Thoughts on OpenAI, reinforcement learning, and killer robots • Hacker News Board

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

#51

Post by windmaple » Fri, Jul 28, 2017, 11:40 PM UTC

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.

'Very few examples of valuable applications to society or the economy.'

Not true. RL has been applied often in production system inside the bigger Internet companies. They are just not published.

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

#52

Post by jorgemf » Fri, Jul 28, 2017, 11:40 PM UTC

jorblumesea wrote: post #4

> Cracking AGI is a very long-term goal. Is this fair to say? I feel like advancements in the field happened far quicker than anyone expected, and every few years we are reevaluating timelines. Especially given the research happening in tandem that will almost certainly speed up AGI, like graphene, quantum computing, advanced GPU design... If you asked someone 10 years ago about the possibilities of ML/Deep learning…

My opinion is that it is a very long-term goal. Compare it to the autonomous car, getting the first 90% of a complete autonomous car is much easier than the last 10%. With AGI probably it is the same. Deep learning has got traction the last years, but we are almost using the same algorithms than 20 years ago, just in better hardware (plus some tweaks to make them work with bigger models). But I think we know almost nothing about how to achieve AGI. Just compare our deep learning models with the models we have from our brains, they are a subset of what we know about our brains. And I don't think we know a lot about our brains, but very little.

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

#53

Post by DrNuke » Fri, Jul 28, 2017, 11:42 PM UTC

As for the intellectual challenge, I really think Francois Chollet says it very well in his latest book: deep learning is a way to unpack, transpose, visualise and re-aggregate data fundamentals. We only need to master a bit of algebra and coding to make it happen on top of freeware wrappers like Keras and Anaconda, to say two. All the rest pertains to domain knowledge, ethics, politics and access to the hardware. Thanks Rachel and Jeremy for demystifying this field for the masses.

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

#54

Post by dclowd9901 » Fri, Jul 28, 2017, 11:42 PM UTC

jph00 wrote: post #10

jorblumesea wrote: post #4

> Cracking AGI is a very long-term goal. Is this fair to say? I feel like advancements in the field happened far quicker than anyone expected, and every few years we are reevaluating timelines. Especially given the research happening in tandem that will almost certainly speed up AGI, like graphene, quantum computing, advanced GPU design... If you asked someone 10 years ago about the possibilities of ML/Deep learning…

We don't make specific time predictions because it's just not possible. But we can make relative predictions. However long it takes to get to AGI, when we're (say) half way there, the amount of societal upheaval will be enormous. If we can't navigate that successfully, we'll never get to see AGI...

We'll figure it out. Those who stand to benefit the most from AGI will want to keep their vast fortunes and lobby governments to figure out ways to keep the common man happy. Not to have every dream fulfilled, but just happy enough to not uprise. It's kinda always worked that way.

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

#55

Post by udkl » Fri, Jul 28, 2017, 11:44 PM UTC

jph00 wrote: post #29

stale2002 wrote: post #27

Earlier quoted context omitted.

If self driving cars/trucks become a thing, and cause millions of people to be unemployed, there is ALSO a correspondingly massive economy increase. IE, the world is now massively richer because of all this awesome new technology. Yes, there could be some short term disruption, but honestly I think things will end up fine, just because of the massive amount of extra money and wealth that the world will have that coul…

That's not how things have generally worked out in the world. Billions live in abject poverty even although the world has plenty enough to feed them and provide shelter. The issue is income distribution - and just making more money doesn't magically fix the problem.

> just making more money doesn't magically fix the problem

Magically, no. With an effort yes. There are already experiments with basic pay for example.

Jeremy Rifkin books such as https://www.amazon.com/End-Work-Decline-Global-Post-Market/d... & 'Zero Marginal Cost' discuss the topic.

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

#56

Post by jacquesm » Fri, Jul 28, 2017, 11:45 PM UTC

_qbjt wrote: post #47

RodericDay wrote: post #30

Earlier quoted context omitted.

You're just awed by Musk and can't see how ridiculous what he's saying really is. François Chollet nailed it with the following comparison, mocking LHC alarmists: > It's not that turning on the LHC will create a black hole that will swallow the Earth. But it could! Albeit no physicist thought so. https://twitter.com/fchollet/status/891033876415397888

Accelerated particle colliders are not exactly equivalent to AI. It's not as if I can just build one in my garage. Anyone in the world, regardless of intent, can train a neural network to do what it wants. Extrapolate this decades down the road at the point that AI and its capabilities are much more sophisticated. Do you want to put money on the likelihood that it's all just going to go down smoothly? I don't even kn…

> 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.

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

#57

Post by maxander » Fri, Jul 28, 2017, 11:47 PM UTC

miguelrochefort wrote: post #37

Regarding "killer robots": If we can't make "paperclip maximization" the main goal of a some human, why do we expect to be able to make it the main goal of some AGI?

We don't have the luxury of designing humans from the ground up. Nor do we fully understand the structures underlying human motivation. Neither will be true (we expect) of AI, eventually.

It would be nice if there were some fundamental property of motivation that kept paperclip maximization from being an overriding goal of an intelligent entity, but we don't yet have particularly strong reasons to believe that this is the case.

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

#58

Post by philipkglass » Fri, Jul 28, 2017, 11:47 PM UTC

investments into addressing mass unemployment and wealth inequality (both of which are well-documented to cause political instability)

I don't really expect to see this solved in the USA before it's solved in poorer countries. In the USA there's a tension between pleasing the millions of surplus workers and pleasing the top billionaires that'll be minted when robots can replace millions of workers. It's cheaper for the billionaires to buy legislatures than to endure higher taxes or weakened IP rights.

By way of contrast, there are no local power brokers whose fortunes are built on intellectual property in Bolivia or Bangladesh. It'll be 99% upside for populist politicians to just ignore American IP concerns and freely "pirate" machines-that-do-work and machines-that-make-those-machines. The long term solution to machines-do-all-the-useful-work isn't to tax the profits and redistribute them to unemployed people for spending anyway. That's just an elaborate historical-theme-park imitation of a 20th century economy. "Machines make all clothing, then we tax those machines and redistribute money to the people so they can buy the clothing." The better solution is widespread copying of the maker-machines and the dramatic price deflation that follows on everything they can make.

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

#59

Post by dclowd9901 » Fri, Jul 28, 2017, 11:47 PM UTC

_qbjt wrote: post #28

> 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 problem or "die" along the way.

Come to think of it...

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

#60

Post by daly » Fri, Jul 28, 2017, 11:48 PM UTC

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% accuracy of identifying each ship using some Neural Net technology.

One day this net decides that an approaching warship is Chinese and sinks it. But it turns out to be a U.S. warship. Clearly a mistake was made. Deep investigation reveals that what the Neural Network "learned" happened to be related to the area of the ocean, based on sunlight details, rather than the shape of the warship or other features. Since the Chinese ships were photographed in Chinese waters, and the U.S. warship that was sunk was IN those waters at the moment, the Neural Net worked perfectly.

Recognition and action are only part of the intelligence problem. Analysis is also needed.