So we need to do more Good Old Fashioned AI, and get off my lawn.
He has a good point that model-less LLMs have serious trouble with problems that require a model.
But predicate calculus hasn't worked out well as that model.
Many years ago, I took John McCarthy's "Epistemological problems in artificial intelligence" class. He laid out the missionary and cannibals problem informally, then wrote it up in a predicate-calculus notation, and then applied his "circumscription logic"[1]. As he wrote it up in his formulation, I thought "and then a miracle occurs".[2] As with most story problems, it's getting the problem into the correct formalism that's hard. Turning the crank on the formalism is usually straightforward.
Much of the AI community spent the 1980s beating on this problem. A large number of very smart people tried to solve it. Many things were tried that were less rigid than predicate calculus - probabilistic logic, Markov chains, fuzzy logic, etc. All mostly failed. The AI Winter followed.
The classic critique in this area is "Artificial Intelligence meets Natural Stupidity", by Drew McDermott.[3] That's from 1976, and still relevant to this argument.
LLMs, though, might be able to use such models. Something to try: put a story problem into an LLM, and ask it what formal methods might help solve this problem. Then ask it to convert the problem into each of those formal methods. Then use something like Mathematica on each formal method. LLMs can't do logic problems, but they can sort of write code and translate between languages. So maybe they can do the miracle part. Anybody working on this?
[1] https://en.wikipedia.org/wiki/Circumscription_(logic)
[2] https://trevor-hopkins.com/fiction/miracle2.jpg
[3] file:///home/john/Downloads/Artificial_Intelligence_meets_natural_stupidity-2.pdf
He has a good point that model-less LLMs have serious trouble with problems that require a model. But predicate calculus hasn't worked out well as that model.
Many years ago, I took John McCarthy's "Epistemological problems in artificial intelligence" class. He laid out the missionary and cannibals problem informally, then wrote it up in a predicate-calculus notation, and then applied his "circumscription logic"[1]. As he wrote it up in his formulation, I thought "and then a miracle occurs".[2] As with most story problems, it's getting the problem into the correct formalism that's hard. Turning the crank on the formalism is usually straightforward.
Much of the AI community spent the 1980s beating on this problem. A large number of very smart people tried to solve it. Many things were tried that were less rigid than predicate calculus - probabilistic logic, Markov chains, fuzzy logic, etc. All mostly failed. The AI Winter followed.
The classic critique in this area is "Artificial Intelligence meets Natural Stupidity", by Drew McDermott.[3] That's from 1976, and still relevant to this argument.
LLMs, though, might be able to use such models. Something to try: put a story problem into an LLM, and ask it what formal methods might help solve this problem. Then ask it to convert the problem into each of those formal methods. Then use something like Mathematica on each formal method. LLMs can't do logic problems, but they can sort of write code and translate between languages. So maybe they can do the miracle part. Anybody working on this?
[1] https://en.wikipedia.org/wiki/Circumscription_(logic)
[2] https://trevor-hopkins.com/fiction/miracle2.jpg
[3] file:///home/john/Downloads/Artificial_Intelligence_meets_natural_stupidity-2.pdf