Data preparation for function tooling is boring
thehyperplane.substack.com
Data preparation for function tooling is boring
1–6 of 6 posts
Re: Data preparation for function tooling is boring
#2Re: Data preparation for function tooling is boring
#3From building your own Siri, now you learn the boring dataset part that you cannot skip!
Re: Data preparation for function tooling is boring
#4Where 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 Am I out of date?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.
Re: Data preparation for function tooling is boring
#5> 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 effe…
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?"