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Thoughts on OpenAI, reinforcement learning, and killer robots

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Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#181

Post by k_lander »

maxander wrote: post #70

> ...but is it really the best use of resources to throw $1 billion at reinforcement learning without any similar investments into addressing... The precise same sentiment could be made about his plans to go to Mars- people are starving on Earth. But a Martian "backup civilization" might someday save humanity. Similarly, godlike AGI might be mere decades away and apocalyptically dangerous- predicting scientific advan…

> ...but is it really the best use of resources to throw $1 billion at reinforcement learning without any similar investments into addressing..

I didn't like this part. Elon Musk may be misguided about the immediate threat of AI but he is free to invest his money in whatever he thinks is important.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#182

Post by gbersac »

j2kun wrote: post #24
Yuioup wrote: post #11

Ok, so I consider myself an above-average programmer, capable of building a standard database driven web applications using the latest du-jour techniques. I suck at Math - I mean I _really_ suck at Math. I can visualize algorithms and data structures and have no problem whipping up programs. I have written a lot of code in my lifetime and have helmed a lot of successful projects as my capacity as lead programmer or a…

I'm working on a book for programmers who want to learn math. I can send you the first few chapters if you're interested, but I'm also interested to hear your thoughts about math in general.

If you are doing this, this is what I'd love : a book with theory and ton of exercises. My usual workflow is : I read theory, kind of understand something. Then first try one type of exercise that applied that theory. I don't understand a thing. Then I read the solution and I get it. I then need at least two if not more exercises more to play with that theory before I REALLY get it in my mind.

So please, add at least three exercises for each of the applications of each concepts explained in your book.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#183

Post by mostafab »

jph00 wrote: post #22
toisanji wrote: post #9

it sounds like people who don't work with machine learning asked that question. People who do work with machine learning should see the difference. Besides what is mentioned in the blog post, OpenAI is a research effort for moving start of the art, while fast.ai is for teaching students in a non math heavy way.

We also do research and try to move the state of the art. Although we share our results and methods largely through courses rather than academic papers. Our plan is to teach more material each year, in less time, with less prerequisites, by both curating the best practice techniques and adding our own. So far we've spent much more time on education than research since that's the highest leverage activity right now (h…

If you published your research in peer-reviewed venues, it would help your democratization ambitions. Few people can pay attention to original research that is buried into teaching material.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#184

Post by mostafab »

jph00 wrote: post #15
phreeza wrote: post #8

Earlier 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.

Maybe because RL research is not democratized enough to practionners. It is easier to study RL in a controlled environment like a video game (those 'elite researchers' are still not smart enough for real-world applications).

So you remark means that more education about RL is needed, and OpenAI, alongside other institutions like FastAI or Startcrowd, is helping for this effort.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#185

Post by mynameisvinn124 »

moravak1984 wrote: post #159
visarga wrote: post #101

Earlier quoted context omitted.

This problem is well studied - there are ways to make a neural net explain what parts of the input most influenced the decision. Another solution would be to use autoencoders or GANs to create a latent code from the input image. By construction, these codes need to carry the most important features about the input, because otherwise they couldn't reconstruct it. And regarding analysis - a lot of groups are attempting…

"This problem is well studied - there are ways to make a neural net explain what parts of the input most influenced the decision." Would you mind providing some reference here? I am interested and not familiar with any such way.

darpa recently launched a new program to do just that - force ML models to "explain" their predictions. it's called "explainable artificial intelligence" and the goal is to increase trust of autonomous systems.

[1] https://www.darpa.mil/program/explainable-artificial-intelli...

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#186

Post by lemming »

nopinsight wrote: post #91
tanilama wrote: post #85

Earlier quoted context omitted.

> Top people including DeepMind CEO Demis Hassabis and Prof Stuart Russell, a AAAI and AAAS fellow who is a co-author of the AI textbook most used at top universities, agree that AGI is definitely possible and going to happen. Even though they are high-profile people, in DL, since people still don't know a lot about it, their confidence means nothing. When I was in college, my professors/textbook alike, claimed that…

The point is whether we should be complacent and dismiss concerns just because we don't know when it will happen. Once someone builds it, stopping it might be very difficult. Here's why: https://youtu.be/4l7Is6vOAOA (less than 9 minutes and very clearly explained). Dismissing even a 10% chance of possible catastrophic risks is not what we practice in any other domains. Would you dismiss a concern over airplanes that…

To quote Bret Victor (from memory): worrying about general AI when climate change is happening is like standing on the train tracks in the station when the train is rushing in, worrying about being hit by lightning.

