DNA is not a program-- it is a molecule, and one that may very well do things at the quantum level that are biologically important.

Sure, but Kurzweil's claim is merely that if DNA can encode everything the brain does with N bits of information, then regardless of how the DNA behaves, we have at least a loose estimate of the level of complexity in the brain. I don't necessarily think that he's right that AI will first be achieved in that manner, but I think I have a bit more faith in human ingenuity than he does, and I think we'll get the software there "by hand" before brain scanning hardware can actually do what he needs it to do.

Of course it's true that the decoding scheme and the dynamics of the end result could provide a whole lot of additional complexity, just like it's possible to build a decompression algorithm that allows us to compress a Linux distribution into 1 byte (put the whole program in the decompressor). But quantum effects or no, it seems extremely unlikely that the physics, chemistry, and biology behind all of this are somehow conspiring, magically tuned to provide an awesomely efficient set of basis functions to encode the algorithms that the brain needs to apply - sure, some parts of the brain's work probably exploit physical coincidences that make the overall job easier, but as far as we know, quantum chemistry doesn't offer a "do intelligence" utility function, that will have to be built up from much smaller sub-units. Far more likely is that the bulk of the brain's function is more or less explicitly coded for somewhere within our DNA.

The brain is not a neural network. It is an interconnected colony of living cells of a variety of types, and it has been shown that all types of cells in the brain are involved in cognition.

"Involved" is a serious weasel word when it comes to the brain, especially when AI is under discussion; everything in your skull is "involved" in cognition, but that doesn't mean it's doing anything particularly important, and it definitely does not mean that every detail of the dynamics is an absolute necessity to obtain Cognition.

But I think we might be arguing different things...

On a related tangent, I've found that many engineers are sympathetic to intelligent design type arguments against evolution. This is because they try to think about biology like engineers and take these machine analogies literally.

[Aside: I don't know too many engineers that buy into intelligent design, but I guess YMMV...]

The mistake that biologists make is that they always assume we're thinking about biology, and that our goal is to understand biological systems.

But when we're talking about AI, the goal is not to understand the brain, it's to figure out how to do something pretty close to what the brain does. Chances are, that's a much simpler goal than figuring out the dirty details about what every cell in the thing does. But it means that we have to be very careful not to get lost in the muck, worrying about the form of the brain's computations rather than the function. This is tricky, because it may be that the way the brain gets things done is not very well abstracted or comprehensible, so it's possible that we'll need to pick the level from which to draw inspiration from the brain very carefully (I think the apparent uselessness of neural nets in strong AI is a good indication that we might need to abstract at some level other than "neuron").

Again, though, Kurzweil has a very specific (and I'd argue, peculiar, at least relative to most people in AI) view on this, and thinks that full scale detailed brain simulations are the way that we need to do this (or at least that this will be the quickest route to the goal). I suspect even he doesn't think we'll simulate the physics of every neuron in detail, though, preferring to instead abstract away the most important bits of functionality.