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Why Robot Brains Need Symbols

nautil.us

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Re: Why Robot Brains Need Symbols

#51

Post by mindgam3 »

laichzeit0 wrote: post #12

I really don't get Gary Marcus' fundamental problem. He ends the essay with "All I am saying is to give Ps (and Qs) a chance.". But who exactly is this aimed at? Surely no one is being held academically ransom to Deep Learning. If Ps (and Qs) is a better approach then do the research and publish the results. Instead he just seems to whine about it on Twitter all day and attack people who are actually "doing the resea…

As stated in the article, Marcus' fundamental problem is:

1) "the notion that deep learning is without demonstrable limits and might, all by itself, get us to general intelligence, if we just give it a little more time and a little more data, as captured in a 2016 suggestion by Andrew Ng"

and

2) "Leaders in AI like LeCun acknowledge that there must be some limits, in some vague way, but rarely (and this is why Bengio’s new report was so noteworthy) do they pinpoint what those limits are, beyond to acknowledge its data-hungry nature."

Re: Why Robot Brains Need Symbols

#52

Post by mindgam3 »

Robot brains need symbols because the rhetoric around deep learning is getting out control. In the video analysis below of the latest AlphaZero vs Stockfish paper, AlphaZero is described as "DeepMind's general-purpose artificial intelligence system".

Let's give credit where it's due. AlphaZero is an impressive algorithm with results in 3 different types of perfect-information games: chess, go, shogi. But to describe it as "general purpose AI" is simply absurd. Yes, this isn't an official Deep Mind video, but this is the kind of rhetoric they are putting it out there.

I'm open to the possibility that deep learning might one day solve some of its core problems (like the elementary schoolbus-snowplow errors described in the source article) and turn into a general purpose AI. But we aren't there yet, and we're not even close.

https://www.youtube.com/watch?time_continue=13&v=2-wFUdvKTVQ

Re: Why Robot Brains Need Symbols

#53

Post by timkam »

d--b wrote: post #43

My case against hardcoding some kind of symbolic logic within the architecture of an AI model is that there won't be a way to challenge the symbols as the brain does. When I think "the house is red", I know what it means very well, but I'm also able to doubt or modulate my understanding of the symbols. These conversations would be hard to put in symbols: - This house is red - No! It's crimson! - But crimson is red! O…

There is a small CS/AI community that works on "argumentation", putting exactly the problems you describe in symbols. For anyone who is interested in the details, there are several books on the topic, for example the "Handbook of Formal Argumentation" by Baroni et al. I concede that formal argumentation is--as far as I know--still waiting to be applied in large-scale scenarios.

Re: Why Robot Brains Need Symbols

#54

Post by soVeryTired »

mindgam3 wrote: post #52

Robot brains need symbols because the rhetoric around deep learning is getting out control. In the video analysis below of the latest AlphaZero vs Stockfish paper, AlphaZero is described as "DeepMind's general-purpose artificial intelligence system". Let's give credit where it's due. AlphaZero is an impressive algorithm with results in 3 different types of perfect-information games: chess, go, shogi. But to describe…

I think there's some ambiguity there regarding what is general-purpose: if you want to be charitable, you might interpret the description as saying it's a general-purpose system rather than a general-purpose AI.

Who knows what they really meant though...

Re: Why Robot Brains Need Symbols

#55

Post by polkapolka »

giardini wrote: post #47
polkapolka wrote: post #27

Symbolic AI is machine programming. Connectionist AI is machine learning. Machine programming simply does not scale. It is also not biologically plausible: it is not as if God put symbols into our brain, these formed, are prefaced by, and were learned from neural activity. Just try to solve the spam problem using symbolic AI. It will keep you busy (and paid) for a long time, while yielding subpar results. Deep learni…

polkapolka says> "Machine programming simply does not scale....Just try to solve the spam problem using symbolic AI. It will keep you busy (and paid) for a long time, while yielding subpar results." 1. We can scale "machine programming" by making computers faster and more complex, 2. The spam problem can be solved with Bayesian methods (which I consider to be part of "machine programming"): a connectionist solution i…

Faster and more complex computers does not make you faster at manual programming. Computer vision had this before the DL boom: engineers painfully crafting feature extractors. It went nowhere.

Bayesian models underperform to DL by a wide margin (though it is a step up from handwritten rules: if DEAR FRIEND then Spam score++.

Re: Why Robot Brains Need Symbols

#56

Post by mindgam3 »

soVeryTired wrote: post #54
mindgam3 wrote: post #52

Robot brains need symbols because the rhetoric around deep learning is getting out control. In the video analysis below of the latest AlphaZero vs Stockfish paper, AlphaZero is described as "DeepMind's general-purpose artificial intelligence system". Let's give credit where it's due. AlphaZero is an impressive algorithm with results in 3 different types of perfect-information games: chess, go, shogi. But to describe…

I think there's some ambiguity there regarding what is general-purpose: if you want to be charitable, you might interpret the description as saying it's a general-purpose system rather than a general-purpose AI. Who knows what they really meant though...

