Perhaps the disconnect here is that Kurzweil, operating from an information theory perspective, is neglecting the possibility that the biological environment in which a brain grows effectively adds a ton of "data" to the system

Please realize, despite the fact that pretty much everyone on HN is repeating this argument (the "data gets added to the system" argument), it is an extraordinary claim, and should require correspondingly extraordinary evidence if we're to consider it.

I'm going to justify this in excruciating detail, because the claim has now come up so many times.

But first, let's nail down the context, because if we can't agree on that then we really shouldn't even be discussing the topic (and I suspect the whole problem here is that Myers thinks they're arguing about something other than what Kurzweil is actually claiming) - we're discussing the amount of information that we would need to construct an effective intelligent algorithm. Not one particular algorithm, but any effective intelligent algorithm.

Here goes, a pseudo-mathematical breakdown of why this "data gets added" argument is so hideously wrong:

There's an entire infinite universe of "possible intelligence algorithms" (for the moment, we won't define this too precisely, but we'll hand wave and say that this universe consists of all algorithms that take the right inputs and provide the right outputs, whatever those are), most of which are utterly useless, and are certainly not intelligent. Let's call this universe U0.

Step one: let's cut U0 down to a finite practical size, eliminating ridiculous algorithms that we could never expect to implement. We can do this in a million ways, it doesn't really matter; for now, let's just say that we're cutting it down to algorithms that have possible physical realizations using the resources on our planet. That's still a huge number of algorithms. Call this U1.

Step two: Let's now trim U0 in a different way, picking out only the algorithms that we consider actually intelligent, however you want to define "intelligent". Name this (still infinite) set Z.

Step three: Take the intersection of Z (intelligent algorithms) with U1 (practical algorithms), call this set P. P is all the practical algorithms that qualify as "intelligent".

Now let Prob(I) = (size of P / size of U1), the probability that a randomly selected practical algorithm will be intelligent. This is an extremely small probability, but it's finite and non-zero (human intelligence suffices to prove that it's non-zero).

Step four: Now we slice up U1 in a different way, and create a set D_N: the set of all algorithms that can be specified by growing a human from a string of DNA of length N (and that ultimately run within the space constraints).

Step five: Set P(D_N) = intersection of D_N and P, all intelligent algorithms satisfying the space constraints that can be grown from a DNA string of length N.

Ok, that's a lot of sets, but it's okay, we don't need most of them. One last calculation:

Prob(D_N) = (size of P(D_N) / size of D_N), the probability that a randomly selected practical DNA-created algorithm will be intelligent.

No more set-fu, I promise. We've boiled it down to two probabilities, Prob(I), and Prob(D_N). These probabilities are proxies for the information content needed to pick an intelligent algorithm out of the corresponding sets of algorithms.

The "information gets added" claim has a very simple mathematical expression:

Prob(D_N) > Prob(I) when N = the length of human DNA

i.e. a randomly selected DNA-created algorithm with DNA length N has a greater probability of qualifying as intelligent than a randomly selected algorithm in general. And not just a little bit greater - you're saying that the fact that it's implemented via DNA makes the probability much higher, corresponding to the data difference you're claiming with the statement 'far, far more than 50MB of "data" here'.

Perhaps now you see the trouble: in order for me to consider the "data gets added" argument plausible, I need to hear an argument that suggests that a random construction based on DNA is far more likely to lead to an intelligent algorithm than a random construction in general.

Myers has not offered an argument in this direction. Neither has anyone else. Until someone does, the odds are overwhelmingly in Kurzweil's favor; statistically speaking, Myers is flat out wrong.

So I put the question to everyone: what's so special about the DNA construction process that makes it so much more likely to create intelligence than any other construction process we might conceive of?