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Why general artificial intelligence will not be realized

nature.com

291–300 of 403 posts

Re: Why general artificial intelligence will not be realized

#291

Here is, to me, the relevant line: "Hubert Dreyfus, who argued that computers, who have no body, no childhood and no cultural practice, could not acquire intelligence at all. One of Dreyfus’ main arguments was that human knowledge is partly tacit, and therefore cannot be articulated and incorporated in a computer program. " I have not read the rest of the article but in the introduction it's stated: "The article furt…

If by "soul" you mean an emotional core, then you'd be correct. Emotions allow us to short-circuit the processing required to ascribe value to a thing or situation.

But that has nothing to do with dualism or theology.

Re: Why general artificial intelligence will not be realized

#292
Why do we think computers can achieve intelligence? Where did this idea ever first come from? it sounds almost childish if one traces the history and wild misconception it must have emerged from. The idea maybe dates to Turing? maybe even Leibnitz? What was the idea based on? On seeing that some machines can "behave" i.e. do things a human does? And they started thinking if ultimately that machine might be able to do everything a human does? That a human is nothing but a " complicated machine" in the sense that we can formulate complex but finite rules for its behavior? maybe even simple rules which when applied on appropriate substrates would lead to "emergence" of such behaviors? That is a BIG assumption to make really. Intelligence and cognition here are treated as lists of rules which can be applied to any substrate. An electronic computer is just one substrate. i should also be able to do this on a sufficiently giant mechanical computer.

Even physics seem to have this rule-obssessed assumption. Can we really simulate the universe AS IT IS? Sure we can some parts of it. But is there a theory of everything really? After such a theory we would need to know nothing. physics would be pretty much done with. This theory would explain all observations in the past, present and future of anything we make in the universe.

Even in our search for the smallest particles can such a "bottoming out" ever take place?

EDIT: grammar

Re: Why general artificial intelligence will not be realized

#293
post #256

Earlier quoted context omitted.

The author of the article specifically says this: I have earlier said that neural networks need not be programmed, and therefore can handle tacit knowledge. Also you are misunderstanding what tacit means. It doesn't mean anything mystical - merely that it is gained from observations rather than logically reasoning about something.

You might be right but I'm not inclined to give the author the benefit of the doubt. From the abstract, the author clearly says: "The article further argues that ... computers are not in the world." The specific quote you mention is in a larger paragraph which says: "Computers are not in our world. I have earlier said that neural networks need not be programmed, and therefore can handle tacit knowledge. However, it i…

(I've read the whole article.)

I don't think the author makes a strong argument, and I disagree with their conclusion.

But the author's argument actually appears to be mostly that science itself is insufficient to understand the world. This argument is outlined in the section starting "But the replacement of our everyday world by the world of science is based on a fundamental misunderstanding. Edmund Husserl was one of the first who pointed this out, and attributed this misunderstanding to Galileo."

I think it's a pretty weak argument and I'm surprised Nature published it - the author wouldn't last 2 minutes trying to defend it on HN.

I do think that a better articulated version of his argument would be something like this (which attempts to capture what he means by "not in the world"): "despite all the advances in neural networks encoding tacit knowledge, it still takes a deeper human-level set of tacit knowledge in a wider context to make these neural networks useful. While we have surpassed human skills in-the-small, science based benchmarks, we seem no closer to achieving embodied human-level intelligence from machines in-the-large."

But tacit still doesn't mean what you claimed.

Re: Why general artificial intelligence will not be realized

#294
post #245

Earlier quoted context omitted.

> Every deep learning system has tacit knowledge: it knows a chair when it sees one but can't explain how it knows. A traditional computer program that can find the derivative of sin(x) also can not explain how it knows.

> A traditional computer program that can find the derivative of sin(x) also can not explain how it knows. Oh but it could , and that's the point. Some computer differentiation techniques just follow the same rules you learned when you took calculus. They typically don't show you which rules they followed, but they easily could . Other differentiation techniques are more exotic but there's no reason they couldn't sho…

I'm not sure a human can explain how they know a chair is a chair, either. They can come up with a post-hoc rationalisation, but that's not guaranteed to really represent the decision-making process they went through.

At best you get an answer that describes one or more conscious decisions and leaves the unconscious decisions out, such as "it looks a lot like a stool because it's low to the ground and has three legs, but it has a back, so I think it's a chair"; when the real answer is that they have a bunch of pattern-matching visual neurons, and those neurons feed into other neurons that detect more complicated patterns, and the concept of a chair eventually emerges.

Re: Why general artificial intelligence will not be realized

#295
post #216

I came to this article expecting a logical proof of why AI was impossible, but instead found the following tautological argument: hard AI, which I define as intelligence with tacit knowledge, which in turn I define as knowledge that cannot be ran in algorithms, is impossible to be ran in algorithms. Disappointing. My counterpoint: is there anything that cannot be ran in algorithms? The way I see it the only thing sto…

> is there anything that cannot be ran in algorithms? The way I see it the only thing stopping me from simulating every atom in a brain is computational power.

I am not for sure I understand the specifics of what you mean by "is there anything that cannot be ran in algorithms?", but there are plenty of things that are not computable or decidable in computation. These are theoretical constraints. There are also practical constraints that effectively increase the list of these things.

