| ▲ | quietbritishjim 13 hours ago | |||||||
I don't think that's true. Often, to come up with a proof of a particular theorem of interest, it's necessary to invent a whole new branch of mathematics that is interesting in its own right e.g. Galois theory for finding roots of polynomials. If the proof is automated then it might not be decomposed in a way that makes some new theory apparent. That's not true of a simple calculation. | ||||||||
| ▲ | seanmcdirmid 5 hours ago | parent | next [-] | |||||||
> I don't think that's true. Often, to come up with a proof of a particular theorem of interest, it's necessary to invent a whole new branch of mathematics that is interesting in its own right e.g. Galois theory for finding roots of polynomials. If the proof is automated then it might not be decomposed in a way that makes some new theory apparent. That's not true of a simple calculation. Ya, so? Even if automation is only going to work well on the well understood stuff, mathematicians can still work on mysteries, they will simply have more time and resources to do so. | ||||||||
| ▲ | ndriscoll 12 hours ago | parent | prev [-] | |||||||
This is literally the same thing as having the model write well factored, readable code. You can tell it to do things like avoid mixing abstraction levels within a function/proof, create interfaces (definitions/axioms) for useful ideas, etc. You can also work with it interactively (this is how I work with programming), so you can ask it to factor things in the way you prefer on the fly. | ||||||||
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