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Message: <blockquote data-quote="Blue" data-source="post: 9768554" data-attributes="member: 20564">You made a jump there that just isn't true.  Yes, it's the tiny models that you can run at home.  But just having the ability to do so at home has prompted a lot of improvements.  For generative AI art it was home users who worked out LoRAs and their descendants, to add a specific training layer on top of a trained model without the costs of retraining the original model.  Lots of improvements because of those limitations.  Necessity is the mother of invention and all that.They've published the costs of bulk queries, and it's not "very expensive" to do a query.  Doing tens of millions of queries, especially in deep thinking mode, is a different story, but that requires tens of millions of questions asked by people.Again, I've professionally managed both owned and co-lo datacenters for global companies.  Running a single query against a trained model isn't "very expensive".If you want to sliding into a separate discussion about the economics of the companies, fine.Year ago, if you wanted to find a phone number you dialed 411.  Back when phone calls were still a big thing.  And you got charged for it.  Google did a free one (1 800 GOOG 411 if I recall) that would also connect you for free.  You just spoke what you wanted, it verified it, and then it would giove you the numebr and offer to connect you.  It was a free service.Did it make money?  Lots.  Oh, you only can see that calling a free number didn't make them anything.  What they were doing was doing voice recognition training on loads of people, different accents and dialects, and getting down proper nouns correctly.  It was an extremely economical way to do that, and that paid off nicely.So if you're only looking that Open AI doesn't make money on current queries, you need to ask yourself why are they doing it?  It's not altruism.  There's a payoff, even if it's not a direct one.Remember the old truism, "If something is free, you're the product".</blockquote>

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