Re: Why general artificial intelligence will not be realized

#296

Earlier quoted context omitted.

All purely binary logic. It can't be anything more --- this is all the hardware understands.

Wrong. The process is more than the operations. A computer is not just a playback machine like a mechanical loom.

A computer is not just a playback machine like a mechanical loom.

What is it then? Magic?

The fact that you don't understand how it works doesn't make it magical.

Every program ever written for your desktop computer was ultimately "compiled" into a long series of simple binary logic operations that your computer blindly repeats at very high speed. For every set of inputs, it recreates the same output --- kinda like a loom mechanically weaves a particular pattern at high speed once it has been "programmed" using a set of punch cards not unlike those once used to program computers.

Re: Why general artificial intelligence will not be realized

#297
post #244

Earlier quoted context omitted.

The Church-Turing thesis only states that the lambda calculus and Turing machines can compute the same functions. It has nothing to do with materialism or dualism and it certainly doesn’t state that the universe is a Turing machine.

The Church-Turing thesis is: "Every effectively calculable function is a computable function" [1] The definition is a little terse so we have to expand on what "effectively calculable function" and "computable function" mean. By a "computable function", we mean a Turing machine. The term "effectively calculable function" is a little unclear but one definition that I think is the closest to the intent is "it can be do…

"That is, the physical world, including human cognition, can be realized by a Turing machine."

How did you get to the conclusion that all physical world is computable? Rather a huge jump i would say. Sure some things are, but "all of it" would rather be a BIG assumption. Physical theories of the world are limited to our current state of observations and knowledge of the world, they AREN'T the actual world. Who is to say this continuous search, observation and refinement of theories will ever end and we'll have a FINAL theory of everything that we can then plug into a computer and simulate?

Sure you can now say "I don't require a theory of everything, I just need a "sufficient" amount of theory to simulate the part of the world from which I can have my intelligence & cognition emerge". Sure you can say that but that would again hinge on the assumption that such cognition is reducable to these "sufficient" laws.

Likewise saying that the whole physical world can be realized by a Turung machine is a bit rich when we don't even know if such a complete reduction of the physical world is possible and when such reduction to physical laws is surely not yet complete.

EDIT: grammar

Re: Why general artificial intelligence will not be realized

#298
post #245
post #164

Earlier quoted context omitted.

Tacit knowledge is knowledge that results from adapting to experience, like learning to tie shoelaces with practice, rather than something like finding the derivative of sin(x) by the usual mathematical proof method (reasoning step by formal step). Every deep learning system has tacit knowledge: it knows a chair when it sees one but can't explain how it knows. It just adapted its connections to training until it got…

> Every deep learning system has tacit knowledge: it knows a chair when it sees one but can't explain how it knows. A traditional computer program that can find the derivative of sin(x) also can not explain how it knows.

People can't explain how they know something either. They know it has something to do with their brains, but they don't know how exactly the mechanism works.

At a certain level, "knowledge" is baked into the execution hardware.

Re: Why general artificial intelligence will not be realized

#299
post #249
post #224

Earlier quoted context omitted.

I have read it and you’re not missing anything. One of the examples of tacit knowledge they give is walking and that therefore it is impossible to teach a computer to walk. They should watch one of the videos from Boston Dynamics.

That's not teaching a computer to walk, that's building a walking machine. Subtle difference, but it's easy to prove; no matter how well you build a Boston dynamics robot, it will never like walking in the same way your TV will never like entertaining people. There's no "I" there to learn.

Way to change the goal posts. We built a machine than learned how to walk. Mission accomplished. The assertion in the article was either wrong or irrelevant, pick one.

Then a bald assertion, computers will never X. Says you. Just because we’re not there yet is no proof it’s impossible.

Re: Why general artificial intelligence will not be realized

#300
post #293

Earlier quoted context omitted.

You might be right but I'm not inclined to give the author the benefit of the doubt. From the abstract, the author clearly says: "The article further argues that ... computers are not in the world." The specific quote you mention is in a larger paragraph which says: "Computers are not in our world. I have earlier said that neural networks need not be programmed, and therefore can handle tacit knowledge. However, it i…

(I've read the whole article.) I don't think the author makes a strong argument, and I disagree with their conclusion. But the author's argument actually appears to be mostly that science itself is insufficient to understand the world. This argument is outlined in the section starting "But the replacement of our everyday world by the world of science is based on a fundamental misunderstanding. Edmund Husserl was one…

Again, I think you're giving the author the benefit of the doubt when it's not warranted. Your paraphrasing "science itself is insufficient to understand the world" is code for dualism.

I forgot to add the reference in the comment above but tacit means what I said it meant. I quoted directly from Wiktionary [1]. I'll do so again here:

    Adjective
      tacit (comparative more tacit, superlative most tacit)
        1. Expressed in silence; implied, but not made explicit; silent. 
           tacit consent : consent by silence, or by not raising an objection
        2. (logic) Not derived from formal principles of reasoning; based on
           induction rather than deduction.
I chose the "logic" interpretation as it seemed the most appropriate given the context.

[1] https://en.wiktionary.org/wiki/tacit

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