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Why Robot Brains Need Symbols

nautil.us

21–30 of 73 posts

Re: Why Robot Brains Need Symbols

#21
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…

> 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.

A mouse can't do that either. Yet we are unable to mimic mouse intelligence with any of our current tools.

Re: Why Robot Brains Need Symbols

#22
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…

> And right now, the tangible evidence for symbolism is simply not cutting it. In AI/ML perhaps. In the biological and psychological sciences the importance of symbols to cognitive functioning is pretty well established. Just look at how important the mastery of language is for complicated thought. One of the main differences between linguistic thought and other forms of thinking is all about symbol manipulation. (Th…

It’s also pretty well known in math and CS/SE communities.

Heck, the mathematical research into the power of language, and in particular the ability to embed models of reasoning into equations to allow you to formalize your meta-reasoning, is what led to the birth of electric computers.

So I find it shallow skepticism to suggest there’s not evidence that it would be useful to AI, because literally the most cursory glance would show mounds of it.

The real challenge is and always has been how to combine or embed symbolic reasoning capabilities efficiently within a fuzzier approximator, allowing for “getting close” in a fuzzy way then fine tuning it using more advanced rules.

That mimics more closely how we think, where we broadly intuit a few potential answers, then use higher order thinking to sift through them.

Re: Why Robot Brains Need Symbols

#23
post #16

Earlier quoted context omitted.

Humans can almost always give an explanation judgement but, for intuitive judgements at least, the reasons we give are frequently wrong or incomplete. People seldom notice that we rate essayists with more symmetric faces as better at writing but we have this bias and tons more besides. But I don't think that there's any reason to doubt that when using abstract reasoning, Kahneman's system 2, our explanations of our t…

Aren't we - as a group - better in this? I'm thinking about the scientific method, and the common differentiation there between the context of discovery and the context of justification . So you are free to discover a mathematical theorem by intuition or during daydreaming (like the molecular structure of benzene) - anything goes . But in the context of justification, you have to be much more disciplined - even if yo…

We are verifying the results of our opaque brain processes. We cannot yet verify that our explanations of those processes are correct.

Re: Why Robot Brains Need Symbols

#24

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…

>> He ends the essay with "All I am saying is to give Ps (and Qs) a chance.". But who exactly is this aimed at?

It's a slightly garbled (and so not immediately recognisable, perhaps) pun on the verse "All that we're saying/ is give peace a chance" from John Lennon's "Give Peace a Chance".

So it's not addressed to anyone- it's just his attempt at injecting a bit of levity in the debate.

EDIT:

>> If Ps (and Qs) is a better approach then do the research and publish the results.

Well, people have done that, yes. For example, the Evans and Grefenstette paper Marcus' article cites towards the end has shown in a very clear manner the power of combining symbolic with sub-symbolic approaches, as has the work of, off the top of my head, Artur D'avila Garcez (neuro-symbolic computation), Luciano Serafini (a differentiable logic), and many others.

And yet, my intuition at least is that most people who have heard about Deep Learning, haven't heard about that work.

Re: Why Robot Brains Need Symbols

#25
post #6
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…

Or to frame your argument in terms of science rather than engineering, it's a falsifiable hypothesis. The author should go try to test it and then let us know if it works.

i’d say the bus picture classification is a pretty telling example that something’s missing in the amount of knowledge deep learning is able to extract from training data sets.

Anybody who understand what a school bus is wouldn’t mistake it for a snow plow in the other pictures.

Re: Why Robot Brains Need Symbols

#26
post #11

Earlier quoted context omitted.

> 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. What definition are you using? From the my understanding, if you can explain your reasoning, then a deep learning system can in principle learn how to explain its reasoning. If it couldn’t, you couldn’t either.

Humans can almost always give an explanation judgement but, for intuitive judgements at least, the reasons we give are frequently wrong or incomplete. People seldom notice that we rate essayists with more symmetric faces as better at writing but we have this bias and tons more besides. But I don't think that there's any reason to doubt that when using abstract reasoning, Kahneman's system 2, our explanations of our t…

Given some results regarding brain damage we might just be rationalizing afterwards separate from the problem solving. Severed corpus callosum I believe it was.

Or that effect might just be how a brain keeps functioning after losing some pieces - better off evolutionarily have data integrity issues than shut down if a checksum fails.

I believe that ML can technically give you an answer but it ammounts to a summation of its training set and how it parses the data. Which isn't too readable to even mathematicians and leaves it vulnerable to stuff like adding a small pixel cloud to cause it to see a toy turtle as an assault rifle. Our errors certainly exist for visual processing but they tend to be more distorion than that.

Re: Why Robot Brains Need Symbols

#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 learning is the most promising direction AI went into since a long time. Finding flaws in DL does not point back to a programmer crafting handwritten rules to correct it. It merely points to more DL research needed to have machines correct this themselves. Preferrably differentiable.

Re: Why Robot Brains Need Symbols

#28
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…

> 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, ...

Re: Why Robot Brains Need Symbols

#29

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…

>> He ends the essay with "All I am saying is to give Ps (and Qs) a chance.". But who exactly is this aimed at? It's a slightly garbled (and so not immediately recognisable, perhaps) pun on the verse "All that we're saying/ is give peace a chance" from John Lennon's "Give Peace a Chance". So it's not addressed to anyone- it's just his attempt at injecting a bit of levity in the debate. EDIT: >> If Ps (and Qs) is a be…

This comes across a bit like the Tanenbaum–Torvalds monolithic/microkernel debate in the 90s. Tanenbaum in this case is Marcus and Torvalds is LeCunn. There are so many well established benchmarks out there. Just build whatever this symbolic system is that you're advocating and beat the benchmarks. Or maybe create your own benchmarks and then we can also apply Deep Learning to those problems too and see who wins? Until then, no one really has to pay any serious attention to these clamourings.

Re: Why Robot Brains Need Symbols

#30
This is something that’s been a challenge to my team for a long time. For us, machine learning has produced very good inferences, but it doesn’t create models of how the universe works. For example, if we input a lot of raw weather data into a statistical model, we can predict how it may affect the power output of a solar array. But, I can’t get the machine to ‘understand’ that clouds decrease solar availability.
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