I agree with the information theoretical claim, and I think you could prove it with the usual language-to-language argument for Kolmogorov complexity; the gist: the brain is the result of a program written in DNA for a certain extremely complex language known as 'the human body', which when run, takes an extremely complex input known as 'life' (all of which can be modeled in binary thanks to the universe apparently being computable). We want to translate the program written in DNA to a program written in x86; both are languages, so the translation only requires a certain fixed-length prefix interpreting the DNA for x86.
I take your link as agreeing that it works in theory but disagreeing about the practice: 'yeah, but all of those parts are extremely extremely complex and that fixed-length prefix is a really big prefix which we aren't even close to writing, and X and Y and Z; hence, Kurzweil's forecasts are way off and ridiculously optimistic'. Notice he doesn't talk in terms of it being impossible, period, but rather of missing parts and explanations of how something will be accomplished:
I presume they understand that if you program a perfect Intel emulator, you don't suddenly get Halo: Reach for free, as an emergent property of the system. You can buy the code and add it to the system, sure, but in this case, we can't run down to GameStop and buy a DVD with the human OS in it and install it on our artificial brain. You're going to have to do the hard work of figuring out how that works and reverse engineering it, as well. And understanding how the processor works is necessary to do that, but not sufficient.
(Having the fixed-length interpreter for the DNA program is necessary but not sufficient; having the input for the program is necessary but not sufficient; etc.)
This is the other case where I think Kurzweil is just in error.
The number of bits that it takes to encode DNA given "the language of the human body" is small, but how many bits to encode the language of the human body, and the language of cells, and the language of chemistry, and the language of the biome?
I can encode wikipedia with one digital bit, if I allow Wikipedia as one of the units in which I am encoding, and keep that complexity off the books. That's what Ray is doing here - keeping the complexity of atoms and molecules and cells and bi...
Ray Kurzweil's writings are the best-known expression of Singularity memes, so I figured it's about time I read his 2005 best-seller The Singularity is Near.
Though earlier users of the term "technological Singularity" used it to refer to the arrival of machine superintelligence (an event beyond which our ability to predict the future breaks down), Kurzweil's Singularity is more vaguely defined:
Kurzweil says that people don't expect the Singularity because they don't realize that technological progress is largely exponential, not linear:
Kurzweil has many examples:
He emphasizes that people often fail to account for how progress in one field will feed on accelerating progress in another:
Kurzweil's second chapter aims to convince us that Moore's law of exponential growth in computing power is not an anomaly: the "law of accelerating returns" holds for a wide variety of technologies, evolutionary developments, and paradigm shifts. The chapter is full of logarithmic plots for bits of DRAM per dollar, microprocessor clock speed, processor performance in MIPS, growth in Genbank, hard drive bits per dollar, internet hosts, nanotech science citations, and more.
The chapter is a wake-up call to those not used to thinking about exponential change, but one gets the sense that Kurzweil has cherry-picked his examples. Plenty of technologies have violated his law of accelerating returns, and Kurzweil doesn't mention them.
This cherry-picking is one of the two persistent problems with The Singularity is Near. The second persistent problem is detailed storytelling. Kurzweil would make fewer false predictions if he made statements about the kinds of changes we can expect and then gave examples as illustrations, instead of giving detailed stories about the future as his actual predictions.
My third major issue with the book is not a "problem" so much as it is a decision about the scope of the book. Human factors (sociology, psychology, politics) are largely ignored in the book , but would have been illuminating to include if done well — and certainly, they are important for technological forecasting.
It's a big book with many specific claims, so there are hundreds of detailed criticisms I could make (e.g. about his handling of AI risks), but I prefer to keep this short. Kurzweil's vision of the future is more similar to what I expect is correct than most people's pictures of the future are, and he should be applauded for finding a way to bring transhumanist ideas to the mainstream culture.