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Hard for me to reconcile the idea that they don't have enough compute with the idea that they are also losing money to subsidies.
by mattas 6mo ago
Hard for me to reconcile the idea that they don't have enough compute with the idea that they are also losing money to subsidies.
- Glemllksdf 6mo agoThey are loosing money because the model training costs billions.
- ACCount37 6mo agoModel inference compute over model lifetime is ~10x of model training compute now for major providers. Expected to climb as demand for AI inference rises.
- howdareme9 6mo agoThey are constantly training and getting rid of older models, they are losing money
- ACCount37 6mo agoWhich part of "over model lifetime" did you not understand?
- adgjlsfhk1 6mo agoThat's not a sufficient condition for profitability if both inference and scaling costs continue to increase over time.
- Glemllksdf 6mo agoFor sure and growth also costs money for buying DCs etc.
- anthonypasq 6mo agothey clearly arent losing money, i dont understand why people think this is true
- smt88 6mo agoPeople think it's true because it is true, and OpenAI has told us themselves. They (very optimistically) say they'll be profitable in 2030.
- Capricorn2481 6mo agoThey're saying Anthropic doesn't have enough compute, not OpenAI. They said OpenAI specifically invested early in compute at a loss.
- repparw 6mo ago- Not enough compute for the requests they have - Selling those requests at less money than it cost to run the compute for those requests (because if you raise price clients go to openai) The statements are not contradicting each other? They keep subsidizing to try to grow customer base, but they can't serve the customer base they have, they're expecting customer base grows faster than it drops from people bothered with rate limits (it probably will, average user won't hit rate limits enough to change) Probably expecting a breakthrough in efficiency for compute, or getting enough cash flow (IPO?) to get more compute before it all comes crashing down