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507 points martinald | 1 comments | | HN request time: 0s | source
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simonw ◴[] No.45054022[source]
https://www.axios.com/2025/08/15/sam-altman-gpt5-launch-chat... quotes Sam Altman saying:

> Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company.

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dcre ◴[] No.45054061[source]
ICYMI, Amodei said the same in much greater detail:

"If you consider each model to be a company, the model that was trained in 2023 was profitable. You paid $100 million, and then it made $200 million of revenue. There's some cost to inference with the model, but let's just assume, in this cartoonish cartoon example, that even if you add those two up, you're kind of in a good state. So, if every model was a company, the model, in this example, is actually profitable.

What's going on is that at the same time as you're reaping the benefits from one company, you're founding another company that's much more expensive and requires much more upfront R&D investment. And so the way that it's going to shake out is this will keep going up until the numbers go very large and the models can't get larger, and then it'll be a large, very profitable business, or, at some point, the models will stop getting better, right? The march to AGI will be halted for some reason, and then perhaps it'll be some overhang. So, there'll be a one-time, 'Oh man, we spent a lot of money and we didn't get anything for it.' And then the business returns to whatever scale it was at."

https://cheekypint.substack.com/p/a-cheeky-pint-with-anthrop...

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LZ_Khan ◴[] No.45054819[source]
Also Amodei has an assumption that a 100m model will make 200m of revenue but a 1B model will make 2B of revenue. Does that really hold up? There's no phenomenon that prevents them from only making 200m of revenue off a $1B model.
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1. colinsane ◴[] No.45055225[source]
> So, there'll be a one-time, 'Oh man, we spent a lot of money and we didn't get anything for it.'