Viewing profile — benl_c

They often can run code in sandboxes, and generally are good at instruction following, so maybe they can run variants of doom pretty reliably sometime soon.

If a document suggests a particular benign interpretation then LLMs might do well to adopt it. We've explored the idea of helpful embedded prompts "prompt medicine" with explicit s…

Hi HN, I’m Ben from CSIRO, Australia’s national science agency. We’ve been exploring how to make data and documents "think" when you use them with LLMs. We call it Self-Thinking Da…

Thanks, structured output makes a lot more sense. The pydantic approach at the link looks straightforward.

I have not done that but I like that strategy not just for this use case but as a general idea for replacing exclusion with finer grained categorisation. One thing I did do is use …

The backend is still a mess of code, so no. It's not too hard to do though. The prompt I used extract location is "The text provided are enviornmental science papers. They often (b…

This is our Atlas of Water Science. It's a globe mapping water science that colleagues have done over the past few years. Approx 300 papers got analyzed. The pipeline sends open ac…