[smj-edison]

This seems like a great blend of LLM and classic analysis. I've recently started thinking that LLMs (or other ML models) would be fantastic at being the interface between humans and computers. LLMs get human nuance/satire/idioms in a way that other NLP approaches have really struggled with. This piece highlights how ML is great at extracting information in context (being able to tell whether it's go the language or go the word).

LLMs aren't reliable for actual number crunching though (at least from what I've seen). Which is why I really appreciate seeing this blend!

[ramblerman]

> I've recently started thinking that LLMs would be fantastic at being the interface between humans and computers

Join the club :) I'd say that's a pretty mainstream idea right now.

Exciting nonetheless

[smj-edison]

Yeah, I guess it is pretty mainstream :) Though another view I keep hearing is that LLMs are going to replace all jobs in 5 years, which quite frankly is disconnected from reality. Even assuming that we could create a ML model that could replace a human (which I think the current paradigm is insufficient after this[0] discussion), there's still the matter of building data centers, manufacturing chips, and it would need to be cheaper than paying a human.

I personally would like AI to help humans be better humans, not try to replace humans. Instead of using AI to create less understanding with black box processes, I'd rather it help us with introspection and search (I think embeddings[1] is still a pretty killer feature that I haven't heard much noise about yet).

[0] https://news.ycombinator.com/item?id=21786547 [1] https://terminusdb.com/blog/vector-database-and-vector-embed...

[TechDebtDevin]

I would say they're very bad at inferring any sort of complicated nuance.

[javcasas]

So we win the war against the machines with sarcasm, irony and double meanings? That would be one hell of a shitty Terminator movie.