in the next few years.

And Intel has the opportunity to communicate that.

This seems like the first step in that chain.

So companies, including Tesla, often designed

their own semiconductors, but need a supplier

to actually make the so-called chip fab.

Musk companies have source chips from a wide range

of suppliers, including Nvidia, Samsung, Taiwan semiconductor.

Oh, I got it.

Musk said that TerraFab is needed because his company's

demand for chips is slated too far outstrip the supply

it gets from partners.

I was listening to Chuck Robbins from Cisco talk

about data centers in space, and the heating issue

came up, and he was like, yeah, I don't really

have a solid answer for that yet.

But I do think that if you are bullish

on data centers in space, you have to start

with the fact that Starlink works in space currently

because it is doing compute.

You couldn't possibly put, let's be honest, John.

We couldn't possibly put a computer up there.

Yeah, there are computers with,

they can't inference frontier models,

they can't, it's not gigawatts in space yet,

but there are, I believe across the entire Starlink cluster,

megawatts of compute in space with solar panels,

and they do heat up because you are running a chip

that routes packets across the internet

from one satellite to the next to get you

your internet via Starlink.

And so it's not that it's a solve problem,

is that we are actually, we are on a path

to deploy some level of compute in space, Tyler.

Yeah, I mean, we've seen Philip Johnson,

there are chips in space right now, they're GPUs,

I think, he said they were like five or six,

eight hundred and hundreds, right?

Yeah, so they do work, it's like the,

yeah, I think most people's problem

with space data centers is that it's economically,

it doesn't make any sense.

Well, yes, that is the correct angle,

but a lot of people are getting it hung up on the,

no, no, there is a whole conversation

about it is impossible, and you need to move past that

into the economic equation,

which then gets you into timelines

and actually thinking about what needs to happen

to dissipate that heat, but clearly, yes, you can,

I mean, you can put humans in space on the ISS

and cool that, like we have created ways to move

heat around in space for decades,

it's obviously a new challenge,

but I think starting with the baseline of like,

there is compute happening in space right now,

we're going to try and, I mean, Elon wants

like 1,000 exit, 100,000 exit, million exit,

I don't even know what the scale is,

but orders of magnitude, and so there's new engineering challenges.

Speaking of space, it looks like Elon is going to use

SPCX as a ticker for the SpaceX IPO,

which he had to acquire from Matt Tuttle

as the ETF's ticker change shown below.

Eric from Bloomberg says,

we predicted this could happen in a December note,

nice catch by Will, who famously gave

a meta ticker to Zach, I did not know

that Will Hershey had the meta ticker previously,

so we know somebody that spots on,

who had the meta ticker?

Guy named Will Hershey, just a company called Round Hill,

but we know somebody who's been...

Look, there's Matt Ball.

We had somebody here,

come in, outside of show hours

and say that they were squatting on a bunch of tickers

and the idea seems so, I think what might be the reality

is that it needs to be further along than just reserved.

I don't know.

I think so.

Having it, you can go.

If you're a startup today, you can go reserve your ticker today.

Yeah.

But I'm not sure that actually gives you enough leverage

to when Elon comes knocking ready for an IPO.

You actually have a priority.

All right, we've got to talk about a corporate retreat

that went badly wrong.

Okay.

The technology company Plex took its 120 employees to Honduras

for a week-long bonding experience.

It was a disaster from the moment they arrived.

Senior executives at the Tech Company Plex were eager to treat

their 120 fully remote staffers

to a week-long corporate getaway in a tropical paradise.

Pop quiz, Tyler.

Do you know what Plex is?

I don't know about Plex.

No.

Have we seen Plex?

I don't know, either.

So, we all failed,

but now it's your job to figure it out.

I will continue.

The plan for the Honduras trip was simple.

So, the streaming company?

By powdery soft beaches during the day and island fun at night

at a cost of roughly half a million to the company.

They'd build the trip around a survivor theme

with teams and challenges.

But it'd be fun, not too physically grueling.

The CEO of Plex, a free streaming platform,

would play a role similar to that of survivor host Jeff.

Perhaps the executive should have taken it

as a sign that just as the first bus of staffers

pulled up to the resort.

The chief executive was already in his hotel bathroom

experiencing the initial waves of violent stomach infection.

What followed was a comedy of errors,

including military drills that outpaced anything

this group of office workers had in mind.

A rogue porcupine stranded airplanes

and one syringe to the butt of an employee.

Corporate retreats are generally assumed to be torture,

or at least a semi-stressful chore.

What with their forced fun activities and hybrid workplace

environments that leave workers confused about boundaries?

Is that, is that like the industry standard that seems wild?

I don't know.

I think I've ever been on a corporate retreat.

I've been on some like founders fund events,

but those aren't really retreats.

Those are more just like conferences.

But I don't know, corporate retreat seems,

I don't know, unexplored territory for me.

