[louiereederson]

At some point AI may deliver the level of net economic benefit you reference, but it's not entirely clear that we're there yet.

Right now much of the direct monetization occurs via OpenAI and Anthropic, who together have around $30B in annualized revenue. They are burning cash like crazy, though admittedly have potentially sustainable unit economics (gross margins around 40-60% before revenue share).

However, they need to spend a huge chunk of revenue on training. OpenAI spent something like $9b on training against around $13-14b in rev in 2025 (different from annualized rev) according to The Information. Anthropic's mix is supposed to be similar. Also implies a lot (maybe majority) of their compute spend is training.

If scaling laws falter, what happens to training spending? What happens to competitive degree of differentiation given Chinese open source models are a few months behind frontier? Then what happens to margins? It is very fragile.

[mg]

The earnings do not need to come via direct monetization.

Google search revenue for example was over $200B in 2025. This revenue will be tightly coupled to the quality of their AI models in the future.

[louiereederson]

That is fair but doesn't do much to push back against the risk to the independent model vendors, particularly in consumer. This has represented a huge portion of the AI capex so far. OAI alone represented 2GW of compute in 2025. The point is they are in a fragile position, and so are the economics of AI DC spending in aggregate.

With respect to Google, I'd also wonder about the economics of AI search vs traditional.

[goalieca]

Googles search revenue comes from ads which depend somewhat on the quality and speed of the search result. Yeah, a better LLM could do it but a better pagerank with NLP that actually works again could do it.