I always assumed that with inference being so cheap, my subscription fees were paying for training costs, not inference.

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beAbU 2 hours ago | parent | next [-]

Is inference really that cheap? Why can't I do it at home with a reasonable amount of money?

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simonw 6 hours ago | parent | prev | next [-]

Anthropic and OpenAI are both well documented as losing billions of dollars a year because their revenue doesn't cover their R&D and training costs, but that doesn't mean their revenue doesn't cover their inference costs.

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overgard 6 hours ago | parent | next [-]

Does it matter if they can't ever stop training though? Like, this argument usually seems to imply that training is a one-off, not an ongoing process. I could save a lot of money if I stopped eating, but it'd be a short lived experiment.

I'll be convinced they're actually making money when they stop asking for $30 billion funding rounds. None of that money is free! Whoever is giving them that money wants a return on their investment, somehow.

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vidarh 3 hours ago | parent | next [-]

At some point the players will need to reach profitability. Even if they're subsidising it with other revenue - they'll only be willing to do that as long as it drives rising inference revenue.

Once that happens, whomever is left standing can dial back the training investment to whatever their share of inference can bear.

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ben_w 3 hours ago | parent [-]

> Once that happens, whomever is left standing can dial back the training investment to whatever their share of inference can bear.

Or, if there's two people left standing, they may compete with each other on price rather than performance and each end up with cloud compute's margins.

	▲	vidarh an hour ago \| parent [-]
		Sure, but they will still need to dial it back to a point where they can fund it out of inference at some point. The point is that the fact they can't do that now is irrelevant - it's a game of chicken at the moment, and that might kill some of them, but the game won't last forever.

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simonw 5 hours ago | parent | prev | next [-]

It matters because as long as they are selling inference for less than it costs to serve they have a potential path to profitability.

Training costs are fixed at whatever billions of dollars per year.

If inference is profitable they might conceivably make a profit if they can build a model that's good enough to sign up vast numbers of paying customers.

If they lose even more money on each new customer they don't have any path to profitability at all.

	▲	citrin_ru an hour ago \| parent [-]
		> If they lose even more money on each new customer they don't have any path to profitability at all. In theory they can increase prices once the customers will be hocked up. That's how many startups works.

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krainboltgreene 5 hours ago | parent | prev [-]

There's an argument to be made that a "return on investment by way of eliminating all workers" is a reasonable result for the capitalists.

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generic92034 3 hours ago | parent [-]

At least until they are running out of customers. And/or societies with mass-unemployment destabilize to a degree that is not conducive for capitalists' operations.

	▲	ben_w 3 hours ago \| parent [-]
		That's a problem above most CEOs' pay grade.

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vrighter 3 hours ago | parent | prev [-]

Models are fixed. They do not learn post training.

Which means that training needs to be ongoing. So the revenue covers the inference? So what? All that means is that it doesn't cover your costs and you're operating at a loss. Because it doesn't cover the training that you can't stop doing either.

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smashed 7 hours ago | parent | prev [-]

Doubtful