In the Loop AI

There's no easy way to say this, but the stock markets are getting crushed because

three of the richest men in the world might have called the top of the AI bubble.

One of them is Elon Musk, one of the biggest proponents of AI in the first place.

He thinks that there's not enough capital and money in the market to support

the expensive buildout of AI.

And Ken Griffin, the CEO of Citadel, agrees with them. He says we're almost

certainly in a bubble. Chamath thinks that 75% of every single dollar spent

and invested in AI is being subsidized by venture capital.

And AI stocks are down horrendously, particularly neoclouds,

who have drawn down on average around 30 to 35% over the last couple of weeks. Absolutely brutal.

But what doesn't make sense about me and where the alarm bell started ringing

is each of these three individuals have an incentive to say that thing.

Elon Musk most famously recently took SpaceX to a pivot where they weren't just

a rocket company or AI company, they also became a neocloud.

So it makes sense for him to talk down on his competitors.

And Ken Griffin's Citadel is rumored to be short billions of dollars worth of semiconductor stocks.

And Chamath, he says it in his own words, owns a bunch of power and energized

land. So he might just be talking his book.

Now, the reason why I'm creating this episode is kind of self-serving in a way.

I am an investor, I invest in some of these markets, and I'm trying to figure

out what's actually truthful from what they're saying, and what actually isn't.

I want to debunk anything and everything and see what actually makes sense.

And I figured a bunch of you are also investors or investing oriented as well.

Or maybe just some of you just want to know what the hell is going on,

because it's affecting pretty much anything and everything from an investment

perspective out there. It's affecting global macroeconomic indexes.

So let's get into all of this and more on today's episode brought to you by Qualcomm.

So it all started off with this one tweet from Chamath, where he basically lists

out a lot of reasons why neoclouds and investing in compute GPUs,

the capex intensive part of AI, is currently in a bit of a precarious situation.

Neoclouds are disorganized and very poorly capitalized. Neoclouds being the

smaller startups and companies that aim to provide compute for AI labs that

want to train and inference their models.

He's saying they're poorly capitalized they can't get access to enough money

to be able to fund the compute that they're promising these companies and so

it's ending up becoming a bit of a bubble or bottleneck due to power and energy

stuff and Elon Musk decided to pile on here and he said as of the past few weeks

debt markets have almost entirely shut off access to money

for any company that doesn't have substantial revenue independent of AI data

centers he then goes on to say that means the 200 plus neoclouds are going to see

guppy level death and consolidation some will make it through, but not many.

And obviously, the market's reaction to this was terrible.

There was an entire near cloud meltdown, as you're seeing on this tweet,

where stocks just cratered and tanked.

And it's interesting to see, one, because these guys have such a huge amount

of influence on social media to influence these markets at such a great capacity.

But two, this was the second time these guys have done it in a week.

Last week, I was talking about how the core we've trade kind of became unwound.

It was down, I think now 35% after Chamath and Elon Musk wrote tweets about

them being over-levered in the debt market. I made an episode back then basically explaining.

This was kind of not exactly true. Yes, they're taking out a lot of debt,

but they had a huge amount of revenue backlog to back it up.

And Chamath himself even said that it isn't as bad as everyone is making out

and that the market is actually overreacting.

Chamath's point is that 90% of AI spending that we see today,

that Drive, Anthropic's massive ARR that we saw in the S1 yesterday,

and OpenAI's rumored ARR, comes from 1% of companies.

And 80% of that revenue, of that spending, comes from VC subsidized dollars.

So subsidized from venture capital, aka coming from startups that don't actually

have the revenue or profit to be spending that money. They're just spending

the funding that they raised.

And so the point that he's making is if this napkin math is true,

then we are in a heavily inflated bubble that is bound to either pop or recede

pretty aggressively over the next year.

And he makes the case that it's going to happen mainly in 2027.

We're going to see some form of consolidation.

Now, Elon Musk piling on, particularly around neoclouds, I find very interesting

because SpaceX's entire MO,

the reason why they had blockbuster revenue earnings literally last week.

Was because they became the number one Neoclod provider. So forgive me if I'm

just a little bit skeptical as to why Elon might be talking his book.

This is coming from one of the biggest Elon fans out there. And their words

have had a pretty gnarly impact. The markets have been wiped of around $1.6

to $2 trillion over the last 14 days.

Staggering and it's part of a broader drawdown that we haven't seen for a significant time.

The last couple of years has been up only and you could consider this nearing

a recession type indicator.

But the sector that's suffering the most are neoclouds and the three main ones

CoreWeave, Nebius and IREN are down around 30 to 35 percent over the last couple

of weeks absolutely shattering the market caps now the reason why this is a

problem in their situation if you were in their boots is

they need as much capital as they can get they need as much favorable credit

financing aka money that they can borrow that they can get to be able to buy the gpus to

set up the data centers to then do their entire business.

