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by simonw
403 days ago
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> Let's look at the data: 72% of enterprises are now fine-tuning models rather than just using RAG (22%) or building custom models from scratch (6%). This isn't a trend, it's because fine-tuning works when other approaches fail. Where did that data come from? My mental model is still that most companies find fine-tuning an LLM isn't worth the effort compared to promoting with better chosen examples or setting up effective RAG. Am I out of date? On reading further: it looks like this series of posts is specifically about building voice assistants that run on a mobile phone, which need TINY models. From what I understand getting tiny models to perform interesting custom tasks is a challenge that fine-tuning is well suited for. |
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They surveyed Fortune 500 types for it. The numbers above were from a survey of 70 "AI decision makers" and the question concerned "How are enterprises customizing their models?"