Absent a major breakthrough all the major providers are just going to keep leapfrogging each other in the most expensive race to the bottom of all time.
Good for tech, but a horrible business and financial picture for these companies.
They’re absolutely going to get bailed out and socialize the losses somehow. They might just get a huge government contract instead of an explicit bailout, but they’ll weasel out of this one way or another and these huge circular deals are to ensure that.
I've had that uneasy feeling for a while now. Just look at Jensen and Nvidia -- they're trying to get their hooks into every major critical sector as they're able to (Nokia last month, Synopsys just recently). When chickens come home to roost, my guess is that they'll pull out the "we're too big to fail, so bailout pls" card.
Crazy times. If only we had regulators with more spine.
Antitrust regulators must be sleeping at the wheels.
I also think the circular dealing fears in particular are overstated. Debt financing that looks like this is common in semicon, and I doubt there are any serious investors that haven’t already priced it in. If the bust is fatal for AI investment, it’ll just be bankrupt companies owing money to other bankrupt companies.
The longer a bubble grows, though, the worse it gets when it pops. According to Fed stats, we might still be postponing most of the crash that was going to happen in 2008.
If AI turns the world into a dictatorship, what gives anyone the idea they'll just agree to share that dictatorship with their shareholders? They could just ignore company law - they're dictators!
There is still significant value in AI/ML Applications from a NatSec perspective, but no one is actually seriously thinking about AGI in the near future. In a lot of cases, AI from a NatSec perspective is around labor augmentation (how do I reduce toil in analysis), pattern recognition (how do I better differentiate bird from FPV drone), or Tiny/Edge ML (how do I distill models such that I can embed them into commodity hardware to scale out production).
It's the same reason why during the Chips War zeitgeist, while the media was harping about sub-7nm, much of the funding was actually targeted towards legacy nodes (14/28nm), chip packaging (largely offshored to China in the 2010s because it was viewed as low margins/low value work), and compound semiconductors (heavily utilized in avionics).
[0] - https://www.zaobao.com.sg/news/china/story20250829-7432514
[1] - https://finance.sina.com.cn/roll/2025-09-30/doc-infsfmit7787...
You can be optimistic about the value of agentic workflows or domain specific applications of LLMs but at the same time recognize that something like AGI is horseshit techno-millenarianism. I myself have made a pretty successful career so far following this train of logic.
The point about Solow's Paradox is that the gains of certain high productivity technologies do not provide society-wide economic benefit, and in a country like China where the median household income is in the $300-400/mo range and the vast majority of citizens are not tech adjacent, it can lead to potential discontent.
The Chinese government is increasingly sensitive to these kinds of capital misallocations after the Evergrande Crisis and the ongoing domestic EV Price War between SoEs, because vast amounts of government capital is being burnt with little to show for it from an outcomes perspective (eg. a private company like BYD has completely trounced every other domestic EV competitor in China - the majority of whom are state owned and burnt billions investing in SoEs that never had a comparative advantage against BYD or an experienced automotive SoE like SAIC).
Some people certainly argue that about the computer age, and it’s not totally unsupported. But I don’t think the evidence for that interpretation (as opposed to a delayed effect) is strong enough that I’d want to automatically generalize it to a new information technology advance.
To be clear, I don’t think China’s reticence is necessarily wrongheaded. But “we will usher in an age of undisputed dominance in a decade or two instead of right now from this investment” is a weird argument, especially from a government as ostensibly long-term focused as China.
The most important priority for any government is political stability. In China's case, the local and regional government fiscal crisis is the primary concern because every yuan spent on subsidizing an industry is also a yuan taken away from social spending - which is entirely the responsibility of local governments after the Deng reforms. This is why despite China being a large economy has only just caught up to Iran and Thailand's developmental indicators in the past 2-3 years.
The meme of a "long-term focused China" is just that - a meme. Setting grand targets and incentivizing the entire party cadre to meet those targets or goals is leading to increasingly inefficient deployments of limited capital and led to two massive bubbles busting in the past 5 years (real estate and EVs). The Chinese government doesn't want a third one, and is increasingly trying to push for capital to be deployed to social services instead of promotion-targeted initiatives.
Also, read Chinese pronouncements in the actual Putonghua - the translations in English make bog standard pronouncements sound magnanimous because most people who haven't heard or read a large number of Chinese government pronouncements don't understand how they tend to be structure and written as well as the tone used.
They do.
These kinds of statements and discussions happen all the time - in Chinese. The "long-termism" trope is largely an English language one because outsiders either severely degrade or severely fawn Chinese policymaking. Additionally, because most outsiders don't speak or understand Chinese, the spectre of China is often used as a rhetorical device to help drive decisionmaking and using "long-termism" is an easy device for that. A similar thing used to be used with Japan in the 1980s and Germany in the 2000s.
And what actually is the long term value of investing tens of billions in (eg.) AGI versus a similar amount in subsidized healthcare expansion in China? Applications based usescases and domain specific usecases of AI/ML have shown the most success from an outcomes perspective for both National Security and Economic usecases.
AI/ML has a lot of value, but a large amount of the promise is unrealistic for the valuations provided in both the US and China. THe issue is in China, an AI bubble bursting risks leaving local and regional governments holding the bag like during the real estate crisis because the vast majority of capital deployed in subsidizes came from regional and local government's budgets, and takes a large amount of capital away from social service expansion.
For a lot of Chinese leadership, the biggest worry is Japanification, which itself set itself due to the three-way punch of the 1985 Endaka recession, the 1990 Asset Bubble bust, and the 1997 Asian Financial Crisis. Much of China's financial leadership and regulators started their careers managing the blowback of these crises in China during that era or were scholars on them. As such, Chinese regulators are increasingly trying to pop bubbles sooner rather than later especially after the past experiences dealing with the 2015-16 market crash and the Evergrande crisis. Irrational exuberance around AI is increasingly being viewed through that lens as well.
https://www.whitehouse.gov/presidential-actions/2025/08/demo...
Many retirement accounts/managers may already be channeling investment such that 401k accounts are broadly set up to absorb any losses… Could also just be this large piece of tin foil on my head.
I was an OpenAI fan from GPT 3 to 4, but then Claude pulled ahead. Now Gemini is great as well, especially at analyzing long documents or entire codebases. I use a combination of all three (OpenAI, Anthropic & Google) with absolutely zero loyalty.
I think the AGI true believers see it as a winner-takes-all market as soon as someone hits the magical AGI threshold, but I'm not convinced. It sounds like the nuclear lobby's claims that they would make electricity "too cheap to meter."
Investors in AI just don't realize AI is a commodity. The AI companies' lies aren't helping (we will not reach AGI in our lifetimes). The bubble will burst if investors figure this out before they successfully pivot (and they're trying damn hard to pivot).
There's a lot more than money at stake.
Long term, yes. But Wall Street does not think long term. Short or medium term, you just need to cash out to the next sucker in line before the bubble pops, and there are fortunes to be made!
This is still sorta true, but swap "LLM" for "chatbot." I mentor high school kids, and a lot of them use ChatGPT. A lot of them use AI summaries from Google Search. None of them use gemini.google.com.
It seems that Blackberry's market share of new phone sales peaked at 20% in 2009. So I'm not sure if it's coincidence, but it looks like the market actually did a pretty good job of pricing in the iphone/android risk well before it was strongly reflected in sales.
Yes, companies like Google can catch up and overtake them, but a moat is merely making it hard and expensive.
99.999.. perc of companies can't dream of competing with OpenAI.
That’s not a bubble at all is it?
I can't imagine it making sense to purposefully neglect to keep a model as up-to-date as possible!