AI Bubble 🫧

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Bryan McMahon wrote about a potential AI bubble in The American Prospect.

In 2024, [Apple, Nvidia, Tesla, Alphabet, Meta, Amazon, and Microsoft] were responsible for the lion’s share of the growth of the S&P 500, with the returns of the other 493 companies flat.

For the tech industry, DeepSeek is a threat to its incredible bull run because it proved three things.

First, frontier AI models could be trained much more cheaply and efficiently than the current Silicon Valley approach of building massive models requiring hundreds of thousands of GPUs to train. From a capital perspective, the U.S. strategy is wasteful, relying on at least ten times the investment to make similar model progress.

Second, DeepSeek showed you could train a state-of-the-art model without the latest GPUs, calling into question the current demand for the latest GPUs that is so hot customers have been facing delays of six months to a year to get their hands on them.

Finally, the high valuations of leading AI startups depend on a technical lead in their models to charge prices anywhere near what they need to recoup their computing costs, but that technical lead, enabled by a combination of closed-source models, billions in capital expenditure, and export controls blocking Chinese companies like DeepSeek from accessing the latest GPUs, is gone. Should demand for GPUs fall or even not hit the exponential increases the billions invested are betting on, the bubble will pop.

Between VCs, Big Tech, and power utilities, the bill for generative AI comes out to close to $2 trillion in spending over the next five years alone. […] While AI-fueled coding could definitely boost productivity, it’s hard to see how it could become a multitrillion-dollar industry.

keywords: OpenAI, artificial intelligence, machine learning, artificial general intelligence, AGI

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Thanks for sharing, @mike!

I’ve been reading the (sometimes) bi-weekly newsletters at wheresyoured.at for some time. It’s a very interesting dig into the financials of the companies riding the generative AI wave.

I don’t agree with everything Ed says, but there is definitely something very wrong here. I don’t doubt the market is going to crash when the AI bubble bursts. I doubt LLMs will disappear for good.

There’s a lot of good stuff, but this one really stuck with me:

The Stargate Project" — a relatively new partnership of “up to $500 billion” to build massive new data centers for AI, led by SoftBank, and OpenAI, with investment from Oracle and MGX, a $100 billion investment fund backed by the United Arab Emirates. OpenAI has committed $19 billion to the Stargate project — money it doesn’t have, meaning that part of $25 billion to $40 billion funding round that OpenAI is currently raising will be committed to funding these data centers (unless, as I’ll get to later, OpenAI raises more debt).

Leading the round is SoftBank, which is also committing $19 billion, as well as creating a joint venture called SB OpenAI Japan to offer OpenAI’s services to the Japanese market, as well as “spending $3 billion annually to use OpenAI’s technology across its group businesses” according to the Wall Street Journal.

SoftBank also does not appear to have the money. According to The Information, SoftBank CEO Masayoshi Son is planning to borrow $16 billion to invest in AI, and may borrow another $8 billion next year.

On top of that, OpenAI anticipates it will burn as much as $40 billion a year by 2028, and projects to only turn a profit “by the end of the decade after the buildout of Stargate,” which, I add, is almost entirely dependent on SoftBank, which has to take on debt to fund both OpenAI and the project required to (allegedly, theoretically) make OpenAI profitable.

This is bonkers.

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Paraphrasing Cory Doctorow:

Freedom can mean the freedom for everyone to live healthy, productive, and meaningful lives; or it can mean the freedom for one powerful person to make decisions that harm everyone else.

There always has been more demand for tech workers than supply. If a programmer does not like their job then they can quit and find a better one the same day.

Meaningful work and the power to push back against bad leadership have been significant reasons why coders stay at their current jobs.

So, the reason why executives are excited and willing to spend trillions of dollars is so they can fire those skilled workers and replace them with poorly educated workers that supervise machine learning models: powerless workers who can be fired and replaced at will.

Then the executives can make decisions without anything resembling democracy.

