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So, if I read this right, all the major AI companies are not releasing their highest performing models because it's too expensive to roll them out en masse, the

So, if I read this right, all the major AI companies are not releasing their highest performing models because it's too expensive to roll them out en masse, they are instead using it to (somehow, IANA ML expert) make their existing models cheaper to run. If I'm reading this right, they're peaking on general performance (as a function of GPUs on hamster wheels), and instead are focusing on reducing costs for their most-demanded operating modes. A testable prediction of this is then: "All major AI companies will roll out hyper-specialized models that exceed general models at the same price point" and simultaneously will boost profits. The game is to find the specializations that make the most money?

chilmers 2y ago
Well, I think the most interesting point made is that it may not make sense for AI companies to release models _at all_ as they approach AGI. Exposing models allows their capabilities to be easily copied, whereas keeping them internal lets you capture the profit from their output while protecting your IP. For example, say OpenAI trained a hyper-intelligent model specialising in designing new small molecule drugs. Why make that publicly available at all? Why not just partner with a pharmaceutical manufacturer and make money from selling the drugs? We’ve become accustomed to AI-as-a-service being the default, via chat or API, but this might just be a blip. After all OpenAI have made it clear that they only see their mission as making the “benefits” of AGI available to all, which doesn’t necessarily correspond with making AGI itself available to everyone.