My point is, calling a system that learned how to play 3 types of board games "general purpose" in any sense is a bit of a stretch. At best this is a "general purpose games-playing" system.

Re: Why Robot Brains Need Symbols

#57

Post by FakeComments »

mindgam3 wrote: post #50
FakeComments wrote: post #19

Earlier quoted context omitted.

I don’t think we’re able to show our workings for higher level things like proofs. For instance, I can’t tell you (accurately) how I composed the proof conceptually, ie what strategy it takes, or even determined the appropriate steps, ie how I determined to use a particular tactic. I can tell you the premises lead to the conclusion via a chain of reasoning, but that’s the artifact of my thought process, not anything…

"I don’t think we’re able to show our workings for higher level things like proofs." I can't speak for proofs, but this is false in the case of higher level things like chess. I'm not a grandmaster, but I was a chess master at age 10 and I am ranked ~2400 in bullet chess. To the average person my ability to play chess is "magic". But to me it's not magic at all. I can explain my thought process at any time. It's all…

There’s chess theory, which is rule based and what you start off describing.

But then you admit you don’t work directly with chess theory when selecting moves, there’s a trained black box evaluator that selects candidate moves, which you then select from via chess theory.

That’s how you’re finding chess moves in the blink of an eye: you run a fuzzy approximation, then refine the results using higher level reasoning. But you don’t have access to the network doing the evaluation and can’t describe exactly how it operates, just that it was trained on chess theory.

It’s that fuzzy reasoning to speed up the process of actually finding solutions that I was calling out as the source of the unknowns in our processing — and at least from my exposure to board games (and their players), it’s often the source of things like innovative moves.

Re: Why Robot Brains Need Symbols

#58

Post by polkapolka »

hopler wrote: post #46
polkapolka wrote: post #27

Symbolic AI is machine programming. Connectionist AI is machine learning. Machine programming simply does not scale. It is also not biologically plausible: it is not as if God put symbols into our brain, these formed, are prefaced by, and were learned from neural activity. Just try to solve the spam problem using symbolic AI. It will keep you busy (and paid) for a long time, while yielding subpar results. Deep learni…

Why do you think human-style learning can scale? Human brains are terrible at basic arithmetic like raising 3 to the 6th power.

Statistical learning with connectionist architectures is driving current AI at scale.

To me, this paradigm is also the most promising: learn from data bottom-up, not from experts top-down.

Re: Why Robot Brains Need Symbols

#59

Post by gnode »

mindgam3 wrote: post #50
FakeComments wrote: post #19

Earlier quoted context omitted.

I don’t think we’re able to show our workings for higher level things like proofs. For instance, I can’t tell you (accurately) how I composed the proof conceptually, ie what strategy it takes, or even determined the appropriate steps, ie how I determined to use a particular tactic. I can tell you the premises lead to the conclusion via a chain of reasoning, but that’s the artifact of my thought process, not anything…

"I don’t think we’re able to show our workings for higher level things like proofs." I can't speak for proofs, but this is false in the case of higher level things like chess. I'm not a grandmaster, but I was a chess master at age 10 and I am ranked ~2400 in bullet chess. To the average person my ability to play chess is "magic". But to me it's not magic at all. I can explain my thought process at any time. It's all…

I don't think this refutes the argument. You've just explained that the process by which you play chess is by calculation. In essence, you're doing something you could program a machine to do (without any learning component).

The question is: how do you explain how you have an original idea, or learn something you previously had no conceptualisation of.

I think chess is a poor example at a professional level, because players have learnt mainly from analysis of other's techniques, rather than mostly making their own inferences. How a novice plays chess, inventing as they go, because they cannot draw on extensive experience, would be a better analogy, in my opinion.

Re: Why Robot Brains Need Symbols

#60

Post by mindgam3 »

gnode wrote: post #59
mindgam3 wrote: post #50

Earlier quoted context omitted.

"I don’t think we’re able to show our workings for higher level things like proofs." I can't speak for proofs, but this is false in the case of higher level things like chess. I'm not a grandmaster, but I was a chess master at age 10 and I am ranked ~2400 in bullet chess. To the average person my ability to play chess is "magic". But to me it's not magic at all. I can explain my thought process at any time. It's all…

I don't think this refutes the argument. You've just explained that the process by which you play chess is by calculation. In essence, you're doing something you could program a machine to do (without any learning component). The question is: how do you explain how you have an original idea, or learn something you previously had no conceptualisation of. I think chess is a poor example at a professional level, because…

"how do you explain how you have an original idea, or learn something you previously had no conceptualisation of"

This is like "where does your chess intuition come from" - and what I'm trying to express is that my chess intuition isn't actually a black box. There is a set of heuristics which I follow in order to come up with these "original ideas". Some of these I learned from watching other great players. Others I learned through trial and error, by playing tons of games, just like AlphaZero. The difference between me and AlphaZero is I can describe these heuristics conceptually in a way that anyone can understand, without resorting to "it's because this move tended to work in a large portion of the million games I played".

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