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Comment by sk11001 | Hacker News Reader

This isn't an argument about the capabilities of LLMs, it's an argument about whether we use the term AI - and that ship sailed a long long time ago.

If your point is that LLMs won't lead to some kind of extreme AI capability that you're imagining or you've read about in science fiction books, you can just say that instead. But LLMs are already as AI as can be.

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I am doomed to repeat myself, but I mentioned it countless times in the past and I also mentioned it here: Try asking it to derive something given a set of definitions and axioms from a non-widespread domain (e.g., Clifford algebra, perspective geometry). Then you might see that it parrots what the majority of its dataset says. It is essentially similar to Google, but you don't mix and match the search results, the LLM or the "AI" does.

I don't see how that's relevant.

The non-popular or non-widespread aspect of a "prompt" (e.g., "derive the geometric product given axioms/definitions ...") should be understood as a data point that it might lack reasoning skills. As it seemingly parrots what most of its dataset "says". For more details, check my other past comments. Calling such LLMs "AI" seems to be sensationalism at work.

This is a problem of your expectations. Things don't need to be perfect to qualify as AI.

Hmm... wouldn't you agree that a formal (relatively accurate language) such as math is easier to get right than an non-accurate human language?

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