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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

#121

> As I've said in previous statements: most of human and animal learning is unsupervised learning. I don't think that's true. When baby is learning to use muscles of its hands to wave them around there's no teacher to tell it what should its goal be. But physics and pain teaches it fairly efficiently which moves are bad idea. It has built in face detection engine and the orienting and attempting to move and reach tow…

The difference between supervised and unsupervised is that the inputs are paired with known outputs for supervised. In unsupervised the agent has (initially) no knowledge of what the outputs will be, given the inputs.

The baby does not know (initially) that something will cause pain, or the extremities of its joints. It must learn this over time and experience. The baby must also learn how to use the built in components, as it has no idea what outputs will occur given the inputs.

As you allude to, there are built in mechanisms/configurations in the brain which provide various forms of feedback, as well as built in behaviours and responses. If there was no basic structure to the brain, I think it would be almost impossible for an unsupervised agent to develop and learn to the complexity and level of a human brain. These basic behaviours significantly speed the initial development process up.

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

#122
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.

That's an equivalent of saying that advancements in airplanes will come from biology rather than engineering fields. Biology at best can give hints to improve aerodynamics, and it still can be solved mathematically better. Same will be with neuroscience.

I believe it's more likely that engineering of AI will bring new ideas to neuroscience instead, just like after building helicopters we gained some intuition and understanding on why certain features of dragonflies exist.

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

#123
post #106

Ah, the joys of arguing about artificial intelligence without ever defining intelligence. It is the perfect argument, everyone can forcefully make their points forever, and we'll be none the wiser whether this AI is 'true AI' or not.

So then the discussion is all about defining intelligence, beginning with a fuzzy conception of required qualities. It literally means ability to select, read, choose between. The discussion can be a means to judge the AIs or, for the sake of the argument, to judge and improve intelligence with AI as a heavily simplified model, which is an old hat by now. Do you think that's irrational? Do you expect neuroscience or…

I remember similar arguments in the early 90s when I was doing my PhD. They got about as far then. The same arguments will be happening in another 25 years. And beyond, even when a computer is super-human in every conceivable way, there'll be arguments over whether it is 'real AI'. And nobody will define their terms then either. Ultimately the discussion will be as irrelevant then as it is now, and, then as now, it will be mostly take place between well-meaning undergrads, and non-specialist pundits.

(Philosophers of science have a discussion that sounds similar, to someone just perusing the literature to bolster their position, but the discussion is rather different though also not particularly relevant, in my experience.)

> What do you know about it (honest question)?

About recurrent NNs? Not much beyond the overview kind of level. My research was in evolutionary computation, though I did some work on evolving NN topologies, and using ecological models to guide unsupervised learning.

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

#124
post #56

Preface: AlphaGo is an amazing achievement and does show an interesting advancement in the field. Yet ... it really doesn't mean almost anything that people are predicting it to mean. Slashdot went so far as to say that "We know now that we don't need any big new breakthroughs to get to true AI". The field of ML/AI is in a fight where people want more science fiction than scientific reality. Science fiction is sexy,…

I took a closer read through the AlphaGo paper today. There are some other features that make it not general. In particular, the initial input to the neural networks is a 19×19×48 grid, and the layers of this grid include information like: - How many turns since a move was played - Number of liberties (empty adjacent points) - How many opponent stones would be captured - How many of own stones would be captured - Num…

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

#125
post #87

If you look at how child learns, it's huge amount of supervised learning. Parents spend lots of time in do and don't and giving specific instructions on everything from how to use toilet to how to construct a correct sentence. Lots of language development, object identification, pattern matching, comprehension, math skills, motor skills, developing logic - these activities has huge amount of supervised training that…

As a parent, I have quite an opposite experience to your claims.

> Parents spend lots of time in do and don't and giving specific instructions on everything from how to use toilet to how to construct a correct sentence.

What you're missing is that the child is initially a blank page. He has no knowledge of language either, so giving instructions to somebody that doesn't understand your language is challenging, to say the least. And acquiring language is something they do just by listening and observing others, in a very cool game of trial and error. At some point a child starts mimicking what the parent does, repeating words or gestures and then notices the triggered response.

They learn best by observing what you do and not by what you say. They also learn by discomfort. I taught my boy to use the chamber pot, not by language, but by letting him without diapers and letting him pee on himself, until he got the hint that he should use the chamber pot :-)

And of course, you might classify this as "supervised learning", but these are just shortcuts. Because of our ability to communicate in speech and writing, we learn from the acquired knowledge of our ancestors. Isolate a couple of toddlers from the world and you'll eventually see that they'll invent their own language and they'll learn by themselves to not shit were they eat or sleep.

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

#126
post #87

If you look at how child learns, it's huge amount of supervised learning. Parents spend lots of time in do and don't and giving specific instructions on everything from how to use toilet to how to construct a correct sentence. Lots of language development, object identification, pattern matching, comprehension, math skills, motor skills, developing logic - these activities has huge amount of supervised training that…

Interesting. I have heard the opposite of this. Supervised learning may be how it looks from the outside, but consider that out of the >6,570,0000 waking seconds of a child's life up to age 5, there maybe only a few dozen instances of supervised adult instruction per day. Besides those, what do neurons do the remaining 99.99% of the time? Part of the problem might be that comparing supervised and unsupervised learnin…

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

#127
Stop looking at the red dot. Take a step back and look around you. "True" AI is here and it's been here for some time. You're communicating with it right now.

It's just that we find it so hard to comprehend it's form of "intelligence", because we're expecting true AI to be a super-smart super-rational humanoid being from sci-fi novels.

But what would a super-smart super rational being worth 1 billion minds look/feel like to one human being ? How would you communicate with it ?

Many people childishly believe that "we" have control over "it". You don't. We don't.

The more we get used to it being inside our minds, the harder it becomes to shut it down without provoking total chaos in our society. Even with the chaos, there is no one person (or group) who can shut it down.

But "we" make the machines ! Well... yes, a little bit..

Would we be able to build this advanced hardware without computers ? Doesn't this look like machines reproducing themselves with a little bit of help from "us" ?

Think about the human beings from the Internet's perspective - what are we for it ? Nodes in a graph. In brain terms - we are neurons, while "it" is the brain.

But it's not self-aware ! What does that even mean ?

Finally, consider that AlphaGo would have been impossible without the Internet and the hardware of today.

And that "true" AI that everybody expects somewhere on the horizon will also be impossible without the technology that we have today.

If so, then what we have right now is the incipient version of what we'll have tomorrow - that "true" AI won't come out of thin air, it will evolve out of what we have right now.

Just another way of saying the same thing - it's here.

Is this good or bad ? Well, that's a totally different discussion.

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

#128

Stop looking at the red dot. Take a step back and look around you. "True" AI is here and it's been here for some time. You're communicating with it right now. It's just that we find it so hard to comprehend it's form of "intelligence", because we're expecting true AI to be a super-smart super-rational humanoid being from sci-fi novels. But what would a super-smart super rational being worth 1 billion minds look/feel…

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