I have to admit that I have no idea; my understanding of the brain isn't enough to even assess the magnitude of the challenge. Intuitively, it seems at least as hard as “find cheap renewable energy”, but I might be completely wrong.
My point is that to “model brains better” requires a lot more knowledge about the brains (neurology, microbiology, chemistry) and a lot more computing power, and those things require progress in other areas, and so on, so that sounds like one of those equivalent supergoals.
Right. This should read “if you believe in friendly AI singularity”. Updating the post.
This is a response to Ars Longa, Vita Brevis, an excellent piece by Scott Alexander. In fact, it moved me so much that I signed up on LessWrong just to write this response. I'm going to argue that the essay's central idea is wrong, and that's a good thing. You should read Alexander's essay before reading mine.
Alexander writes:
... (read 1262 more words →)The first student has no master, and must discover everything himself. He researches for 70 years, then writes his wisdom into a book before he dies. The second student reads the book, and in 7 years, he has learned 70 years of research. Then he does his own original research for 63 years and writes
Interesting.
This might have something to do with the fact that the problems are getting harder now that the low-hanging fruit has been picked. Every additional year to life expectancy is harder than the one before. Every cycle of Moore's law is harder because we're starting to deal with sizes comparable to molecules.
I admit that this makes my point weaker.