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> But one cannot deny RAG is a lot more accessible to teams which are likely developers / AI engineers compared to ML engineers/researchers.

It looks like major vendors provide simple API for fine-tuning, so you don't need ML engineers/researchers: https://platform.openai.com/docs/guides/fine-tuning

Setting RAG infra is likely more complicated than that.

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You are certainly right, managed platforms make finetuning much easier. But managed/closed model finetuning is pretty limited and in fact should be named “distribution modeling” or something.

Results with this method are significantly more limited compared to all the power open-weight finetuning gives you (and the skillset needed in return).

And in either case don’t forget alignment and evals.

> Results with this method are significantly more limited compared to all the power open-weight finetuning gives you (and the skillset needed in return).

I am not sure I understand why you are so certain that finetuned top market models, built by top researchers will be significantly worse than whatever open source model you pick.

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