Site creator here. I was just submitting this as a Show HN!
I'm a big fan of In Our Time. There are episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all available to listen to, so it's my starting point to learn about most topics. But it's not well organised by the BBC.
So here are the episodes sorted by library code.
Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I asked for a Dewey classification... and it worked. So a few days of work replaced by 3 cents per inference and an overnight data run.
My takeaway is that I'll be using LLMs as function call way more in the future. This isn't "generative" AI. So I'm interested in what temperature=0 LLM usage looks like (you want it to be pretty deterministic), at scale, and what a language that treats that as a first-class concept might look like.
I'm a big fan of In Our Time. There are episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all available to listen to, so it's my starting point to learn about most topics. But it's not well organised by the BBC.
So here are the episodes sorted by library code.
Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I asked for a Dewey classification... and it worked. So a few days of work replaced by 3 cents per inference and an overnight data run.
My takeaway is that I'll be using LLMs as function call way more in the future. This isn't "generative" AI. So I'm interested in what temperature=0 LLM usage looks like (you want it to be pretty deterministic), at scale, and what a language that treats that as a first-class concept might look like.