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Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

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61–70 of 181 posts

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#62
Not sure how I feel about this; for one, the Kurzweilian singularity which largely could be fueled by the advent of AGI is both exciting and yet also scary. The upside could forever change humanity as we know it; far increased longevity, the potential to create anything via a universal assembler[0], bringing everything feasible within the laws of physics to reality. Knowledge is the only limiting factor stopping us from doing anything which is physically possible in this universe; and in that light AGI could be an enlightenment.

On the other hand, the ubiquity of knowledge once it's available could lead any maniac to use it for the wrong purpose and wipe out humanity from their basement.

My feelings on the potential of AGI is therefore mixed. I for one have just found my particular niche in the workforce and am finally reaping the dividends from decades of hard work. Having AGI displace me and millions (or billions) of individuals is frightening and definitely keeps me on my toes.

Technology changes the world; my parents both worked for newspapers and talk endlessly about how the demise of their industry after the advent of the internet is so unfortunate. Luckily for them they are both at retirement age so their livelihood was not upset by displacement.

If AGI does become a thing it will be interesting to see how millenials and gen Z react to becoming irrelevant in what would have been the peak of their careers.

[0] https://en.wikipedia.org/wiki/Molecular_assembler

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#63

And no one should be surprised by this. The NN advancement of late doesn't help addressing human-style symbolic reasoning at all. All we have is a much more powerful function approximator with a drastic increased capacity (very deep networks with billions of parameters) and scalable training scheme (SGD and its variants). Such architecture works great for differentiable data, such's images/audios, but the improvement…

Something very interesting to me about the work Deep Mind has been doing is the way they've been combining neural network intuitions with tree search reasoning in Go, Chess, protein folding, etc.

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#64
post #8

Behind every successful neural network is a human brain. Neural networks are a tool, an advanced tool for sure, but still just a tool. If we are looking for AGI, and assuming the brain is an AGI, then there are still many differences to resolve. For example, back propagation has not been observed in nature. Nor has gradient descent. So the core mechanisms for learning in nature have still to reveal their secrets.

Behind every brain is a successful neural network. Or at least that's the promise of connectionism.

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#66
post #51

And no one should be surprised by this. The NN advancement of late doesn't help addressing human-style symbolic reasoning at all. All we have is a much more powerful function approximator with a drastic increased capacity (very deep networks with billions of parameters) and scalable training scheme (SGD and its variants). Such architecture works great for differentiable data, such's images/audios, but the improvement…

I don't understand this fixation on symbolic reasoning. Do any other animals practice this? If the answer is no, then it is probably not the most important milestone to AGI or at least not the one we should be currently aiming for. Right now we can not replicate the cognition of a mouse. Feels like we want to go to Mars before figuring out how to build a rocket.

Seconded. Even if animals do symbolic reasoning, they do it on top of hardware based on continuous physical dynamics, more similar to DNNs... So why not build on that platform?

I don't think biological precedent is the only or even most valuable heuristic for deciding where to research intelligence... But I don't see where there is evidence that symbolic reasoning is either necessary or sufficient for AGI, except people describing how they think their brain works.

Related, there are a lot of statements that symbolic or rule based systems do better / as well as / almost as well as neural methods. Citation please, I'd love a map of which ML problems are still best solved with symbolic systems. (Sincerely - it's not that I expect there aren't any.)

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#67

Demis Hassabis (true) statements here would be much more credible if DeepMind wasn't currently making a mint by promoting AlphaZero to the masses as a "general purpose artificial intelligence system". Don't believe me? Check out this series of marketing videos on YouTube by GM Matthew Sadler. 1. “Hi, I’m GM Matthew Sadler, and in this series of videos we’re taking a look at new games between AlphaZero, DeepMind’s gen…

I suspect "general purpose artificial intelligence system" means the same architecture applied to 3 games (western Chess, Shogi, Go).

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#68
I take huge offense to this article. They claim that when it comes to AGI, Hinton and Hassabis “know what they are talking about.” Nothing could be further from the truth. These are people who have narrow expertise in one framework of AI. AGI does not yet exist so they are not experts in it, in how long it will be, or how it will work. A layman is just as qualified to speculate about AGI as these people so I find it to be infinitely frustrating when condescending journalists talk down to the concerned layman. This irritates me because AI is a death scentance for humanity — its an incredibly serious problem.

As I have stated before, AI is the end for us. To put it simply, AI brings the world into a highly unstable configuration where the only likely outcome is the relegation of humans and their way of life. This is because of the fundamental changes imposed on the economics of life by the existence of AI.

Many people say that automation leads to new jobs, not a loss of jobs. Automation has never encroached on the sacred territory of sentience. It is a totally different ball game. It is stupid to compare the automation of a traffic light to that of the brain itself. It is a new phenomenon completely and requires a new, from-the-ground-up assessment. Reaching for the cookie-cutter “automation creates new jobs” simply doesn’t cut it.

The fact of the matter is that even if most of the world is able to harness AI to benefit our current way of life, at least one country won’t. And the country that increases efficiency by displacing human input will win every encounter of every kind that it has with any other country. And the pattern of human displacement will ratchet forward uncontrollably, spreading across the whole face of the earth like a virus. And when humans are no longer necessary they will no longer exist. Not in the way they do now. It’s so important to remember that this is a watershed moment — humans have never dealt with anything like this.

AI could come about tomorrow. The core algorithm for intelligence is probably a lot simpler than is thought. The computing power needed to develop and run AI is probably much lower than it is thought to to be. Just because DNNs are not good at this does not mean that something else won’t come out of left field, either from neurological research or pure AI research.

And as I have said before, the only way to ensure that human life continues as we know it is for AI to be banned. For all research and inquires to be made illegal. Some point out that this is difficult to do but like I said, there is no other way. I implore everyone who reads this to become involved in popular efforts to address the problem of AI.

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#69
post #64
post #8

Behind every successful neural network is a human brain. Neural networks are a tool, an advanced tool for sure, but still just a tool. If we are looking for AGI, and assuming the brain is an AGI, then there are still many differences to resolve. For example, back propagation has not been observed in nature. Nor has gradient descent. So the core mechanisms for learning in nature have still to reveal their secrets.

Behind every brain is a successful neural network. Or at least that's the promise of connectionism.

[deleted]

Re: Geoffrey Hinton and Demis Hassabis: AGI is nowhere close to being a reality

#70
post #8

Behind every successful neural network is a human brain. Neural networks are a tool, an advanced tool for sure, but still just a tool. If we are looking for AGI, and assuming the brain is an AGI, then there are still many differences to resolve. For example, back propagation has not been observed in nature. Nor has gradient descent. So the core mechanisms for learning in nature have still to reveal their secrets.

Behind every successful brain is a little strand of DNA and some environmental inputs. Somehow a brain might be more than the DNA however.

That's called an emergent property.
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