Work is being done on climate change, but at the current rate, we're way off preventing catastrophic effects. I'd say that our current level of effective effort basically amounts to ignoring the problem.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#187

Post by MacsHeadroom »

eli_gottlieb wrote: post #162
visarga wrote: post #101

Earlier quoted context omitted.

This problem is well studied - there are ways to make a neural net explain what parts of the input most influenced the decision. Another solution would be to use autoencoders or GANs to create a latent code from the input image. By construction, these codes need to carry the most important features about the input, because otherwise they couldn't reconstruct it. And regarding analysis - a lot of groups are attempting…

> This problem is well studied - there are ways to make a neural net explain what parts of the input most influenced the decision. That's a new area of research, actually.

New areas of research become "well studied" in a year or two in AI. GANs are considered both new and well studied, for example.

Machine Learning works on a different timescale from everything else.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#188

Post by Kurtz79 »

k_lander wrote: post #179
daly wrote: post #60

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…

in your example, was the neural net trained with examples of US ships in Chinese waters?

I assume it would have to be trained with existing material, which would mostly consist of US ships in US waters and Chinese ships in Chinese waters.

You are implying that the problem would have been in the set that was used as input, but my understanding is that in many a case you would realize that mistake when it's already too late.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#189

Post by jacquesm »

pure21r wrote: post #175
jacquesm wrote: post #56

Earlier quoted context omitted.

> The idea of replacing human life with AI isn't exactly controversial in the realm of futurism. It isn't in Science Fiction. But this is reality, and in this reality we do not have AGI and we have no idea of how far we are away from it. And even if and when it happens there is absolutely no guarantee that that will lead to the extinction of the human race and/or us ending up as slaves to the machine.

So what would be your equivalent position in the 1940s about the nuclear solution? "Don't worry about it, humanity has always prevented slow moving disasters."? Because the question is not about whether one should develop AI or not (this is going to happen in either case), but if we should be worried and work actively to minimize risk, as has been done on the nuclear case... So suppose you simulate 100 Earths from to…

You can worry as much as you want. And I'm free not to worry as much as you want.

Re: Thoughts on OpenAI, reinforcement learning, and killer robots

#190

Post by nopinsight »

lemming wrote: post #186
nopinsight wrote: post #91

Earlier quoted context omitted.

The point is whether we should be complacent and dismiss concerns just because we don't know when it will happen. Once someone builds it, stopping it might be very difficult. Here's why: https://youtu.be/4l7Is6vOAOA (less than 9 minutes and very clearly explained). Dismissing even a 10% chance of possible catastrophic risks is not what we practice in any other domains. Would you dismiss a concern over airplanes that…

To quote Bret Victor (from memory): worrying about general AI when climate change is happening is like standing on the train tracks in the station when the train is rushing in, worrying about being hit by lightning. Work is being done on climate change, but at the current rate, we're way off preventing catastrophic effects. I'd say that our current level of effective effort basically amounts to ignoring the problem.

Au contraire, climate change will not pose an existential risk within the next 30 years. The chance of that happening is pretty much nil and no one serious argues otherwise. Even in 100 years, there could be much suffering and dislocations, but it still most likely won't be an existential risk to all of humanity.

There is a non-negligible possibility that AGI will be invented in 30 years. Many AI experts agree on that. A number of experts also believe that its invention could be highly beneficial or catastrophic, depending on its form and our preparation.

With cost-benefit analysis based on the best knowledge we have weighed by probabilities, it is clear that AGI risks are more substantial and worth at least as much investment as climate change. The current funding for AI Safety Research is not even 1/10th, perhaps less than 1/100th, of climate change funding. Inaction is also an action.

If you do not trust intelligent domain experts, and also intelligent non-experts with almost no conflict of interests like Bill Gates and Stephen Hawking, then please let us know which source(s) of knowledge we should rely on instead.

Note: I believe we should fund both. A certain but slow train wreck and an uncertain but even more catastrophic and possibly speedier train wreck are both worth preventing.

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