So you can see how this could end up in a house of cards or domino style collapse.

But at the same time, I see some form of justification behind what Ken Griffin,

Elon Musk and Chamath are saying.

The number one indicated being that there are currently millions of dollars

or rather billions of dollars worth of GPUs sitting collecting dust in data centers.

And if you don't believe me, take Amazon's word for it, where they have openly

said that they have millions of dollars worth of GPUs collecting dust.

Because they can't quite find the power and electricity and access to the grid

to be able to switch them on.

Now, this is okay, typically, but eventually it becomes cumbersome,

where you end up actually losing money to the tune of $1 to $5 million a day.

And I saw something recently, which basically indicated that now these companies

who have been promised data centers stood up by a certain time,

if it gets delayed, they are owed $1 to $5 million per day.

And insurance markets are coming out of nowhere saying, okay,

we'll back this kind of debt.

And these are the same insurance providers that are lending the money in the first place.

Now, I'm not trying to get too complex here, but what I'm trying to describe

is this is a very circular loop that is forming.

And this is not something that we have been secretive about in previous episodes.

I've spoken about it quite blatantly and honestly here, but we're starting to

see the actual evidence of these deals, what's being kind of signed on behind

the scenes actually forming and what might give this a bit of substance.

And even banks and chief economists, I think the chief economist of Apollo Global

actually went online over the weekend and posted his thoughts.

And he basically said that, listen, aside from the top seven companies in the

world who are actually using AI profitably, so per employee,

they're making actually more money than they did, let's say a year ago.

The other 493 companies in the Fortune 500 are not doing this at all.

In fact, they're probably losing money. So I'm a bit at odds here.

Now let's take Chamath's first claim, which is 75% of every dollar spent in

AI is heavily subsidized by venture capital.

Now, I'm from the start going to say I don't necessarily disagree with this

take. I definitely do agree that there's a bunch of subsidies being made here,

but I don't think it's as extensive as he's making out.

And I thought about that immediately yesterday when Anthropic released their

S1 file, which is their pre-IPO financials. And I looked into it.

And one astounding thing for me was, one, how much cash they had on the balance

sheet. It's around $132 billion, by the way.

And two, how much they've burned on compute over the last year.

We're talking about one of the leading AI labs here who have spent the most

to train and inference their models to create the number one leading model.

Guess how much they spent of that?

Only $7 to $9 billion.

So they're very capital rich at this point. But there was also another important

detail in the S1, which said that of all of Anthropic's main enterprise customers

who were spending anywhere between $100,000 a year to $10 million a year,

this only accounted for 0.1%,

of their entire annual company budget.

0.1% of the entire company's money that they spend in a year is being spent on clawed models.

I don't know about you, but I thought that number would be way, way bigger.

And it just highlights that not only is companies or labs

generating the revenue that we hypothesize and speak about, but they're also

making it in a way where it's not really too damaging to the books,

which implies that there's probably more to grow here and more money to be spent.

And maybe I just can't wrap my head around what that number might look like.

Now, the second claim, which is showed beautifully by this Apollo chart over

here, basically says that of the 90% of money that is being spent in AI.

It's all focused on 1% of companies. And I guess this doesn't surprise me too much.

If you are AI native or trying to pivot your business to become AI native,

it makes sense that you are spending as much time experimenting with these different

AI models and tools to try and figure out how to accelerate and automate parts of your business.

It kind of makes sense that the concentration of spending is happening in these few companies.

And that gray box might actually signal future potential growth for the AI sector as a whole.

But equally speaking, if they are right, and it is all coming from VC subsidized

dollars and only from 1% of companies in the world, the question is,

why aren't the other 99% of companies actually using this thing?

And my answer is, I don't think they're not trying to use the thing.

I just don't think they've realized whether these models are useful to them in the first place.

And so there's this weird gap that's widening behind the people who are AI obsessive

and are spending all of their money, capex and time trying to figure out how

to pivot to become AI native.

And then the rest of the world that just don't really know what's happening

that interact with a version of chat GPT, or maybe even an older model of Claude.

And they're like, yeah, this thing hasn't really changed over the last year.

Now Elon's point around neoclouds not being able to access financial capital,

I think is starting to materialize now. It maybe wasn't the case six months

ago, but it is now because only investment grade lenders. So these are.

Providers that are able to gather the amount of capital, which is a lot,

like we're talking about tens of billions of dollars to back up all the promises

that these neoclouds collectively have made.

Is hard to come by because capital used to be abundant, but is no longer abundant.

You've got OpenAI that is raising rumored to be around $30 billion that I think

they've recently closed.

