= 27d567bc2d48d9f40e9ccc20ea370b15)
soreff comments on Should I believe what the SIAI claims? - Less Wrong
You are viewing a comment permalink. View the original post to see all comments and the full post content.
= 783df68a0f980790206b9ea87794c5b6)
Loading…= b715d02e85f7b3b4ae65ca3d3e450868)
Subscribe to RSS Feed
Powered by Reddit
= f037147d6e6c911a85753b9abdedda8d)
You are viewing a comment permalink. View the original post to see all comments and the full post content.
Comments (600)
What would you accept as evidence?
Would you accept sophisticated machine learning algorithms like the ones in the Netflix contest, who find connections that make no sense to humans, who simply can't work with high-dimensional data?
Would you accept a circuit designed by a genetic algorithm, which doesn't work in the physics simulation but works better in reality than anything humans have designed, with mysterious parts that are not connected to anything but are necessary for it to function?
Would you accept a chess program which could crush any human chess player who ever lived? Kasparov at ELO 2851, Rybka at 3265. Wikipedia says grandmaster status comes at ELO 2500. So Rybka is now even further beyond Kasparov at his peak as Kasparov was beyond a new grandmaster. And it's not like Rybka or the other chess AIs will weaken with age.
Or are you going to pull a no-true-Scotsman and assert that each one of these is mechanical or unoriginal or not really beyond human or just not different enough?
I think it at least possible that much-smarter-than human intelligence might turn out to be impossible. There exist some problem domains where there appear to be a large number of solutions, but where the quality of the solutions saturate quickly as more and more resources are thrown at them. A toy example is how often records are broken in a continuous 1-D domain, with attempts drawn from a constant probability distribution: The number of records broken goes as the log of the number of attempts. If some of the tasks an AGI must solve are like this, then it might not do much better than humans - not because evolution did a wonderful job of optimizing humans for perfect intelligence, but because that part of the problem domain is a brick wall, and anything must bash into it at nearly the same point.
One (admittedly weak) piece of evidence: a real example of saturation, is an optimizing compiler being used to recompile itself. It is a recursive optimizing system, and, if there is a knob to allow more effort being used on the optimization, the speed-up from the first pass can be used to allow a bit more effort to be applied to a second pass for the same cpu time. Nonetheless, the results for this specific recursion are not FOOM.
The evidence in the other direction are basically existence proofs from the most intelligent people or groups of people that we know of. Something as intelligent as Einstein must be possible, since Einstein existed. Given an AI Einstein, working on improving its own intelligence - it isn't clear if it could make a little progress or a great deal.
This goes for your compilers as well, doesn't it? There are still major speed-ups available in compilation technology (the closely connected areas of whole-program compilation+partial evaluation+supercompilation), but a compiler is still expected to produce isomorphic code, and that puts hard information-theoretic bounds on output.