this post was submitted on 01 Apr 2025
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This also isn't an accurate characterization IMO. LLMs and ML algorithms in general can generalize to unseen problems, even if they aren't perfect at this; for instance, you'll find that LLMs can produce commands to control robot locomotion, even on different robot types.
"Reasoning" here is based on chains of thought, where they generate intermediate steps which then helps them produce more accurate results. You can fairly argue that this isn't reasoning, but it's not like it's traversing a fixed knowledge graph or something.