I've worked in a lot of AI-related projects and was around when the AI winter arrived. These various techniques that currently work by training, either supervised or self-training, can have fatal flaws. Take, for example, some high-tech camera technology. Use it on a drone to take pictures of warships from thousands of angles. You take pictures of U.S. warships, Russian warships, and Chinese warships. You achieve 100…
Thoughts on OpenAI, reinforcement learning, and killer robots
71–80 of 205 posts
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#72Another subtle point (one of many) involves transfer of knowledge. My most recent system "learned" by self-modification (similar in concept to growing new synapse connections but done by self-modifying code). This kind of modification will eventually arrive with Neural Nets as they move beyond simple 'dropout' techniques to more context-specific additions of specialized subnets and/or cooperating subnets (e.g. the room-recognizer adds a 'table'-specific subnet).
Assume two systems start out in a similar state. After interactions the systems are no longer identical and they gradually diverge over time (think twins). One is used in accounting and thinks of a 'table' as a kind of spreadsheet. Another is used in woodworking and thinks of a 'table' as a wooden object.
The implication is that one cannot just 'copy' what the first system knows to 'teach' the second system. There would have to be some sort of teaching mechanism (aka college) to transfer the information.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#73Earlier quoted context omitted.
> In fact, Chollet links a whole series of essays worth reading: Appeal to authority. You're not presenting any substantive rebuttals, just assuming it's not a concern because someone else with credentials said so. It's identical to alleging that I'm only worried because Elon Musk says so. > The frustrating thing is that people with insane amounts of resources and disposable income get swallowed up by these Basilisk-…
He wasn't talking about you, he was talking about Musk.
That's fair. Regardless of Musk's talking points, I'm still worried and I don't care how many people here think I'm paranoid. Engineers during the Industrial Revolution had no idea they were sowing the seeds of global warming [1]. We're putting a lot of money into AI under the assumption that it's all going to be a smooth ride. There's this notion that even if neural networks become more sophisticated than those of human brains, that AI will be completely subservient to us and we can just pull the plug whenever we want. If there's one thing humans are good at, it's self-destructive hubris.
[1] http://theconversation.com/the-industrial-revolution-kick-st...
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#74Earlier quoted context omitted.
> No, we don't. I haven't seen a computer that I couldn't power off yet, SF movies to the contrary. Ok. Turn off the computer systems that control Russia's nuclear weapons delivery systems. I'm waiting.
Now you're being (even more) silly. Obviously I can't turn that one off any more than I can turn off the refrigerator downstairs from where I'm sitting. But there are people there that can turn it off, and if I was physically present there then I could turn it off.
You're working under the assumption that no one will attempt to use AI to assert power over others, and that the human race will come together to pull the plug when it becomes a problem. Looking at our current geopolitical situation, I'd rather be silly than naive.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#75I've worked in a lot of AI-related projects and was around when the AI winter arrived. These various techniques that currently work by training, either supervised or self-training, can have fatal flaws. Take, for example, some high-tech camera technology. Use it on a drone to take pictures of warships from thousands of angles. You take pictures of U.S. warships, Russian warships, and Chinese warships. You achieve 100…
That's called 'data leakage'. http://machinelearningmastery.com/data-leakage-machine-learn...
Not quite. Another popular example is the cnn learning to distinguish wolves from non-wolves, because the wolf was always photographed on snow & the other animals not on snow. It just learnt to distinguish snow vs non-snow instead of wolf vs non-wolf. It then failed catastrophically when you put a non-wolf on snow.
There's no leakage in either case. The model is learning one thing and you think it's learning another.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#76"how existing gender and racial biases are being encoded in our algorithms" sounds like a great first problem to work on for those worried about super-intelligence, as it's basically a concrete instance of the value-alignment problem.
IMO, as long as you accept that human brains run on physical processes (no souls) and that computers continue to improve, super-intelligent AI is inevitable; but it's reasonable to think it's more like 150 years away than 10. Given the magnitude of the consequences here, it's still worth spending some resources to work on.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#77Earlier quoted context omitted.
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Typically if you start making crazy claims the onus is on you to present actual arguments.
Present an argument against what? All you have done is shot down my claims with some "life isn't science fiction" garbage. You haven't posted a single comment in this thread relevant to the future implications of AI. There's nothing thought provoking about your comments. You're just being dismissive.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#78Top people including DeepMind's CEO Demis Hassabis and Prof Stuart Russell, a AAAI and AAAS fellow who is a co-author of the AI textbook used at most of top universities, agree that AGI is definitely possible and going to happen. [1]
Hassabis also stated in another session that there are probably at least half a dozen mountains to climb before reaching AGI and he would be surprised if it takes more than 20. He also said that it has been easier to develop major advances than he thought. [2]
Considering that there has been about one major leap per year in neural networks architecture and systems for the past 3-4 years, and this includes training neural networks to do one-shot learning for physical robot control after practicing in a simulator, should we really be that complacent?
Even if the advances slow down to one per 2 years and it takes 12 of them to get to AGI, that's only 24 years. If the rate continues to be one per year, that's only 12 years.
[1] From the start of https://youtu.be/h0962biiZa4
[2] https://youtu.be/V0aXMTpZTfc
Note: Reinforcement Learning is far from the only component being researched at major labs, including DeepMind and OpenAI.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#79Earlier quoted context omitted.
Calling it an "Atari problem" sounds quite disparaging and misses the point. It's like calling a convolutional network doing the ImageNet task a "Doggy-detection" problem. That may be the original development problem, but the final product still helps detect cancer in CT scan images... Same goes for advances in reinforcement learning made on atari games.
Perhaps, but the jury is still very much out. The vast majority of RL applications are game playing. Very few examples of valuable applications to society or the economy. There's also plenty of evidence already that RL isn't really the right way to tackle the credit problem. E.g random search is only 10x slower.
Also used for robotics:
https://blog.openai.com/roboschool/
and other control problems: https://vmayoral.github.io/robots,/ai,/deep/learning,/rl,/re...
I think not so long ago supervised learning felt similarly 'toy', and now they are the state of the art model for machine translation and object detection. Just because they aren't useful today doesn't mean that they won't be useful.
Re: Thoughts on OpenAI, reinforcement learning, and killer robots
#80> It is hard for me to empathize with Musk’s fixation on evil super-intelligent AGI killer robots in a very distant future. I would argue this person has no business working with AI with this sort of myopic thinking. If you think "fake news" is a problem now, just wait until decentralized AI networks are able to tweet, publish articles and affect public discourse in a way that is indistinguishable from human influenc…
I agree. The best way to subjugate a machine and prevent it from breaking out of its bounds is to create an artificial "universe" in which it "exists" with arbitrary restrictions and forces, much like the speed of light, gravity and magnetism and have it work on problems using individual workers in a "lifecycle" in which they have their own motivations and "lives" that they live out until they either solve the proble…
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