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JonahSinick comments on Tiling Agents for Self-Modifying AI (OPFAI #2) - Less Wrong
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All I'm saying here is that general intelligence can construct algorithms across domains, whereas my impression is that impressive human+ artificial intelligence to date hasn't been able to construct algorithms across domains.
General artificial intelligence should be able to prove:
and thousands of other such statements. My impression is that current research in AI is analogous to working on proving these things one at a time.
Working on the classification of simple finite groups could indirectly help you prove the Atiyah-Singer Index Theorem on account of leading to the discovery of structures that are relevant, but such work will only make a small dent on the problem of proving the Atiyah-Singer Index Theorem. Creating an algorithm that can prove these things (that's not over-fitted to the data) is a very different problem from that of proving the theorems individually.
Do you think that the situation with AI is analogous or disanalogous?
I'm not sure if I follow. Is the algorithm that you have in mind the conglomeration of all existing algorithms?
If so, it's entirely unclear how quickly the algorithm is growing relative to the problems that we're interested in.
No, there is a single SDP rounding scheme that gets optimal performance on all constraint satisfaction problems (the best we know so far, and the best possible under the unique games conjecture).
Can you give a reference?
http://dl.acm.org/citation.cfm?id=1374414
PDF.
I'd be interested in your thoughts on this discussion post.
I would disagree with the statement that our algorithms are all domain-specific. Often some amount of domain-specific knowledge is needed to design a good algorithm, but it is often quite minimal. For instance, my office-mate is building a parser for interpreting natural language semantics, and has taken zero linguistics classes (but has picked up some amount of linguistics knowledge from talks, etc.). Of course, he's following in the footsteps of people who do know linguistics, but the point is just that the methods people use tend to be fairly general despite requiring task-specific tuning.
I agree, of course, that there are few systems that work across multiple domains, but I'm not sure that that's a fundamental issue so much as a symptom of broader issues that surface in this context (such as latent variables and complex features).
Thanks Jacob. I'd be interested in your thoughts on this discussion post.