[iotb]

Entrenched mindsets don't like for the flaws in their views to be highlighted. It's one of Humanity's most serious flaws. As far as AGI being 10-20 years away based purely on compute power, you can't make this statement accurately unless you have a firm understanding of the underlying algorithms that power human intelligence and by extension AGI. From there, you also need to have a formal education and deep industry experience with Hardware to know what its capabilities are today, what they will be in the future roadmap wise, and how to most efficiently map an AGI algorithm to them. I'd say that 0.1% of people have this understanding and nobody is listening to them.

> The real problem though (as I see it) is that the vast majority of the best and brightest minds in our society get lost to the demands of daily living. I've likely lost any shot I had at contributing in areas that will advance the state of the art since I graduated college 20 years ago. I think I'm hardly the exception. Without some kind of exit, winning the internet lottery basically like Elon Musk, we'll all likely see AGI come to be sometime in our lifetimes but without having had a hand in it.

They don't get lost so much as they become trapped for reasons due to systematic and flawed optimization structures found throughout society. All is not lost if one breaks out long enough to realize they can make certain pursuits if they are willing to make a sacrifice. The bigger the pursuit, the bigger the required sacrifice. Not many people are willing to do that in the valley when you have a quarter of a million dollar paycheck staring you in the face. You could of course make a decision to sacrifice everything one given day and you'd have 5 years of runway easily if you saved your money properly. Obviously, VC capital wont fund you. Obviously universities aren't the way to go given the obsession with Weak AI. Obviously no AI group will hire you unless you have a PhD and/or are obsessed with Weak AI. Obviously you might not even want this as it will cloud your mind. So, clearly, the way to make ground breaking progress is to walk off your job, fund a stretch of research yourself, and be willing to sacrifice everything. Quite the sacrifice? People will laugh at you. What happens if you fail? Socially, per the mainstream trend, you'll fall behind. If you have a partner, this will be even more difficult as the trend is to get rich quick, get promoted to management, buy a million dollar home, have kids, stay locked in a lucrative position at a company. And what of your pride? Indeed.. And therein is the true pursuit of AGI.

The winners are pushing fundamentally flawed AI techniques because it requires massive amounts of data and compute which is their primary business model. They wont succeed because they are optimizing a business model that is at the end of its cycle and not optimizing the pursuit of AGI.

AGI is coming and it is completely out of the scope of the current winners. If a person desires to pursue and develop AGI, they'd have to be bold enough to sacrifice everything... It's how all of the true discoveries are made for all of time and science. Nothing has changed but for reasons due to money primarily, when the historical learning lessons are far off enough people attempt to re-tell/re-invent the wheel in their favor.. Only to be reminded : Nothing has changed.

The individual discoverers change over time however for they learn from history.

[zackmorris]

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.

[iotb]

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.

[zackmorris]

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.