On 12/24/2024 9:06 PM, PGC wrote:
You see what I'm getting at. It’s true that from a purely
outcome-based perspective—either a problem is solved, or it isn’t—it
can seem irrelevant whether an AI is “really” reasoning or simply
following patterns. This I'll gladly concede to John's argument. If
Einstein’s “real reasoning” and an AI’s “simulated reasoning” both
yield a correct solution, the difference might appear purely
philosophical. However, when we look at how that solution is
derived—whether there’s a coherent, reusable framework or just a
brute-force pattern assembly within a large but narrowly defined
training distribution—we begin to see distinctions that matter.
I think that LLM thinking is not like reasoning. It reminds me of my
grandfather who was a cattleman in Texas. I used to go to auction with
him where he would buy calves to raise and where he would auction off
one's he had raised. He could do calculations of what to pay, gain and
loss, expected prices, cost of feed all in his head almost instantly.
But he couldn't explain how he did it. He could do it pencil and paper
and explain that; but not how he did it in his head. So although the
arithmetic would be of the same kind he couldn't figure insurance rates
and payouts, or medical expenses, or home construction costs in his
head. The difference with LLM's is they have absorbed so many examples
on every subject, as my grandfather had of auctioning cattle, that the
LLM's don't have reasoning, they have finely developed intuition, and
they have it about every subject. Humans don't have the capacity to
develop that level of intuition about more that one or two subjects;
beyond that they have to rely on slow, formal reasoning.
Brent
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