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ewjordan: That's beautiful. Let me sort it out slightly and offer a counter argument or at least response to part. So, we agree that Kurzweil's "information

by dasht 16y ago

ewjordan: That's beautiful. Let me sort it out slightly and offer a counter argument or at least response to part. So, we agree that Kurzweil's "information theory" snobbery is wrong. His real argument is "C'mon... look, the genome's small. Under a microscope the brain looks like it has many parts but very regularly arranged. How hard can it be? Trillions of lines? Please!" That's not an information theory argument. That's a vague, hand-wave argument to an underspecified but compelling-sounding conclusion. "Reverse engineer the brain." "Build something similar." WTF could possibly happen that would prove him wrong? How exactly could Kurzweil's "predictions" here be falsified? Put another way, if he changed his rebuttal to Meyers to be "I made no substantive argument or claim. Myers responded as if I had. Therefore Myers has erred." -- I could accept that. It then does raise the question of why Kurzweil was not more explicit about making no substantive argument or claim but that's a separate matter. It's moot because Kurzweil isn't making that rebuttal. To your statistical argument, which is quite interesting... I think the meat of your case is here: So I ask you this: do you know a fact about "zygote machines" that makes them much better suited to constructing intelligence algorithms than most other machines? Rather than quibble over what "intelligence algorithms" mean I am going to pretend you said "human brains or things very similar to such". The answer is "Yes, I know quite a few facts that strongly support the hypothesis that human zygotes are, among the machine-like entities in the world, uniquely well suited to building human brains -- and very difficult to replace by any substantially different kind of machine." At this point I would basically just repeat Myers' argument, perhaps adding in more specific but randomly selected details. If you want to rescue Kurzweil by leaving the abstract "information theory" b.s. he offered and looking at the specifics -- then we've gone full circle. Kurzweil doesn't understand the brain. Now there is an exception to all this. A different way of looking at it. I think that if you scrape off layers of hype and clouds of obfuscation, Kurzweil will consider himself to be proved correct if, in say 20 years, -- and just for example: You can buy a box that has at least stereo video inputs and that, using an artificial neural net, does exquisitely accurate facial recognition. Or that can look at visualization of architectural CAD drawings -- millions of variations per hour -- and select a few with a high percentage chance of being pleasing to most people. Or that, in combination with the tactile-feedback neural net, can manipulate agonizingly capable microscopic tools for very delicate surgeries or for building nanotech or ... I think it's f'ing obvious that (unless civilization fails - not out of the question) we have all that in 20 years and maybe sooner. I think that was f'ing obvious about 30 years ago, and to some, pretty clear even before that. I don't think those devices count, in any reasonable way, as "reverse engineering the brain" but I guess they count as "reverse engineering a few select aspects of useful computational tricks that brains do in real time, quite efficiently". I don't think those inevitable advances offer much support to Kurzweil's "exponential" technology - they are straight up incremental, boringly predictable advances. I don't think they're a real challenge to ordinary human predictive powers: we've seen this stuff coming for decades. Don't even get me started on how "the singularity" is dangerous, meaningless, new-age clap-trap. But, Kurzweil dresses up such banal observations to make it sound like, any day now, massive machine mega-brains will take over the world. Hopefully they'll love us and kindly upload our consciousness and..... So it is, to repeat my original point, with some delight that I take on Kurzweil's "information theory" sniping at Meyers.

knowtheory 16y ago
It just occurred to me that Ray Kurzweil's claim entails that we can solve protein folding.
- jacquesm 16y ago
  We can solve protein folding, we're doing that on a daily basis. We just can't do it fast enough (yet) because we're using (somewhat constrained) brute force for a search space with a very large number of dimensions. As a consequence of that the computations with the current algorithms are for practical reasons limited to relatively small proteins. But the methods are as far as I understand well understood and it is more of an optimization problem than something unsolved. Edit: or did you mean 'solved' in an analytical way?
ewjordan 16y ago
Rather than quibble over what "intelligence algorithms" mean I am going to pretend you said "human brains or things very similar to such". I think this pretty well illuminates the source of our "disagreement" (and resolves it), apart from this we're on the same page about the details, I think. To me, there's a very big difference between what I would qualify as successful AGI (artificial general intelligence) and "human brains or things very similar to such", in that successful AGI could work very differently from a human brain (and IMO, probably will, if/when we ever get there) and still qualify as a bulls-eye hit. Taking that as our (relatively wide) target, I don't think protein folding and all that fun stuff adds much information. However, if our target is narrower, simulating a brain or something close to that, then I agree, the details of biology do shift the estimates considerably. Looking over one of Kurzweil's actual statements: It is true that the information in the genome goes through a complex route to create a brain, but the information in the genome constrains the amount of information in the brain prior to the brain’s interaction with its environment. ...it appears that you're right, he's talking more about creating an actual brain than creating some algorithm that solves the same problem (possibly in a different way). Mea culpa: I unwittingly altered his argument before defending it, so I've really been arguing about what he should have said rather than what he actually said. Not all is lost, though: the fact that his claim can be fixed up so that it's got some actual teeth is still worth noting, and I think Myers criticism is a bit too broad (he essentially claims that you can't say anything useful based on the length of a DNA string, which is not true). I think the real lesson here is that if we want to use DNA length as a proxy for information content, we need to be exquisitely careful about what "information content" means relative to the systems we're discussing, and nail down exactly what systems those are and how we're defining our problem.

by dasht 16y ago

knowtheory 16y ago

It just occurred to me that Ray Kurzweil's claim entails that we can solve protein folding.

jacquesm 16y ago
We can solve protein folding, we're doing that on a daily basis. We just can't do it fast enough (yet) because we're using (somewhat constrained) brute force for a search space with a very large number of dimensions. As a consequence of that the computations with the current algorithms are for practical reasons limited to relatively small proteins. But the methods are as far as I understand well understood and it is more of an optimization problem than something unsolved. Edit: or did you mean 'solved' in an analytical way?

ewjordan 16y ago

Rather than quibble over what "intelligence algorithms" mean I am going to pretend you said "human brains or things very similar to such". I think this pretty well illuminates the source of our "disagreement" (and resolves it), apart from this we're on the same page about the details, I think. To me, there's a very big difference between what I would qualify as successful AGI (artificial general intelligence) and "human brains or things very similar to such", in that successful AGI could work very differently from a human brain (and IMO, probably will, if/when we ever get there) and still qualify as a bulls-eye hit. Taking that as our (relatively wide) target, I don't think protein folding and all that fun stuff adds much information. However, if our target is narrower, simulating a brain or something close to that, then I agree, the details of biology do shift the estimates considerably. Looking over one of Kurzweil's actual statements: It is true that the information in the genome goes through a complex route to create a brain, but the information in the genome constrains the amount of information in the brain prior to the brain’s interaction with its environment. ...it appears that you're right, he's talking more about creating an actual brain than creating some algorithm that solves the same problem (possibly in a different way). Mea culpa: I unwittingly altered his argument before defending it, so I've really been arguing about what he should have said rather than what he actually said. Not all is lost, though: the fact that his claim can be fixed up so that it's got some actual teeth is still worth noting, and I think Myers criticism is a bit too broad (he essentially claims that you can't say anything useful based on the length of a DNA string, which is not true). I think the real lesson here is that if we want to use DNA length as a proxy for information content, we need to be exquisitely careful about what "information content" means relative to the systems we're discussing, and nail down exactly what systems those are and how we're defining our problem.