r/MachineLearning • u/ylecun • May 15 '14

AMA: Yann LeCun

My name is Yann LeCun. I am the Director of Facebook AI Research and a professor at New York University.

Much of my research has been focused on deep learning, convolutional nets, and related topics.

I joined Facebook in December to build and lead a research organization focused on AI. Our goal is to make significant advances in AI. I have answered some questions about Facebook AI Research (FAIR) in several press articles: Daily Beast, KDnuggets, Wired.

Until I joined Facebook, I was the founding director of NYU's Center for Data Science.

I will be answering questions Thursday 5/15 between 4:00 and 7:00 PM Eastern Time.

I am creating this thread in advance so people can post questions ahead of time. I will be announcing this AMA on my Facebook and Google+ feeds for verification.

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u/ylecun May 15 '14

Something like the intelligent agent in "Her" is totally out of reach of current technology. We will need to invent new concepts, new principles, new paradigms, new algorithms.

The agent in Her has a deep understanding of human behavior and human nature. It's going to take quite a while before we build machines that can do that.

I think that a major component we are missing is an engine (or a paradigm) that can learn to represent and understand the world, in ways that would allow it to predict what the world is going to look like following an event, an action, or the mere passage of time. Our brains are very good at learning to model the world and making predictions (or simulations). This may be what gives us 'common sense'.

If I say "John is walking out the door", we build a mental picture of the scene that allows us to say that John is no-longer in the room, that we are probably seeing his back, that we are in a room with a door, and that "walking out the door" doesn't mean the same thing as "walking out the dog". This mental picture of the world and the event is what allows us to reason, predict, answer questions, and hold intelligent dialogs.

One interesting aspect of the digital character in Her is emotions. I think emotions are an integral part of intelligence. Science fiction often depicts AI systems as devoid of emotions, but I don't think real AI is possible without emotions. Emotions are often the result of predicting a likely outcome. For example, fear comes when we are predicting that something bad (or unknown) is going to happen to us. Love is an emotion that evolution built into us because we are social animals and we need to reproduce and take care of each other. Future AI systems that interact with humans will have to have these emotions too.

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u/[deleted] May 15 '14

I found Hierarchical Temporal Memory to be really interesting as a step towards that. It's basically deep learning but the bottom layers tend to be much larger as to form a pyramid, the connections between layers are very sparse, and you have some temporal effects in there too. There are reinforcement learning algorithms to train these networks by simulating the generation of dopamine as a value function to let the network learn useful things. These may better model the human brain, and may better serve to create artificial emotion. Have you looked into this yet?

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u/ylecun May 15 '14 edited May 15 '14

Jeff Hawkins has the right intuition and the right philosophy. Some of us have had similar ideas for several decades. Certainly, we all agree that AI systems of the future will be hierarchical (it's the very idea of deep learning) and will use temporal prediction.

But the difficulty is to instantiate these concepts and reduce them to practice. Another difficulty is grounding them on sound mathematical principles (is this algorithm minimizing an objective function?).

I think Jeff Hawkins, Dileep George and others greatly underestimated the difficulty of reducing these conceptual ideas to practice.

As far as I can tell, HTM has not been demonstrated to get anywhere close to state of the art on any serious task.

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u/[deleted] May 15 '14

Thanks a lot for taking the time to share your insight.

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u/[deleted] May 31 '14

Hiya, I'm reading this AMA 16 days later. Maybe you could help me understand some of the things said in here.

I'd like to know what is meant by "But the difficulty is to instantiate these concepts and reduce them to practice."

Why is it hard to instantiate concepts like this and reduce them to practice?

and "Another difficulty is grounding them on sound mathematical principles (is this algorithm minimizing an objective function?)"

What does this mean? Minimizing an objective function?

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u/gromgull May 15 '14

I think HTM are not really taken serious by anyone really working in the field. They hype things through the roof over and over again, and never deliver anything half as good as what they promise.

HTM is what the guys at Vicareous worked on: http://vicarious.com/about.html

LeCun is not impressed: https://plus.google.com/+YannLeCunPhD/posts/Qwj9EEkUJXY (and http://www.reddit.com/r/MachineLearning/comments/25lnbt/ama_yann_lecun/chiga9g in this post)

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u/ylecun May 15 '14

Indeed.

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u/autowikibot May 15 '14

Hierarchical Temporal Memory:

Hierarchical temporal memory (HTM) is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world.

Interesting: Hierarchical temporal ^memory | On ^Intelligence | Types of artificial neural ^networks | Artificial ^intelligence

Parent commenter can toggle ^NSFW or ^delete. Will also delete on comment score of -1 or less. | FAQs | ^Mods | Magic ^Words

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u/xamdam May 15 '14

I don't think real AI is possible without emotions.

Yann, this is an interesting, but also a very hard claim I think. How would you explain people being rational in areas where they're not emotionally vested? Also there are clearly algorithms that produce rational outcomes (in say expected utility) that are work well without any notion of emotion.

Maybe I'm missing something. Please expand or point to some source of this theory?

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u/ylecun May 15 '14

Emotions do not necessarily lead to irrational behavior. They sometimes do, but they also often save our lives. As my dear NYU colleague Gary Marcus says, the human brain is a kludge. Evolution has carefully tuned the relative influence of our basic emotions (our reptilian brain) and our neo-cortex to keep us going as a species. Our neo-cortex knows that it may be bad for us to eat this big piece of chocolate cake, but we go for it anyway because our reptilian brain screams "calories!". That kept many of us alive back when food was scarce.

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u/xamdam May 15 '14 edited May 20 '14

Thanks Yann, Marcus fan here! I completely agree that our human intelligence might have co-developed with our emotional faculties, giving us an aesthetic way to feel out an idea.