You've got SpaceX, which announced that they officially closed $40 billion on

some higher interest rates than they did a few months ago.

And you've got Anthropic that closed $63 billion worth of compute,

but actually required Broadcom CEO of Hocktan to walk into the banks in the

last hour to try and convince them to actually close the deal.

So the question I ask myself is, well, if they're tentative on the biggest AI

lab in the world to give them that compute,

then why the hell would they give that to the neocloud smaller providers who

don't have the AI research expertise and revenue backlog that a bigger company like Anthropic has.

And when I look at the last year, the explosion of neoclouds,

the pivots of all the Bitcoin miners and crypto miners to become neoclouds, I do end up thinking...

Maybe this place has become a little too crowded. I see a lot of small cap stocks

and I think, yeah, maybe we are due some consolidation. There are way too many

players in the game. So I do think that we will see some of these neoclouds go bust.

I do think that some of their contracts will need to be given up.

But if I had to guess, they'll just get sucked up by bigger hyperscalers like

Amazon, like Google, like Microsoft, who have the credit score,

the capital cash accounts, and the financing and reputation to be able to do so.

And the reason why I'm confident of that is because, as the Anthropic S1 and

many other indicators show, the demand for AI is still at an all-time high.

You look at the average price of a GPU that was debuted 10 years ago,

and it's selling for 2.5x the price than it did back then, even though there

are much better versions of GPUs out there.

You look at NVIDIA selling their brand new GPUs, the Vero Rubin,

and it's completely sold out to one or two particular people,

Mark Zuckerberg and Elon Musk.

And there are a ton of other companies out there that want the same GPU.

So we are very limited and constrained, but the capital itself is not abundant.

Now, on the point of hyperscalers, so these are companies like Amazon,

Google, Microsoft, who have very huge cloud service provider units,

cash-rich balance sheets, and are buying up as many GPUs as they can to stand up data centers.

These hyperscalers have a different type of problem.

They're quite bureaucratic and they're slow moving, which is the point that

Chamath makes. He says that they can't make decisions quick enough in order

to help build out these GPUs, except for one provider. Guess who that provider is?

SpaceX, of course, which Chamath is invested in. So you can start to see the

kind of cohesion that these two are starting to have and the impact that they're

having on the market and where they might be actually talking up their book.

Because of course, SpaceX has been one of the quickest companies to scale up GPUs and data centers.

Elon Musk has famously spun up Colossus 1, 2, and 3 and are bringing online

200,000 to 300,000 GPUs, $13.1 billion worth of compute every single month.

This is currently unmatched by any other company in the world,

so much so that Anthropic is

buying compute directly from SpaceX AI to the tune of around $3.1 billion,

per month, committed over the next couple of years until, I think, 2032.

And Elon Musk is charging a premium for this. He's the only company and only

man that is able to pull this off. And you might be asking, well,

why is Elon the only person to be able to pull this off?

Well, it's because the constraint right now is in the physical...

Challenges that are required to build a data center. Let me try and put this into context for you.

To build a normal data center, so forget about the GPUs, just normal data centers

as they existed pre-chat GPT.

That took a long time, a lot of regulatory burden, a lot of legal red tape.

Now you add in GPUs, incredibly expensive, but also so, so complex to set up.

You need to train technicians from scratch to now try and teach them a completely

other different architecture, a different cooling system, a different type of

transformer, power lines that are able to scale at an industrial level.

You need to retrain all of these people and then get them to work.

But then you're faced by all the legal burden, the red tape.

Data centers want to be switched on tomorrow. They want to be set up in a blink of an eye.

But obviously, that isn't how the world currently works. And even miraculously,

if we get to that point, there is not enough electricity, power or gridline

infrastructure to support this thing.

So what ends up happening is it slows the entire movement of setting up data

centers down, which means that the chips are ready before the electricity and

power is available to power them on. So what do you end up with?

GPUs collecting dust, burning lots of money, and the whole slowdown of the AI market right now.

And so you could argue that the drawdown in the market was because too many

investors were excited or anticipated a much quicker build-out.

And to be honest, if you listen to the news, you'd be led to believe that exact

hypothesis because OpenAI would Stargate, Anthropic with all their data center

efforts, and SpaceX, Google, and all the likes implied that their data centers

would be set up like that.

And in fact, that's what they were promised. But what we're actually seeing

materializing is a slowdown of effort, and Chamath and Elon are simply calling that out.

All right, so is Elon right or wrong, or where is he right, and where is he

wrong? Let's get into it on today's episode brought to you by Qualcomm.

So let's start off with where I think he's right, the debt window,

which basically states that there's not enough money out there to

give attractive enough rates of lending to these neoclads to be able to pay

off all their GPU and CapEx expenses so that they can fulfill the contracts

that they sign with Microsoft Meta and all the other likes.

