OpenAI's $1.5trn valuation is insane
Dan PetersonSynopsis — AI-drafted from Dan's notes
The interview makes three moves. First, the industry’s “slow down” turn is theatre: nobody is training less and nobody is buying less data-centre capacity, so the pacing talk describes a posture rather than a decision. Second, superintelligence and recursive self-improvement are raised to pull attention away from what the labs are shipping now, which means the argument worth having is about present products and not about a future mind. Third, the valuations are the tell. A company assembled out of leased compute and a story is priced as though it owned something, and the reported $1.5trn target is what that pricing looks like at the top of its range.
The regulatory ask that comes with it is unusually specific for this genre: investigate vibe coding, block emotional-support and health LLMs, and hold executives personally accountable for cybercrime their tools enable.
Where I land
Zitron says nobody is slowing down because nobody is buying less capacity. The day before, on the same show, he said much of that buying is pre-orders sitting in warehouses. I think both can be true.
The industry is captured by Nvidia. The hype is high enough, and the near-monopoly on the demanded chips complete enough, that Nvidia can force companies to buy and hold. At the same time there is pushback on data centres, plus both physical and political friction on actually getting them built too soon. Therefore a backlog of chips accumulates.
This problem is also very hard to solve. If you under-purchase chips, your cloud architecture degrades pretty quickly; if you over-buy, you go bankrupt. I think the second is more likely to happen than the former. The companies need adoption, use-cases, revenue, all of it, to speed up. It’s also extremely convenient that the very moment open-source Chinese models start to catch up to private frontier American models, the latter strives to quash the former with regulatory capture.
On his regulation list I land in three different places. I am not sure about the vibe coding: software is especially fluid and the technologies change so quickly. Perhaps we can focus on critical infrastructure (e.g. health care, banks, utilities), but a lot of regulations cover that already.
Executive liability would be a good one. There needs to be at least some guidance on what frontier labs should at least try to anticipate when running these experiments.
Companion LLMs is the interesting one. What counts as a companion? Humans are so hard-wired for anthropomorphization that we stick googly eyes on a Roomba, give it a name and have a whole conversation about it. As such, it is a difficult thing to gate and requires more thought.
Finally, the “no assets” line. I think it makes the blast radius of the bubble bursting worse, not milder. If it was just OpenAI that folds, then other companies can pick up the pieces that get broken by the bankruptcy. However, if OpenAI cannot pay Oracle and Oracle then gets suffocated by debt, the daisy chain of circular financing explodes exponentially. That is Zitron’s main throughline.