Have a bunch of Makerile commands (pbcopy-api, pbcopy-ui, pbcopy-curr) that use some mishmash of git ls-files, grep, xargs tail -n +1 piped into pbcopy.
“ Finding effective documentation, information, and training is likely to get harder, especially in specialised topics where LLMs are even less effective than normal.”
Groq will soon support function calling. At that point, you would want to describe your data specification and use function calling to do extraction. Tools such as Pydantic and Instructor are good starting points.
Currently, LLM models are not state of the art at Named Entity Recognition. They are slower, more expensive and less accurate than a fine tuned BERT model.
However, they are way easier to get started with using in context learning. Soon, they will be cheaper and probably faster enough too that training your own model will be a waste of time for 95% of use cases (probably higher because it will unlock use cases that wouldn’t break even with the old NLP approaches from a value perspective).
This is why I am tracking LLM structured outputs here:
One feature I haven’t seen people write about is the ref2vec capability. I find this to be an interesting way to get some knowledge graph-like capabilities out of Weaviate.
Posting here to see if someone sees it by happenstance and writes an awesome article about it someday so I can read it.
I have a ChatGPT session where I have asked it to do a hybrid search using filtering, pg fts and vector search. Looks reasonable just need to test it and write it up somewhere.
I hope someone implements BM25 and combines it with Pgvector to bring hybrid search to Postgres. I feel like that is the jsonb of the next couple of years.
If Google Docs was the only way most people wrote text then I think your analogy would indeed be apt. In this case, nearly all people using Large Language Models are doing so through a web page (ChatGPT) or an API.
That's the inspiration behind the name, open for something better. Considered "Edge" as well, but was concerned that would seem IoT/mobile specific.