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Along the same lines, it's often useful to think of an LLM's "understanding" a question or a context. Sometimes responses from smaller models show a shallower
by loudmax 1y ago
Along the same lines, it's often useful to think of an LLM's "understanding" a question or a context. Sometimes responses from smaller models show a shallower "understanding" of the question than you'd get from a bigger model.
Obviously, we shouldn't anthropomorphize too much here, and even the most powerful LLMs don't "understand" or "reason" or "think" the way humans do. But whatever they're doing, it's at least analogous to what we do. These concepts are genuinely useful for making better use of these tools.
- simonw 1y agoYeah, that's my position as well. I hesitated on using the term "reasoning", but it's honestly a really good shortcut for describing that thing where the recent models can "think step by step" about a problem before providing their final answer.