> This echoes a lot of the rhetoric around "but how will facebook/twitter/etc make money?" back in the mid 2000s.

The difference is that Facebook costs virtually nothing to run, at least on a per-user basis. (Sure, if you have a billion users, all of those individual rounding errors still add up somewhat.)

By contrast, if you're spending lots of money per user... well look at what happened to MoviePass!

The counterexample here might be Youtube; when it launched, streaming video was really expensive! It still is expensive too, but clearly Google has figured out the economics.

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jsnell 15 hours ago | parent [-]

You're either overestimating the cost of inference or underestimating the cost of running a service like Facebook at that scale. Meta's cost of revenue (i.e. just running the service, not R&D, not marketing, not admin, none of that) was about $30B/year in 2024. In the leaked OpenAI financials from last year, their 2024 inference costs were 1/10th of that.

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matthewdgreen 13 hours ago | parent [-]

But their research costs are extremely high, and without a network effect that revenue is only safe until a better competitor emerges.

	▲	jsnell 8 hours ago \| parent [-]
		You're moving the goalposts, given the original complaint was not about research costs but about the marginal cost of serving additional users... I guess you'd be surprised to find out that Meta's R&D costs are an order of magnitude higher than OpenAI's training + research costs? ($45B in 2024, vs. about $5B for OpenAI according to the leaked financials.)