Ray Kurzweil Responds To PZ Myers 238
On Tuesday we discussed a scathing critique of Ray Kurzweil's understanding of the brain written by PZ Myers. Reader Amara notes that Kurzweil has now responded on his blog. Quoting: "Myers, who apparently based his second-hand comments on erroneous press reports (he wasn't at my talk), [claims] that my thesis is that we will reverse-engineer the brain from the genome. This is not at all what I said in my presentation to the Singularity Summit. I explicitly said that our quest to understand the principles of operation of the brain is based on many types of studies — from detailed molecular studies of individual neurons, to scans of neural connection patterns, to studies of the function of neural clusters, and many other approaches. I did not present studying the genome as even part of the strategy for reverse-engineering the brain."
Re:The best resolution... (Score:3, Informative)
Heck, even people in the fields of science related to some advancements don't see some of those advancements coming.
In one of the Futures in Biotech podcasts (a 2007 episode if I recall) the guest was talking about gene sequencing and that as little as four years before they managed to sequence an earthworm genome it was thought to be impossible because of the work/technology involved. And then they did it. Shortly afterward the human genome project began.
Whether Kurzweil is in crazyland or not, if he's just making optimistic forecasts of the future he's at least getting people to think about it. And if people are thinking about it skeptically, at least we're going to encourage critical thinkers.
Kurzweil is right (Score:4, Informative)
Kurzweil is absolutely correct. His best argument is not the complexity of the genome, but focusing on the actual functional structures in the brain. A cortex composed of a billion repeating units is something we CAN feasibly simulate. Already, we have massive systems that run an algorithm spread across billions of separate instances. (google.com is one)
An "algorithm" could also model the behavior of a few neurons working in circuit.
Also, keep in mind that most of the complexity of the brain and body are completely unrelated to the task of thinking. Much of that genome codes for molecular machine parts needed to maintain and grow the hardware. There's all kind of defense and circulatory and support systems that we won't have to worry about when designing artificial minds.
And finally, when you consider the changes made to the brain from the enviroment : that doesn't make the problem harder. Once you have a self organizing neural system that works like the human brain but a million times faster, you expose that system to our environment and train it up just like we do with humans. Sure, it might take a few years for such a system to reach super-intelligence, but if your fundamental design was right then this would eventually happen.
Re:may actually be SLOWING DOWN, not accelerating. (Score:3, Informative)
As someone who actually does neuroscience research, the tools and techniques available today were almost undreamed of a couple of decades ago. Nothing is slowing down. But more money is always greatly appreciated, of course.
Re:Just because Myers is an ass doesn't mean Kurzw (Score:1, Informative)
A Turing machine is equivalent, from a theoretical point of view, to any computer.
The brain is physical thing, so it can be simulated, by a Turing machine or any powerful enough computer.
Re:Kurzweil is right (Score:3, Informative)
Kurzweil is absolutely correct. His best argument is not the complexity of the genome, but focusing on the actual functional structures in the brain. A cortex composed of a billion repeating units is something we CAN feasibly simulate. Already, we have massive systems that run an algorithm spread across billions of separate instances. (google.com is one)
I would urge you to read the following slashdot post: http://science.slashdot.org/comments.pl?sid=1757102&cid=33278462 [slashdot.org] The point of the post is that we are unable to model the neural activities of a worm with 302 neurons, and this after an extremely large amount of work. The cortex is not 'composed of a billion repeating units'. It is composed of 100 billion non-repeating units, with thousands of connections (each) to other non-repeating units, and each of the non-repeating units keep changing both internally and in their connection strengths, and the fluid that the units works in keeps changing and affecting huge numbers of units, and it turns out that interesting things are happening in the dendritic trees of each of the individual units. The whole question of the computational unit of the brain is back in play.
I don't think that the brain is in-theory too complex to model or understand. We know a lot, and the speed of research is great. It's just that as we make progress in understanding it we are discovering that it is more complicated than we had imagined, so the point that we think that we will really understand the brain isn't getting a lot closer. And these are just the 'known unknowns'. There are quite possibly 'unknown unknowns' that will make it even harder. That's science for you. If we knew what we were doing, it wouldn't be research.
My issue with your post is that it is flippant. You really don't know (and nobody knows, so it's not you specifically) what percent of the way to understanding the brain we are. So having phrases like 'it might take a few years' in your post makes me cringe. We'll get there, I really think we will, but we're a long way from even knowing how well we're doing.