Have you actually used LLMs for non trivial tasks? They are still incredibly bad when it comes to actually hard engineering work and they still lie all the time, it's just gotten harder to notice, especially if you're just letting it run all night and generate reams of crap.
Most people are optimizing for terrible benchmarks and then don't really understand what the model did anyone and just assume it did something good. It's the blind leading the blind basically, and a lot of people with an AI-psychosis or delusion.
I think the OP's comment is entirely fair. Karpathy and others come across to me as people putting a hose into itself: they work with LLMs to produce output that is related to LLMs.
I might reframe the comment as: are you actually using LLMs for sustained, difficult work in a domain that has nothing to do with LLMs?
It feels like a lot of LLM-oriented work is fake. It is compounding "stuff," both inputs and outputs, and so the increased amount of stuff makes it feel like we're living in a higher plane of information abundance, but in reality we're increasing entropy.
Tech has always had an information bias, and LLMs are the perfect vehicle to create a lot of superfluous information.
In my limited experience, using LLMs to code up things unrelated to LLMs (robotics for instance) is significantly less productive than using LLMs to code up things related to LLMs. It works, just not very well and requires a lot more leg work on the user end than in other areas.
To be fair Karpathy isn't known for using LLMs—not that I would assume or question whether he's used them 'for non-trivial tasks', but it's not like making the same comment in reply to Steve Yegge or someone. (However trivial we may think Gastown/Wasteland is in the other sense!)
That is not the case at all, considering that he himself started using and tweeting about llms for coding fairly recently. He's probably less experienced in that area than most people who started using claude cli last year.
He is a researcher who understands neural networks and their architectures exceptionally well. That is all.
That whole thread is just amazing, if you back up a couple of levels from ground zero. Great perspectives from a lot of thoughtful posters.
E.g., you can see a post from a user named dhouston, who mentioned that he was thinking about starting an online file sync/backup service of some sort.
Haha awesome. I guess they were going through YC right then, I still remember their launch video from around then and thinking it was one of the best ads I’d ever seen.
Most people are optimizing for terrible benchmarks and then don't really understand what the model did anyone and just assume it did something good. It's the blind leading the blind basically, and a lot of people with an AI-psychosis or delusion.