I think his point was that we can't code the fundamentals because those require linear time protein folding. And protein folding is one of those hard CS problems.
At this point we don't even have accurate models for most proteins, let alone knowing how to predict what they do.
My current project is a search engine for protein chain geometry. We only have ~20% of the known proteins in our database because the data on the other 80% isn't accurate enough to be useful.
Well that's exactly my criticism: most of the author's objections boil down to "it's hard". Note that I don't disagree with him (nor with you), but this just doesn't help to expose the real issues with Kurzweil's estimates. To "protein folding is difficult" one can always reply "but we'll solve it in the next 10 years" - which I think is what the singularity-folks would say.
My simpler point is that Kurzweil's not taking a useful measure for the size of the system we're solving. (By the way, he plays the same kind of trick on his audience when he's pointing out there are only a few billion neurons in the brain - as if that were the only level of complexity in the brain).
Well that's exactly my criticism: most of the author's objections boil down to "it's hard"
No, common English use of "it's hard" means something completely different from CS "hard". CS hard means NP-complete which to English translates as impossible. Impossible because of well understood mathematical reasons.
Quantum computers may solve it, indeed real life protein folding may have quantum computer-like properties.