It's no wonder the new season of jury duty

a comedy series that tricks an unsuspecting non-actor

into believing his off-the-wall fictional circumstances

are actually happening is set at a corporate offsite.

But in real life, PlexCon 2017 beats anything on TV.

Here's the story of an all-staff company getaway

by six people who were there.

A trip where most everything that could go wrong,

did go wrong.

Nearly a decade later, they're still working together.

They're still talking about that.

So it's crazy that they...

It's crazy that they...

It was bonding experience.

Yeah.

Well, yeah, it's crazy that this is now coming out.

So Sean Hoff, 42, founder of Moniker Partners

and Independent Corporate Retreat Agency

that planned the trip.

About three weeks before we arrived in Honduras,

we got an email from the hotel's general manager

that said, I will be departing.

I wish you the best with your retreat.

I knew something was off.

Three days later, another email.

The head chef was no longer going to be at the hotel.

Scott, 52, Chief Product Officer in Plex co-founder.

We get there.

We've got to take the bus from the airport,

dirt roads.

You start getting closer and there are guard towers

around the property.

People with machine guns and stuff.

A lot of people were like, where are we going?

Keith, the CEO of Plex54.

We usually go day early and we set up.

If there's any little thing we have to get it right

just so the employees have the best experience possible.

Keith woke up the day that people were coming in Sunday morning

and he is sick as a dog.

Everyone there is fried.

Basically people are telling me, don't eat the vegetables.

Don't eat the vegetables.

Don't eat the vegetables.

That's like the same thing.

No, no, no.

Because they clean it.

They wash it in water.

It's usually not filtered water.

It would just be kind of crazy to...

Yeah, yeah, here it is.

I've got to have a salad.

Just one salad.

So I got E. coli, which maybe the worst thing you could get

possibly ever.

Just as people were arriving on the buses,

I had lost eight or ten pounds.

They had a doctor come to me, which apparently is pretty standard.

They nailed an IV bag to the bedpost.

People are arriving for a party that night.

The next day is a survivor theme kick off.

There is not one person on the planet more excited about survivor

than Keith and his wife.

They have watched every single episode.

My wife and I met Jeff, the host of Survivor What.

What I wanted is when everybody shows up, I do it Jeff.

Welcome to the island.

Here is the theme for the week.

But Scott got to do it.

The opening survivor thing was a contest where people

and their different teams open up a platter.

You have to eat what's on the platter.

Sean.

Sean, who's the placks had a business development.

Yeah, somebody is a somebody is a cold texting me.

Oh, yeah.

Pitching me their start up and they've called me a bunch of times today.

Well, he is actually them or is it their agent?

I wish I could pick up.

It's just like a little bit.

Yeah, it's a little too much to pick up.

But yeah, cold texting somebody like getting their number.

I don't think that's the new meta.

No.

It's bold.

Yeah, we heard from an executive in tech that they are getting

dozens of emails every single day trying to recruit them.

And every email comes from a new Gmail account that's unregistered brand new.

But it's all like LLM written very different.

It doesn't really do all the research but has a few keywords in there.

And it's clear that someone is building sort of like a next-gen recruiting agency

that's basically just a lot of spam.

It feels like the end result will be like a return to relationship building

and not like broad top of five.

I should read the cold text from this morning.

Okay.

Nothing again.

Nothing again.

Yeah.

Cold email and just, you know, being bold.

But I did read this out loud to you, John.

So I'll read to everyone.

So I got a text from an unknown number today at 7 a.m.

All right, Jordy.

Good news or bad news first?

This is blank.

And I'll leave the name out.

And then I just get a PDF of a deck and then a text.

All right, Jordy.

The bad news is this was an unplanned introduction.

And on the surface, probably lukewarm outreach.

The good news is that there's zero doubt you're now in touch with the founder

with the most grit of anyone you've interacted with the past 12 months.

And likely anyone you'll interact with over the next 12 months,

50,000 seed round passes over the past 10 months,

here to make 50,000 in one.

So, so you know, you should be coming in being like,

I've been passed on 50,000 times.

Yeah.

I'm hoping this is the one that gets through.

That gets through.

That seems like a rough estimate, though.

Every month of feedback and iterations have made it better.

So you're seeing more quality, more quality presentation than rejection 10,000.

Looking forward to your message.

The chat wants the builder to pitch.

They want you to hear this out.

Everyone's in favor of this.

The chat wants you to get on the phone with them.

Do it live.

I mean, they wanted it to do live.

I don't know if you should do live, but you should take the call.

I will take the call.

I will take the call.

But let's go back to the corporate retreat.

Okay.

So they hire a former Navy SEAL to basically haze of the team on the beach.

And you can pull out the picture, an image here.

The quote is, this is not a super fit group in general.

One of our biggest mistakes was hiring a former Navy SEAL to pump the team up.