Now, in my own voice, if that was your point of view and if your ego was that big then there is no amount of money you can spend that is too much because: b) this is what you always wanted, and a) you don’t want to be on the wrong side of that chasm of inequality this opens up.

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hmmm… seems like that open-source model might make some sense after all - who knew?

frankly, i’d be happy to see the U.S. model collapse, again, since it wouldn’t be the first time “AI” ended up in the dumpster after the hype train ran out of rail

meanwhile, the energy requirements cannot be met, and though i haven’t been keeping up with AI rollout, the solution, far as i know, is to build a bunch of nuclear reactors … another bright idea from the minds of bi-pedal primates, but the idiocy of that proposal is another matter (and i’m not referring to the dangers, but rather the alternatives which aren’t wind, hydro or solar)

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Fear is in the driving seat.

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A must read:

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I think that book is really about automation.

I enjoyed the book Blood in the Machine, which demonstrates that automation is a general pattern where individuals at the bottom pay the costs for changes in society while power concentrates at the top.

Hao’s book just seems like a specific case of automation. And, I don’t think that is useful right now.

I think if people really cared about suffering and the environment then they would strive to learn more about the politics of capitalism and socialism. Society could then pick the low-hanging fruit without getting caught in minutiae or spectacle.

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I think you didn’t read the book, because that’s not what the book is about at all.

If you’re interested there’s a good interview with the writer here:

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What I think is important is that history is repeating itself. OpenAI fits into the broader trend of industrialization which started over two hundred years ago and never stopped. The economic, social, and environmental issues created by OpenAI and written about by Karen Hao are common both now and in the past.

During the interview, Hao says that we are at risk of losing democracy. But, inherent in that statement is the implication that we have democracy now. At the end of the interview, Hao says that scientists working at OpenAI sometimes leave the company because it is not compatible with their values. My argument is that, if we had democracy right now, you would not have to choose between work and morality. Most people care about human welfare and nature. And, a democracy would not choose to destroy itself or ignore its own majority.

I probably am misrepresenting the content of a book that I have not read.

But, I understand the concepts involved.

And, if you are unsatisfied with Empire of AI then try reading Blood in the Machine. It is much more focused on the issue I’m talking about which is the relationship between labor, capital, and automation: the motivation for and pattern of OpenAI, and a major component of capitalism generally.

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This perspective from a veteran of search, covers several aspects of techno-political empireland

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More from Battelle: “Tech hasn’t eclipsed finance. It has captured it.”

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“When will the bubble burst”

“These are the consequences of the global AI race according to economist Andy Xie” (source: Dutch TV program “VPRO Tegenlicht”).

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Xie is correct.

Monetary policy is part of the problem. The economy cannot absorb all the money available for investing.

But, I would add a few more criteria to my analysis.

For starters, there are things worth investing in: affordable housing, health care, public education, justice, climate change, fully funded government.

The problem is not monetary policy per se but too much money in the wrong hands.

The United States has a unique role in this problem. The US dollar is indispensable to world trade. And, operating with a huge trade imbalance, there are many “exports” like treasury bonds, health care, housing, and education. This adds to the capital account.

So, after 2008, we talk about monetary policy. But, the US was happily exporting non-tradable goods before the financial crisis. And, monetary policy only makes a bad situation worse. We’re delaying action and making the next economic depression bigger.

So, I would ask these questions.

  • Why do we simultaneously have trillions of dollars doing nothing useful while we have big social problems like housing and cost of living crises?
  • Could the economy absorb more investment? What would improve investment conditions?
  • What are the conditions for sustainable political change?

We have plenty to do. But, we need to prioritize human needs and the environment over finance and inequality. People need to be educated so that they can participate in democracy and the economy. Then, ordinary people will be able to fully benefit from everything the economy has to offer.

If people are interested in monetary policy, “The Power of the Fed” from Frontline is a good introduction.

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Sam Altman (OpenAI): it’s a bubble.

Is the AI bubble about to pop? Sam Altman is prepared either way. - Ars Technica