4 ms·

I've started thinking about the whole "do computers grok meaning" thing in terms of proof. If a computer tells me a true theorem, I don't know if I can ascribe

by imh 8y ago

I've started thinking about the whole "do computers grok meaning" thing in terms of proof. If a computer tells me a true theorem, I don't know if I can ascribe "understanding" to it. If it tells me a true theorem and comes up with a proof, then I'm comfortable defining that as understanding within the context of that particular proof language. It passes the buck up a step. You define a new notion of understanding-in-a-given-language and then get to argue about whether that language/deduction system constitutes true "understanding."

panic 8y ago
The problem isn't deduction. It's getting things into the deductive system in the first place. You have to model the world, and your model will probably be incorrect somehow (https://www.student.cs.uwaterloo.ca/~cs492/11public_html/p18-smith.pdf https://www.student.cs.uwaterloo.ca/~cs492/11public_html/p18...).
freeone3000 8y ago
Okay, but what if it just made stuff up by trying everything until something came out true? We have theorum provers on this model today. Does such a system "understand" mathematics? It's probably more explainable than anything else, but the strength of the current generation of learning is application to cases with ambiguity present, and our current approaches here are completely unexplainable.
- imh 8y ago
  I'm saying that we can define what constitutes understanding by defining what constitutes reasoning within a given inference system. That's a simpler task, but doesn't solve the original problem. It just passes the buck. Now instead of asking whether a given learner performs reasoning and understands, we could ask whether the language/logic constitutes understanding. I'd definitely say that the current theorem provers have some form of true understanding, even though it isn't the same form as we have. For the typical ML learners, I think it's more interesting to ask and taxonomize "in what ways is this reasoning/understanding" rather than just ask "is this reasoning/understanding?"

by imh 8y ago

panic 8y ago

The problem isn't deduction. It's getting things into the deductive system in the first place. You have to model the world, and your model will probably be incorrect somehow (https://www.student.cs.uwaterloo.ca/~cs492/11public_html/p18-smith.pdf https://www.student.cs.uwaterloo.ca/~cs492/11public_html/p18...).

freeone3000 8y ago

Okay, but what if it just made stuff up by trying everything until something came out true? We have theorum provers on this model today. Does such a system "understand" mathematics? It's probably more explainable than anything else, but the strength of the current generation of learning is application to cases with ambiguity present, and our current approaches here are completely unexplainable.

imh 8y ago
I'm saying that we can define what constitutes understanding by defining what constitutes reasoning within a given inference system. That's a simpler task, but doesn't solve the original problem. It just passes the buck. Now instead of asking whether a given learner performs reasoning and understands, we could ask whether the language/logic constitutes understanding. I'd definitely say that the current theorem provers have some form of true understanding, even though it isn't the same form as we have. For the typical ML learners, I think it's more interesting to ask and taxonomize "in what ways is this reasoning/understanding" rather than just ask "is this reasoning/understanding?"