rustastra

Same with symbolic systems!

aiui a natural language question e.g. "What is the refund policy?" gets matched against formalized contracts, and the relevant bit of the contract gets translated into natural language deterministically. At least this is the way I'd do it, but not sure how it actually works

I couldn't agree more with this take: > Our demand for stimulating content is being overtaken by supply. Analogously, with AI, we might be in a world where scientific progress is accelerated beyond our wildest dreams, where we have more answers than questions, and where we cannot even process the set of answers available to us.

Curious to learn more about prompt engineering takeaways here. Was feeding more context (or chapters of textbooks, bits of papers, documentation) helpful? It does seem like layering information and being very precise helps a lot. Eerily like with interns

As a user, am I expected to write the labeling algorithms myself or do you offer some in-built ones?

Could feature extraction be helpful here?

I am very curious to know which pre-trained models work better for this task and whether it's possible at all to do without a neural net...