I think there's some truth here simply because the interest rates for lending

or borrowing this money has skyrocketed over the last two months.

CallWeave is a prime example where it was sub 10% two months ago,

and now it's at 16%. And the next two months, it's probably going to increase even more.

If you are a neocloud, which had less bargaining power because you're a smaller

company, you don't have a reputation versus some of the bigger hyperscalers,

you're probably borrowing this money at very poor or bad, risky rates.

Now, of course, you can supplement this by charging more money on the back end,

which is what a lot of these neoclouds do.

But at the end of the day, if the rates become higher than what you're actually

charging your client, you end up losing money and you end up being in a worse deal.

Which leads me to the second point that I think Elon's right about,

which is there will be stranded compute from a lot of these different neoclouds.

I don't think it'll be all of them, but it'll certainly be some of them.

And I think two things are going to happen here.

Companies like SpaceX or other hyperscalers are going to suck up the compute

from the smaller fishes in this ocean, or some of the bigger neoclouts are going to merge.

It wouldn't surprise me if I saw a Nebius and CoreWeave merger, for example.

Now, I have to add on that Elon Musk, when he was quizzed about this,

said SpaceX has no interest in acquiring compute.

Why would that make sense? And I found that pretty hilarious because his long-term

vision, I guess, is to launch these GPUs out into space and harness the energy

of the sun at the lowest cost possible, which begs the question

for the 40 billion dollars that you just raised Elon why on earth aren't you

spending that just on focusing on that mission and getting the GPUs out into

space now I'm sure the answer that he would give you is,

we need to make enough money in the short term by selling compute on earth at

a higher premium to the likes of Anthropic and OpenAI so that we can fund the

expensive CapEx build out

of AI in space so that's the balance there now where I think he's wrong and

maybe talking his own book is obviously because he is officially a NeoCloud

competitor anyone who says SpaceX is primarily a space company

hasn't read the news recently because most of their money, I think it's something

along the lines of 40 to 70% of revenue that they generate.

Is now coming from their AI business, their last quarterly earnings.

I think it was about $13.7 billion or $14 billion around there.

And the point being is this is now more than Starlink, which was their major

revenue earner. So it's obvious that Elon wants to double down on this to keep the company alive.

The second thing is he just raised $40 billion.

Now, of course, you don't want your competitors to then go out and do the same

thing or to get the idea to go out and do the same thing. So he's trying to

shut that down immediately.

And the third thing is his accomplice, Chamath, is an investor in SpaceX.

And listen, I love both of these guys. I love their takes. But Chamath is definitely

talking his book when it comes to power, energy, and land.

That being said, I think land power shell is the biggest bottleneck that AI

faces. And to be honest, maybe I should just make an episode explaining my thoughts

here because I think it's important.

But the idea here is this whole AI CapEx buildout is going to slow down because

we don't have enough physical atoms to move to set up these data centers.

We are constrained by regulations, power, and just not having enough energy

to deliver to the GPUs at the right time. The chips are coming first,

the energy is coming later. We are at an undeniable delay.

And that's not necessarily a bad thing because it stops the bubble from inflating.

But people just need to be careful about how much money they borrow and what

interest rates they do so.

And finally, to maybe end on a positive note, I put out an episode yesterday

talking about the Anthropic S1. And one of the main things that I called out

is I was surprised at how lean the revenue is that they're making.

One, that they're making so much. But two, the...

Average that they're making per dollar spend on compute has actually turned

positive. For every dollar of compute that they spend or invest,

they make around $2.08. And that's the first flip that we've seen a step towards

them becoming profitable.

If this is the case for the likes of OpenAI and other AI companies out there

that are spending so much money on this compute that Elon Musk and all these

neoclads are selling, that might actually end up being a bull case, optimistically.

That might reverse this entire trend and actually justify a lot of the spend that we'll see.

At the end of the day, I don't know, but I hope this is a balanced enough take

to help you guys understand what's good and what's bad happening in the markets right now.

And it's important to point out that it's not just the Western market.

The Chinese market, as of this week, is down 40% from its June highs. Catastrophic.

Other parts of Asia, the Indonesian stock index down terribly.

Now, you might be thinking, well, our markets aren't relevant to them.

We are, because a lot of their markets are propped up by the AI bubble,

by the valuations that we're seeing with the Anthropic IPO and Open Air's rumored IPO.

So it's all part of the same cohesive thing.

And AI is the biggest driving factor right now, which is why watching three

individuals tweet out and tank the market is an interesting thing to see and

I guess talk about. So I hope you enjoyed this episode.

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to today's episode brought to you by Qualcomm.