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Yann LeCun's comment on AlphaGo and true AI

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Re: Yann LeCun's comment on AlphaGo and true AI

#31

Post by emcq »

hacknat wrote: post #5

I think we need more advances in neuroscience and, I know this will be controversial, psychology before we really know what the cake even is. Edit: I actually think the major AI breakthrough will come from either of those two fields, not computer science.

I disagree. In engineering we've shown great advancements not by exactly reproducing biology from cases like transportation (wheel vs legs) or flight (engine and wing vs flapping feathers). We can't even mass produce synthetic muscles and instead use a geared motor.

The growth in building increasingly sophisticated AI is faster than our efforts to reverse engineer biology. I could see that changing with improved observational techniques like optogenetics or bacteria and viruses we can "program" to explore.

Researchers are already focusing on concrete insights from cognitive science, neuroscience, etc such as one shot learning or memory that we haven't yet figured out in a cohesive machine learning framework. For the time being I'd bet on more advaces coming without significant changes in biological understanding.

Re: Yann LeCun's comment on AlphaGo and true AI

#32

Post by megaman821 »

It seems to me one of the higher hurdles for creating a general purpose intelligence, is human empathy. Without it you are left with creating a nearly infinite-length rules engine.

When you ask your AI maid to vacuum your house, you would prefer it not to plow through closet door to grab the vacuum, rip your battery out of your car and hardwire to the vacuum, and then proceed to clean your carpets. If you don't want to create a list of rules for every conceivable situation, the AI will need to have some understanding human emotions and desires.

Re: Yann LeCun's comment on AlphaGo and true AI

#33

Post by argonaut »

jacquesm wrote: post #27
argonaut wrote: post #20

Earlier quoted context omitted.

They were taken from neuroscience... 50 years ago. Since then, very few ideas have been explicitly taken from neuroscience.

That's like saying there has been no development in automobiles since 1890. Sure, at first glance the cars from then are still like the cars from now. ICE (or electrical) power source, maybe a gearbox, some seats, a steering wheel and something to keep you out of the weather. But that's at the same time ignoring many years of work on those concepts in order to further refine them. The neural networks that were taken…

This analogy doesn't make any sense. Since automobiles were never patterned off anything in biology (they were the improvement of horse drawn carriages), I'm not sure what point you're trying to make with the analogy.

I never said there weren't any developments in neural nets, I'm just saying that few ideas have been taken from neuroscience (there certainly have been some ideas, like convolutions). In fact most things (including most tricks in convolutional neural nets in their current state) a neural net does, we know a brain does not do.

Re: Yann LeCun's comment on AlphaGo and true AI

#34

Post by argonaut »

modeless wrote: post #21
javajosh wrote: post #14

Is anyone working on an embodied AI? Even a simulated body might help. Ultimately intelligence is only useful insofar as it guides the body's motion. We often tend to minimize the physical act of say, writing down a theorem or actually applying paint to the canvas, but there are certain actions like playing a musical instrument that certainly blur the distinction between "physical" and "mental". Indeed, even 'purely…

Yes http://googleresearch.blogspot.com/2016/03/deep-learning-for...

I wouldn't go as far as calling that emodied AI, since the only percept is a camera.

Re: Yann LeCun's comment on AlphaGo and true AI

#35

Post by typon »

hacknat wrote: post #5

I think we need more advances in neuroscience and, I know this will be controversial, psychology before we really know what the cake even is. Edit: I actually think the major AI breakthrough will come from either of those two fields, not computer science.

I disagree. I think we need advances in philosophy to truly answer these questions in depth.

Re: Yann LeCun's comment on AlphaGo and true AI

#36

Post by pavanky »

Can someone more knowledgeable explain why biological systems are considered unsupervised instead of reinforcement based systems?

While it seems intuitive that most individual "intelligent" systems in animals can be seen as unsupervised, isn't life itself driven in a reinforced manner?

Re: Yann LeCun's comment on AlphaGo and true AI

#38

Post by spurcell93 »

megaman821 wrote: post #32

It seems to me one of the higher hurdles for creating a general purpose intelligence, is human empathy. Without it you are left with creating a nearly infinite-length rules engine. When you ask your AI maid to vacuum your house, you would prefer it not to plow through closet door to grab the vacuum, rip your battery out of your car and hardwire to the vacuum, and then proceed to clean your carpets. If you don't want…

If you haven't read them yet, I would suggest Isaac Asimov's Robot series, which discusses the implications of hardware-level 'laws' to which robots must abide. His take was that these laws would constrain behavior according to human judgments of harm and benefit. I wonder if there is another way of looking at it, one where AI action is not only constrained by human sensibility, but informed by it.

Re: Yann LeCun's comment on AlphaGo and true AI

#40

Post by sound_of_basker »

_snydly wrote: post #39

I have Facebook blocked for the next week (because, you know, productivity). Can someone post LeCun's comment here?

Statement from a Slashdot post about the AlphaGo victory: "We know now that we don't need any big new breakthroughs to get to true AI" That is completely, utterly, ridiculously wrong. As I've said in previous statements: most of human and animal learning is unsupervised learning. If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We know how to make the icing and the cherry, but we don't know how to make the cake. We need to solve the unsupervised learning problem before we can even think of getting to true AI. And that's just an obstacle we know about. What about all the ones we don't know about?
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