▲ | 93po 4 days ago | ||||||||||||||||
In 2024 they had a $5 billion loss. About $3b of that was training. $1.5b was employees. I'm sure there's at least another $0.5b of costs associated to building out rather than just serving inference. In reality it's probably several times that. So if you cut employees to just maintaining what they have, fire all researchers etc, stop expansion, and stop training, you'd be profitable. Which is dumb and they wouldn't do that, but my point isn't that it's realistic, but rather that they could sell what they have at a profit if they wanted to. | |||||||||||||||||
▲ | hansmayer 4 days ago | parent [-] | ||||||||||||||||
So they could be profitable, but the conditions to achieve the profitability are dumb and unrealistic. Your own words. Somehow you claim to have still made your point, because a company firing all its employees and stopping all product development could be profitable, right? Because thats what companies do routinely, they just maximise profits by firing everyone once the product is mature enough and can practically take care of itself. I wonder why all the e-commerce companies just dont apply this one simple trick? Is that the argument that you are making? Now for the calculations - are you sure the losses are only 5B? Well, if we just account for the Microsoft donated Azure credits, they run a lot of their workloads on, its probably a lot, lot more than that. Unaccounted for in the OpenAI books perhaps, but still a huge material investment, that does not make any returns to anyone, hence a (by definition) loss. | |||||||||||||||||
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