4 ms·
I think the biggest pushback this article will get here is the date. Although all he's saying is basically, "It's a tool, not a silver bullet". But the article
by bena 3mo ago
I think the biggest pushback this article will get here is the date.
Although all he's saying is basically, "It's a tool, not a silver bullet". But the article is 3 years old and people will note that the models have been updated since then.
- simonh 3mo agoSure, but they're still LLMs and still do the same things largely the same way they did 3 years ago. There are some architectural changes, and maybe these will merit a re-assessment over time, but fundamentally it's still the same basic technological approach refined and scaled up.
- bena 3mo agoAnd I don't disagree, but the posting of the article feels more like bait of a sort. But I've noticed that if you mention anything that could be seen as slightly critical of LLMs, you'll get people out of the woodwork suggesting that the state of the art has made your criticism invalid.
- Diogenesian 3mo agoThe models have updated but the biggest change is providers leaning in to them being "stochastic parrots," aka probabilistic computing, and if p(good response) > 0.5 then running the algorithm over and over again improves accuracy. Of course it's gussied up as "mixture of agents" "reasoning traces" "agentic dispatching" but high-level it's Randomized Algorithms 101.
- deleted 3mo ago[deleted]
- Kim_Bruning 3mo agoOh, that's an interesting angle! Do you know of texts or concepts I can look up? It might improve my coding by quite a bit.
- Diogenesian 3mo agoI think this is still the classic reference (it's what I used in graduate school): https://www.cambridge.org/core/books/randomized-algorithms/6A3E5CD760B0DDBA3794A100EE2843E8 https://www.cambridge.org/core/books/randomized-algorithms/6...