Hacker News Reader

Comment by midnightmonster | Hacker News Reader

What I got from the previous article (admittedly as my own synthesis, not afaict from the original text as such) was, sure, the program to build a brain is only X Megabytes, but the computer that runs that program is the human body growing in the physical universe. If you want to be able to run that program, you're going to need to emulate at least the relevant instruction subset of the physical universe. It's hard to know how large is the relevant subset or if computers will ever plausibly get there. If the subset turns out to be quite large, you'd need a computer that could model its own subatomic physics.

View on HN

I want to stress that we have the math to do that...and on regular chipsets, its just rather slow..which is inherent to the key to kurzwiel's points, that we're building faster and faster computers, and that brains (and likely the universe) are not the simplest possible expressions of themselves.

That is what I got from the previous article as well. However, from reading Kurzweil's article get that this point is irrelevant, because he never suggested to reverse engineer the brain in that way. He used the genome argument as an estimate on how complex the brain is, basically viewing the genome as a data compression of the brain.

Myers argument only shows that the decompression algorithm, i.e. the route from the genome to brain, is insanely complex, but it doesn't say anything about the actual complexity of the brain. So in essence, yes, if we would choose to model the brain in a highly compressed form like the human genome we would potentially need a computer that could model it's own subatomic physics, but that's not likely the way we would want to approach this.

Anyways, this doesn't mean that the brain isn't very complex and impossible for us to model at the moment. They main question is how long it will take for us until this complexity is manageable (if ever).

> the decompression algorithm, i.e. the route from the genome to brain, is insanely complex, but it doesn't say anything about the actual complexity of the brain

This is where both Kurzweil and you are wrong. A very complex compression/decompression scheme can achieve much better compression. Intuitively, you can encode some of the information in the decompressor itself, even if it is in a very abstract form. This is the reason why compression competitions include size of the decompressor code, e.g. http://prize.hutter1.net/

Even if the "decompression algorithm" is somehow optimized for making intelligent brains easy to encode, the "source code" for it is still present in the other half of the genome, so this doesn't affect the argument much.

It's not in the other half of the genome. All cells in an organism share the same DNA, but different cells develop in a very differentiated manner depending on the cells around them (e.g. should it be a neuron or a connecting tissue?). The "decompression algorithm" is in the laws of physics, biochemistry, and the way life works in general. Since we don't understand these well enough, we can't make reasonable information-theoretic claims about the "decompressed" genome.

It all starts from a single zygote. Every material in that zygote is either an essential nutrient, a peptide made according to its DNA (including mitochondrial DNA), or catalyzed from essential nutrients by those peptides.

The laws of physics and biochemistry are irrelevant, unless you're claiming that a substantial fraction of the information needed to build intelligence (we're talking tens of megabytes here) is encoded in the laws of physics or in the biochemistry we share with snottites.

Reply on news.ycombinator.com