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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

#91

Post by SilasX »

Natsu wrote: post #86
ktRolster wrote: post #78

Earlier quoted context omitted.

We already have true AI - it's a vast, thriving industry. Or how about calling that vast, thriving industry "weak AI," or "clever algorithms," which is what they really are. The original definition of AI was what we now call strong AI, but after some lesser problems were solved without actually creating strong AI, we had to come up with some name for those.

I want to see an AI that can improve itself by developing new algorithms for arbitrary tasks. I wonder how far off we are from that now?

You know, if you're at the point where you can give a human-readable spec of the problem and the AI can make a passable attempt at it, that's basically the Turing Test -- hence why I think it deserves its status as holy grail. Something that passes would really give the impression of "there's a ghost inside here".

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

#92

Post by ludamad »

Natsu wrote: post #86
ktRolster wrote: post #78

Earlier quoted context omitted.

We already have true AI - it's a vast, thriving industry. Or how about calling that vast, thriving industry "weak AI," or "clever algorithms," which is what they really are. The original definition of AI was what we now call strong AI, but after some lesser problems were solved without actually creating strong AI, we had to come up with some name for those.

I want to see an AI that can improve itself by developing new algorithms for arbitrary tasks. I wonder how far off we are from that now?

The problem is that fundamentally all our AI techniques are heavily data-driven. It's not clear what sort of data to feed in to represent good/bad algorithm design

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

#93

Post by gracenotes »

sytelus wrote: 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 learning 'effectiveness' is a bit apples-and-oranges. Their effect together is highly collaborative. Children have to develop abstractions on their own before you can supervise them on those abstractions. It is probably fair to say that a key part of human general intelligence is creating high-level representations of low-level stimuli. It might also be fair to say that this is what the brain is doing 100% of the time.

So if I may hand wave a little: while supervised learning can make a child better maximize objectives on those high-level representations (objectives they may be aware of through unsupervised observation), for the most part it does not fundamentally change the structure of those things in the child's brain. This makes unsupervised learning almost all of the cake to me.

My post has the caveat that children undergo a lot of other objective-based learning besides explicit instruction from adults, and all of this maps only fuzzily to supervised vs unsupervised learning in AI, which is the issue from the submitted post.

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

#94

Post by emmab »

drdeca wrote: post #63
emmab wrote: post #58

Earlier quoted context omitted.

We can describe Solomonoff-based agents like AIXI. None of them are fully sufficient for true general AI, but you could probably accomplish quite a bit with an AIXI-like agent.

I thought full AIXI wasn't computable though?

You can do time-bound AIXI and for a large enough time bound it's sufficient for all practical situations.

AIXI is not tractable, but I'm responding to the parent comment saying we don't even know what a cake is.

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

#95

Post by emmab »

sampo wrote: post #66
emmab wrote: post #58

Earlier quoted context omitted.

We can describe Solomonoff-based agents like AIXI. None of them are fully sufficient for true general AI, but you could probably accomplish quite a bit with an AIXI-like agent.

As fas as I know, the only thing existing AIXI implementations have demonstrated, is to learn to play Pac-man at a somewhat reasonable, but not in any way stellar level.

Yes, it is not tractable. It serves as an example of a definition of an agent though.

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

#96

Post by karmacondon »

sytelus wrote: 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…

I understand what you're saying and I agree with you. Human learning is based almost entirely around feedback and trial and error. But by comparison, machine learning requires a lot of implicitly labelled data, and that's what I think Yann LeCunn was talking about.

For example, to train a classifier to identify birds you need a large number of pictures of birds, maybe millions of varied examples. And then you'd need an equivalent number of images of things that aren't birds, or things that look similar to birds. Humans are able to make that same classification with a very small number of examples, maybe even n = 2. If someone saw a bird for the first time and then another one shortly after, they would be able to put the two together immediately and make a lot of inferences on top of that. Machine learning algorithms aren't even close to that yet.

Supervised learning sucks because it requires vast quantities of labelled and prepared data, which is expensive. Top ML researchers must feel like they're sitting in a Formula One racer but can't afford any gas for it. AlphaGo shows that a computer can do almost anything, but only with a significant investment of resources for each specific task. Unsupervised algorithms tend to be less effective than supervised methods right now, but once that changes it will open up a new world.

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

#97

Post by [deleted] »

sytelus wrote: 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…

[deleted]

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

#98

Post by jmickey »

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…

A while ago I helped develop iSpike - http://ispike.sourceforge.net/, which is an interface between the iCub robot (http://www.icub.org/) and a Spiking Neural Network simulator (We used SpikeStream - http://spikestream.sourceforge.net/)

The coolest part is that there exists a pretty complete simulator for the iCub robot that anyone who is interested can run on their computer - http://eris.liralab.it/wiki/Simulator_README

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

#99

Post by chrischen »

sytelus wrote: 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…

Err. A human is capable of unsupervised learning. Try locking two kids in a room for over decade. Maybe she didn't develop speech and social skills because there was no one to speak to or socialize with.

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

#100

Post by yoodenvranx »

gracenotes wrote: post #93
sytelus wrote: 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…

> there maybe only a few dozen instances of supervised adult instruction per day

There might be only a few dozen instances but I think each instance has a lasting effect which makes up for this.

If you scold a child for something stupid it did then it will remember this for a long-ish time. Same for teaching him things or correcting stuff.

I guess you show the child some correct behaviour at a few instances and this is then used internally as a guideline for selflearning.

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