In my tests LLaMa2-13B is useable for information extraction tasks and LLaMA2-70B is almost as good as GPT-4 (for IE). These models are the real thing. We can fine-tune LLaMAs, unlike OpenAI's models. Now we can have privacy, control and lower prices. We can introduce guidance, KV caching and other tricks to improve the models. The enthusiasm around it reminds me of JavaScript framework wars of 10 years ago - tons of…
> “The enthusiasm around it reminds me of JavaScript framework wars of 10 years ago” Hmm. If LLMs turned out like JS frameworks, that would mean that in ten years people will be saying: “Maybe we don’t really need all this expensive ceremony, honestly this could be done with vanilla if/else heuristics…?”
That would be awesome, but we've tried for decades and haven't gotten there with basic if/else. I do think it's pretty plausible that if you combine some very slimmed down models with strong heuristics you could get far though. At the moment I think expense doesn't really matter -- an hour of a knowledge worker's time is worth 416,000 tokens of GPT-4, the most expensive model out there. For llama-2 it's even less time. Unless you're processing truly epic numbers of tokens, by far the most important is whether we can use these things for real.