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It’s not just math. Anecdotally, LLMs struggle the same way with software engineering where the code they write is correct (compiles and passes tests), but reas
by batshit_beaver 2mo ago
It’s not just math. Anecdotally, LLMs struggle the same way with software engineering where the code they write is correct (compiles and passes tests), but reasoning is wrong often enough to eliminate most trust in these models’ ability to explain codebases or even features they themselves produce. It’s not about the _level_ of the supposed intelligence where a model struggles to summarize things succinctly or simply enough (responding to the “pocket mathematician” comment) or can’t grasp certain concepts at all (if so, how tf is it able to apply them?). It’s that by their design LLMs have no concept of truth and no concept of causality. They guess with every single inference and it’s very hard as a user to understand which guesses are more or less certain, since, you know, confidence ratings aren’t part of these models’ design either.