Comment by j-pb
4 days ago
The main difference between the systems you list and the systems that we have today is closed world reasoning on very narrow formalised tasks, vs. open world common sense reasoning on open ended tasks with vast search spaces.
Common sense is ironically the hard part of AI, not the fix-point rule application.
So any exclamation of "it was just using common sense", is missing the forrest for the trees.
That’s a lot of words just to say “but modern AIs have access to more data”. Why overcomplicate prose? To sound smarter?
Still, OP’s argument still holds even if AIs today have much more data to rely upon.
The fact that cyc, wikidata, description logics and ontologies have led us nowhere is a pretty good argument against your "simplification".
The internet is at your disposal go write a bunch of rules that make use of that data to do common sense reasoning, I dare you.
>> So any exclamation of "it was just using common sense", is missing the forrest for the trees.
I don't know why you say this, I didn't say anything about common sense.
However, you mention CYC. That's a system that is perfectly capable of common sense reasoning and very much like an LLM in many ways. And that should be no surprise: LLMs are giant Expert Systems trained on a human knowledge-base, i.e. the web. OpenAI basically managed to achieve what Doug Lenat was trying to achieve except they did it with machine learning over massive data and compute instead of painstaking manual coding, but it's the same kind of system in the end.
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