As I'm in my room dying, I could hear them out there doing all the drills and yelling.

And so I'm in here thinking, this is terrible.

But it sounds terrible out there, too.

We're doing army crawling on the beach.

It was 100 degrees.

I bailed out partway through.

I went into the ocean just to cool off.

I went in probably on all fours because I was tired.

It's not a super fit group in general.

The ex Navy SEAL is like, we can tone it down.

No problem.

We get up there and it's hot and humid.

And people are passing out.

I don't think he'd ever seen quite such an unfit group.

We ended on, I guess, what's probably a golf course.

On command, everyone had to hit the grass.

Everyone's silent.

We're pretending we're Navy SEALs.

But I happened to land in the wrong spot.

I'm just like, oh God.

What is happening?

I was sitting on a fire ant hill.

I was wearing shorts.

I jumped and had hives and bumps from the bites.

This is ridiculous.

Someone saw an alligator on the golf course.

Sounds like a ridiculous.

There was a porcupine that fell through one of the ceilings.

This is like a fire festival for the fire festival of corporate retreats.

Andthropic is taking steps to arm some of the world's biggest technology companies

with tools to find and patch bugs in their hardware and software.

The company is making a preview of its new AI model called Mythos,

available to about 50 companies and organizations that maintain critical infrastructure,

including Amazon, Microsoft, Apple, Alphabet, owned Google,

and the Linux Foundation.

Cybersecurity researchers and software makers worry that artificial intelligence

is becoming so good at exploiting vulnerabilities that it could cause widespread online disruption.

Security experts have predicted that AI models will discover an avalanche of software bugs

and the effort is set to help companies stay one step ahead of cybercriminals and other threats.

This feels like a very good rollout strategy generally,

both because we've seen a huge amount of cyber attacks and hacks and accidental releases.

Even if it's not, you know, there's been, we had a member of the security team

from CrowdStrike on the show last week talking about the rise in cyber attacks broadly.

Getting the most frontier models in the hands of big companies early,

great from that perspective, and also just great as a product demo,

which will get the entire organization excited about deploying the technology broadly.

So, very good is like a, as a B to B, go to market motion.

This makes a ton of sense.

In some other more positive news, open AI and Thropic,

Google, are you knighting to combat model copying in China?

This is a bigger discussion around AI safety.

We've talked about this.

Do you look at that?

Who knew?

I mean, I'm sure people in the chat have seen the New Yorker article

where there's just tons and tons of quotes from various AI leaders,

all, you know, upset with Sam Altman,

and the inter AI drama has been bubbling up since the dawn of open AI.

Like, opening AI was started as a reaction to Google,

and then, you know, and Thropic leaves and teams up with Google,

and then Elon doesn't like and Thropic,

and then Ilya Satskiver and Mira leave,

but they don't join in Thropic.

And so, there's been so many personalities and so many disputes.

I feel like the takeaway is that this is all extremely high stakes.

There's a technological transition happening,

a huge amount of money on the table,

a huge amount of influence on the table.

Everyone is sort of clamoring for their share,

and it's creating a lot of friction.

So, rivals, open AI and Thropic PBC and AlphaBet Inc's Google

have begun working together to try and clamp down on Chinese competitors,

extracting results from cutting-edge US artificial intelligence models

to gain an edge in the global AI race.

The firms are sharing information through the Frontier Model Forum,

an industry nonprofit that the three tech companies founded

in Thropic Airsoft in 2023,

to detect so-called adversarial distillation attempts

that violate their terms of service,

according to people familiar with the matter.

The rare collaboration underscores the severity of a concern raised

by US AI companies that some users, especially in China,

are creating imitation versions of their products

that could undercut them on price and siphon away customers,

while posing a national security risk.

And so, I was trying to square this question of distillation

and model commoditization with the news that,

and Thropic has reached $30 billion in run rate

and has agreement with Google and Broadcom

for multiple gigawatts of TPU capacity.

Like, clearly there is insatiable demand for Frontier tokens,

Frontier models.

They're incredibly expensive to train.

We saw in the Wall Street Journal that these-

Spectate training costs from-

Yeah, it was training at Andy inference,

but it was hundreds of billions of dollars.

So, the hope is that you're able to amortize that

over at least a couple of years, you know, a long time, ideally.

The shelf life of a model after you train it is pretty limited

if you're being commoditized and copied,

if you're being distilled, it's even faster.

At the same time, it's just staying on the Frontier

clearly leads to an incredible ramp in revenue.

So, is commoditization a real problem?

It feels like it's almost just more of a problem

from an AI safety perspective,

because you can't have the geopolitical conversation,

like what Bernie Sanders is proposing around different

labs working together, potentially pausing or slowing down,

or just even adding more constraints and reviews

before models get released.

It's harder to do that if you have a different country

that's racing ahead and moving much faster

and trying to close that gap.

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Goodbye.