I agree that humans must verify LLM-produced facts, but strongly disagree with these kinds of "stochastic parrot therefore dumb" arguments.

Yes, an LLM is a "stochastic parrot". No, that doesn't imply that it is dumb. Enough to look at how Terence Tao asks ChatGPT to help him understand a solution that nobody had ever discussed before [1], or how a random guy asks ChatGPT in a handful of words to disprove a 30-year-old conjecture, with zero technical input [2].

If your parrot in a birdcage with internet access can finish the sentence, "The counterexample to the Dinitz–Garg–Goemans conjecture is...", then it's a pretty smart parrot, by all reasonable definitions of "smart". Just because someone bottled up the formula into matrix multiplications and added some random sampling to the outcome, that doesn't take away from the fact that the parrot said provably correct statements that the biggest experts in the field couldn't imagine.

And no, I'm not implying that the LLMs are correct all the time, or that their intelligence and reasoning works in any way like ours.

[1]: https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed... [2]: https://chatgpt.com/share/6a60b2eb-0b64-83ee-9c76-7931ca1de0...

Similarly to how no amount of efficiency gains would make Microsoft produce quality software, because they optimize for other metrics.

At least the fact that frontier models are not optimized primarily on formal math reasoning is in itself is good for not putting mathematicians out of their jobs, isn't it?

How do these results (and the future painted by them) affect your profession; do you expect a similar route as in software, where junior developers are unemployable, LLM-assisted development is the norm, and that great developers stand out partly through better communication with their managers?

https://www.reddit.com/r/hermannhesse/comments/1uvcfnj/read_...

Steve Jobs didn't mean "writing good code" as "execution", he meant "making things that align with how people want to use the product". Frontier LLMs are not solving Steve Jobs-level execution (even in the near future) because what that would mean understanding human nature – something that Steve Jobs or Henry Ford were much better than most in the industry today, so at best we're going to see LLMs making things that are as good as the majority of products. Because AI does not see whether something is perfect-according-to-Steve-Jobs or merely good-code-according-to-engineering-practices.

I really don't see the advantages of getting a newer computer for the same price with worse specs, unless it's a gift and social customs only allow a new one.

[1]: https://www.rebuy.de/i,11380014/apple/apple-macbook-air-13-3...

Unlike knitting, I love its usefulness. There are so only many use cases for knitwear, but furniture, man, everyone needs furniture. And being in a home that I built by my two hands is infinite joy.

The three aspects where it falls short to knitting: - It can't be done mindlessly. It would be unsafe and you'd make costly mistakes that you can't undo by pulling on the yarn. - It's more expensive. The materials are a bit more pricy (compared to hours spent on working them), but the machines certainly are. - You are confined to space and time. Whether it's your garage or wood shop where you have machines and can make noise and dust, or it's your living room where you exclusively use hand tools – you surely can't do it in your car while waiting for the kids, or at the university, or on the public transport. Whittling small objects is the one exception.

But yes, woodworking is awesome.