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by Traster
59 days ago
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People can correct me if I'm wrong, but I think the core logic behind OpenAI's valuation was essentially that AI would work like search. Google had the best search engine, it became a centre of gravity that sucked everything in and suddenly network effects meant it was the centre of the universe. There seem to be 2 big problems with that though. The first is that for search, queries are both demand for the product and a way of making the product better. The second, is that Google was genuinely the best product for a very long time. Maybe point (1) was unclear at some point, but I think it's mostly clear today that's not happening. Training the model is modestly distinct from inference. Point (2) is really funny - because sure, at some point OpenAI was the best, and then Sam Altman blew the place up and spawned a whole host of competitors who could replicate and eventually surpass OpenAI's state of the art. It now looks like AI is a death march. You must spend billions of dollars to have the best model or you won't be able to sell inference. But even if you do, a whole host of better funded competitors are going to beat you within months so your inference charges better pay off extremely quickly. When the gap between models starts to drop, distribution becomes king and OpenAI can't compete in that field either. Google can do that. Meta can do that. MSFT probably can do that. Amazon can do that. OpenAI cannot. They do not have the cash to do it. |
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It's also important to note the valuation is not just based off of its possible concrete economic implications in these areas but also future "unknown" possibility ( I.E. whatever "agi" means to investors ). Thats not to say I believe it's possible to achieve this but rather a huge part of Sam Altman's job is increasing valuation through unfounded claims of AGI's possibility and possible impact.