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Well what I'm saying is that we can derive your first paragraph purely with computing power. What we need are computers with roughly 100 billion cores, each at least capable of simulating a neuron (maybe an Intel 80286 running Erlang or similar), and a simple mesh network (more like the web) that's optimized for connectivity instead of speed. This is on the order of 100,000*100,000,000,000 = 1e16 transistors, or about 7 orders of magnitude more than an Intel i7's billion transistors. It would also be running at at least 1 MHz instead of the 100 or 1000 Hz of the human brain, so we can probably subtract a few orders of magnitude there. I think 10,000 times faster than today is reasonable, or about 2 decades of Moore's law applied to video cards.

Then we feed it scans of human minds doing various tasks and have it try combinations (via genetic algorithms etc) until it begins to simulate what's happening in our imaginations. I'm arguing that we can do all that with an undergrad level of education and understanding. Studying the results and deriving an equation for consciousness (like Copernicus and planetary orbits) is certainly beyond the abilities of most people, but hey, at least we'll have AGI to help us.

Totally agree about the rest of what you said though. AGI <-> sacrifice. We have all the weight of the world's 7 billion minds working towards survival and making a few old guys rich. It's like going to work every day to earn a paycheck, knowing you will die someday. Why aren't we all working on inventing immortality? As I see it, that's what AGI is, and that seems to scare people, forcing them to confront their most deeply held beliefs about the meaning of life, religion, etc.




You're focusing on an aspect of Neurons in which there isn't even an accurate understanding and attempting to make a direct mapping to computer hardware. This is framing w/o understanding and you should be able to clearly understand why you can't make analysis or forward projections based on it.

Video cards operate on a pretty limited scope of computing that might not even be compatible with Neuron's fundamental algorithm. The only thing SIMD has proven favorable towards is basic mathematics operations with low divergence which is why Optimization algorithm based NN function so well on them.

This is the entrapment many people in the industry fall for. The first step towards AGI is in admitting you have zero understanding of what it is. If one doesn't do this and simply projects their schooling/thinking and try to go from there, you end up with a far shorter accomplishment.

You can't back derive aspects of this problem. You have to take your gloves off and study the biology from the bottom up and spend the majority of your time in the theoretical/test space. Not many are willing to do this even in the highest ranking universities (Which is why I didn't pursue a PhD).

There is far too little motivation for true understanding in this world which is why the majority of the world's resources and efforts are spent on circling the same old time test wagons.. Creating problems then creating a business model to solve it. We are only fooling ourselves in this mindless endeavors. When you break free long enough, you see it for what it is and also see the paths towards more fundamental pursuits. Such pursuits aren't socially celeberated or rewarded. So, you're pretty much on your own.

> As I see it, that's what AGI is, and that seems to scare people, forcing them to confront their most deeply held beliefs about the meaning of life, religion, etc.

One thing about this interesting Universe is that when a thing's time has come it comes. It points to a higher order of things. There's great reason and purpose to address these problems now and its why AGI isn't far off. If you look at various media/designs, society is already beckoning for it.


You know, I find myself agreeing with pretty much everything you've said (especially limitations of SIMD regarding neurons etc). I'm kind of borrowing from Kurzweil with the brute force stuff, but at the same time I think there is truth to the idea that basic evolution can solve any problem, given enough time or computing power.

I guess what I'm getting at, without quite realizing it until just now, is that AI can be applied to ANY problem, even the problem of how to create an AGI. That's where I think we're most likely to see exponential gains in even just the next 5-10 years.

For a concrete example of this, I read Koza's Genetic Programming III edition back when it came out. The most fascinating parts of the book for me were the chapters where he revisited genetic algorithm experiments done in previous decades but with orders of magnitude more computing power at hand so that they could run the same experiment repeatedly. They were able to test meta aspects of evolution and begin to come up with best practices for deriving evolution tuning parameters that reminded me of tuning neural net hyperparameters (which is still a bit of an art).

Thanks for the insight on higher order meaning, I've felt something similar lately, seeing the web and exponential growth of technology as some kind of meta organism recruiting all of our minds/computers/corporations.




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