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Why Robot Brains Need Symbols

nautil.us

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Re: Why Robot Brains Need Symbols

#41

Post by drb91 »

317070 wrote: post #2

No, they don't. Now, feel free to _show_ me that they do, and I will gladly accept to have been wrong. But this argument that because of some very theoretical view on the problem the current engineering solutions should be abandoned, without actually providing good engineering alternatives, is weird. I have a bit of a "not even wrong" feeling on the symbolist side of the debate. Deep neural networks have serious flaw…

Getting tasks done has never been a ringing endorsement for the general applicability of the underlying algorithm.

Meanwhile, the entirety of human communication is built on symbols. If computers can’t deal with them, how useful can computers ultimately be? Roombas can only improve so much.

Re: Why Robot Brains Need Symbols

#42

Post by marcosdumay »

opless wrote: post #9

He's right about LeCun. Yann really does not like Deep Learning being criticized. Please someone who knows much more than me about deep learning tell me how a deep learning ai can explain how it came to an answer. It can't. By definition. You can say that it's a equation with a lot of terms, but that isn't really showing your working out. You need a symbolic system to show that working out. This isn't to say that dee…

A trained neural network is a model, just like any other kind of model. If there is any overall property of the data it learned, you can coerce it from the network just like you can read them from any mathematical model. (What is, for some properties, very easily, and for others it's very hard.)

An AI can always explain how it came to an answer. But the explanation can be like "there are way too many factors" or "things are like this just because of those other things, if those changed, the explanation would too". But those are not an attribute of the neural networks, but of the problem they are solving. If you get an explanation like that for a problem that has simple explanations, it means you failed at training your network.

Re: Why Robot Brains Need Symbols

#43

Post by d--b »

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!
Or

    - The house is red
    - No! it's green!
    - Nah, it's red, you're colorblind
Brain logic is MUCH fuzzier than symbolic logic. Symbols exist, sure, but they're part of a bigger logical soup. And I believe that no low level logical circuit exists in the brain (which also explains why humans are so slow at logic, calculation and so on).

Maybe symbolic logic could be a intermediate step for some applications. Or maybe humans could be much smarter if they had access to some symbolic logic processing unit. But as far as research is involved, I think there is way more to gain if we managed to have symbolic logic emerge from deep neural nets.

In fact, you could argue that Alpha Go definitely developed some kind of symbolic logic, especially in the end-game, where there's little intuition and way more calculation.

Re: Why Robot Brains Need Symbols

#44

Post by posterboy »

chimprich wrote: post #13
317070 wrote: post #2

No, they don't. Now, feel free to _show_ me that they do, and I will gladly accept to have been wrong. But this argument that because of some very theoretical view on the problem the current engineering solutions should be abandoned, without actually providing good engineering alternatives, is weird. I have a bit of a "not even wrong" feeling on the symbolist side of the debate. Deep neural networks have serious flaw…

> But this argument that because of some very theoretical view on the problem the current engineering solutions should be abandoned That's not the author's argument at all. Even the subtitle of the article says "We’ll need both deep learning and symbol manipulation to build AI.".

A compromise between the two would be to identify powerful abstructions over nodes and nets that are equivalent to symbol manipulation circuits. Self assembly and self modification are certainly not strange to symbolic logic, but this doesn't work so well for most programmers. So we need more geniuses and they need to tailor neural nets to help them build symbolic logic (if only as intermediate debugging output).

Re: Why Robot Brains Need Symbols

#45

Post by p1esk »

red75prime wrote: post #28
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…

> they actually can freely introspect their thought process as part of their thought process. Do you mean that they can in principle? I don't know existing systems, which can inspect their own weights and output a vector of confidence scores that they can recognize classes A, B, C, ...

output a vector of confidence scores that they can recognize classes A, B, C, ...

This is literally what neural networks do when classifying patterns.

Re: Why Robot Brains Need Symbols

#46

Post by hopler »

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.

Re: Why Robot Brains Need Symbols

#47

Post by giardini »

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 is not necessary.

Certainly connectionist deep learning is exciting and should be investigated as far as possible but it is only one of many tools. We should avoid being the man with a hammer who thinks that every problem looks like a nail.

Re: Why Robot Brains Need Symbols

#48

Post by YeGoblynQueenne »

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…

>> 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.

Who said anything about hardcoding anything? Marcus is advocating for the use of gradient descent to learn symbols- he even cites the DeepMind paper on θILP, a differentiable Inductive Logic Programming system that learns symbolic rules with deep learning.

Re: Why Robot Brains Need Symbols

#49

Post by red75prime »

p1esk wrote: post #45
red75prime wrote: post #28

Earlier quoted context omitted.

> they actually can freely introspect their thought process as part of their thought process. Do you mean that they can in principle? I don't know existing systems, which can inspect their own weights and output a vector of confidence scores that they can recognize classes A, B, C, ...

output a vector of confidence scores that they can recognize classes A, B, C, ... This is literally what neural networks do when classifying patterns.

They classify patterns, not their own ability to classify patterns.

Re: Why Robot Brains Need Symbols

#50

Post by mindgam3 »

FakeComments wrote: post #19
opless wrote: post #14

Earlier quoted context omitted.

We're not deep learning systems. So reasoning by analogy there isn't correct. (Aside: There have been experiments that show that many explanation for [everyday] actions are, in fact made up after the decision to execute an action. Which gives some insight to the whole nature of free will - but that's another discussion entirely. However, indeed we're able to show our workings for higher level workings, like mathemati…

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 based on symbolic manipulation at progressively higher levels, i.e. clustering pieces into "chunks", connecting these chunks into higher level patterns like weak pawn structure or forks, and ultimately deciding on the best course of action by weighing all of the different high level patterns. Every step is rule-based logic which I can readily explain to anyone, even a chess novice. The part that appears "magic" is the ability to do all of these calculations in the blink of an eye. But that too is simply due to having trained so many of these patterns extensively at a young age. Anyone who can speak a language is doing the same thing, manipulating complex symbolic objects in real time at progressively higher levels (i.e. letters, words, sentences, paragraphs).

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