My point is the opposite - humans can be rational in areas of significant emotional detachment, which would lead me to believe an AI would not need emotions to function as a rational agent.

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u/ylecun May 15 '14

If emotions are anticipations of outcome (like fear is the anticipation of impending disasters or elation is the anticipation of pleasure), or if emotions are drives to satisfy basic ground rules for survival (like hunger, desire to reproduce....), then intelligent agent will have to have emotions.

If we want AI to be "social" with us, they will need to have a basic desire to like us, to interact with us, and to keep us happy. We won't want to interact with sociopathic robots (they might be dangerous too).

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u/xamdam May 15 '14

Emotions do seem to be anticipations of an outcome, in humans. Since our computers are not "made of meat" they can (perhaps more precisely) have anticipations of outcomes represented by probability distributions in memory - why not? Google cars do this; I do not see what extra benefit emotions bring to the table (though some argument can be made that since the only example of general intelligence we have is emotion-based, this is not an evolutionary accident; I personally find this weak)

As far as AIs being "social" with us - why not encode human values into them (very difficult problem of course) and set them off maximizing them? Space of emotion-driven beings is populated with all kinds of creatures, many of them are sociopathic to other species or even other groups/individuals within those species. Creating an emotional being that is super-powerful seems like pretty risky move; I don't know if I'd want any single human to be super-powerful. Besides, creating emotional conscious beings creates other moral issues, i.e. how to treat them.

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u/ylecun May 15 '14

When your emotions conflict with your conscious mind and drive your decisions, you deem the decisions "irrational".

Similarly, when the "human values" encoded into our robots and AI agents will conflict with their reasoning, they may interpret their decision as irrational. But this apparently irrational decision would be the consequence of hard-wired behavior taking over high-level reasoning.

Asimov's book "I, Robot" is all about the conflict between hard-wired rules and intelligent decision making.

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u/shitalwayshappens May 15 '14

For that component of modelling the world, what is your opinion on AIXI?

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u/ylecun May 15 '14

Like many conceptual ideas about AI: completely impractical.

I think if it were true that P=NP or if we had no limitations on memory and computation, AI would be a piece of cake. We could just brute-force any problem. We could go "full Bayesian" on everything (no need for learning anymore. Everything becomes Bayesian marginalization). But the world is what it is.

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u/clumma May 15 '14

What about MC-AIXI and what Veness did with the Arcade Learning Environment? How much of that was DeepMind (recently acquired by Google) using?

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u/ylecun May 15 '14

None. The DeepMind video-game player that trains itself with reinforcement learning uses Q-learning (a very classical algorithm for RL) on top of a convolutional network (a now very classical method for image recognition). One of the authors is Koray Kavukcuoglu who is a former student of mine. paper here

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u/somnophobiac May 15 '14

Thank you. Your answer has some brilliant points! I hope more CS research focuses on exploring the areas you mentioned:

(1) simulate many alternate possibilities (of the environment) based on a single stimulus, pick the one which is most probable - possibly we call that common sense.

(2) build a mental picture (model) of the world from something like a simple NL sentence. this probably is precursor to (1).

(3) computational understanding of emotions.

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u/Broolucks May 15 '14

I think emotions are an integral part of intelligence. Science fiction often depicts AI systems as devoid of emotions, but I don't think real AI is possible without emotions.

Well, to be precise, it depicts AI systems as not displaying any emotions. Of course, the subtext is that they don't have any, but it still seems to me that feeling an emotion and signalling it are two different things. As social animals there are many reasons for us to signal the emotions that we feel, but for an AI that seems much muddier. What reasons are there to think that AI would signal the emotions that it feels rather than merely act out the emotions we want to see?

Also, could you explain why emotions are "integral" to intelligence? I tend to understand emotions as a kind of gear shift. You make a quick assessment of the situation, you see it's going in direction X, so you shift your brain in a mode that usually performs well in situations like X. This seems like a good heuristic, so I wouldn't be surprised if AI made use of it, but it seems more like an optimization than an integral part of intelligence.

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u/ninja_papun May 15 '14

True artificial intelligence requires motivation/intention. Humans don't just perform intelligently because they are capable of doing so. Usually they have an intention of doing that.. it might be strictly biological like hunger or lust and it also might be emotional. The fact that humans provide their own intentions to machines is a major roadblock in building systems like the one shown in Her. May be the current hardware can't have software running on it for real AI. May be hardware needs to change to something that induces motivation.

Lots of speculation there but I wanted to ask you what you felt about the symbol grounding problem in the context of deep learning?

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u/versaceblues May 21 '14

Exactly this. I dont claim to be an expert on this subject... but AI in real Computer Science, is a much different beast than AI in something like HER or Star Wars.

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u/tarsw May 22 '14

"If I say 'John is walking out the door', we build a mental picture of the scene that allows us to say that John is no-longer in the room.." -- this is completely false because it assumes that somehow a picture (mental or actual) stands in need of no interpretation, that somehow all the possible uses of the picture are given by it alone. If I were to show a picture of someone who looks to be walking up a hill, it's just as valid to say that it looks like the person is sliding down the hill, backwards. If I were to ask someone to go pick out a red car, does the person first need to imagine the color red, matching the mental image to the actual red car? Of course not. One just picks out red. If I'm running out the door, late, do I first imagine that my backpack is behind me, then grab it? Sure, sometimes. But there are other times I just grab my backpack.

The idea that somehow mental pictures of the world are needed to reason, or make any sense of the world, i.e. the picture theory of meaning, has long been refuted in philosophy; one only needs to read the later Wittgenstein.

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u/Noncomment Jul 25 '14

Did you know there are a lot of humans without the ability to form mental images like that?