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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

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.

jacquesm 16y ago
> Taking that as our (relatively wide) target, I don't think protein folding and all that fun stuff adds much information. It may not add information at all, just as the physical structure of a transistor does not add much information to what a computer can or can not do. In a computer the 'smarts' however are not even embedded in the connections (like what's being posited is the case for the brain), but in the software. Software is state, and software is, to all intents an purposes as good as invisible, unless you find a way to do a dump of what sits inside a running brain. And then you still have to reverse engineer the computer that that software was running on in order to be able to resume. Myers DNA length argument is easily disproved by reducing to extremes, if DNA length would be an irrelevant item then you could encode a brain with an arbitrarily short length of DNA, the fact that it takes up as much as it does proves that it is from an information processing perspective not a simple structure. So length is relevant, maybe not the whole story, but definitely a factor. Part of me wonders if we are going to find one day that the genome does not just contain proteins but also contains the 'boot strap' state required to power up a brain after its initial configuration is complete. That's highly speculative but there is a lot more data in the genome than what seems to be used and nature never was that inefficient, even if there are many things that could be improved on with the function oriented hindsight that we have.

jacquesm 16y ago

> Taking that as our (relatively wide) target, I don't think protein folding and all that fun stuff adds much information. It may not add information at all, just as the physical structure of a transistor does not add much information to what a computer can or can not do. In a computer the 'smarts' however are not even embedded in the connections (like what's being posited is the case for the brain), but in the software. Software is state, and software is, to all intents an purposes as good as invisible, unless you find a way to do a dump of what sits inside a running brain. And then you still have to reverse engineer the computer that that software was running on in order to be able to resume. Myers DNA length argument is easily disproved by reducing to extremes, if DNA length would be an irrelevant item then you could encode a brain with an arbitrarily short length of DNA, the fact that it takes up as much as it does proves that it is from an information processing perspective not a simple structure. So length is relevant, maybe not the whole story, but definitely a factor. Part of me wonders if we are going to find one day that the genome does not just contain proteins but also contains the 'boot strap' state required to power up a brain after its initial configuration is complete. That's highly speculative but there is a lot more data in the genome than what seems to be used and nature never was that inefficient, even if there are many things that could be improved on with the function oriented hindsight that we have.