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Cyc

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Re: Cyc

#161
post #147
post #145

Earlier quoted context omitted.

What was the experiment you ran?

Filling in missing assignments for a boolean circuit. In general it is an NP hard problem, and humans appear to do it pretty well at computationally intractable sizes.

Did you publish a paper on these experiments?

I'm not familiar with the boolean circuit problem, but I wonder if it's an instance where the NP hardness comes from specific edge cases, and whether your experiment tested said edge cases. Compare with the fact that the C++ compiler is Turing complete: its Turing completeness arises from compiling extremely contrived bizzarro code that would never come up in practice. So for everyday code, humans can answer the question, "Will the C++ compiler enter an infinite loop when it tries to compile this code?", quite easily, just by answering "No." every time. That doesn't mean humans can solve the halting problem, though.

Re: Cyc

#162
post #161
post #147

Earlier quoted context omitted.

Filling in missing assignments for a boolean circuit. In general it is an NP hard problem, and humans appear to do it pretty well at computationally intractable sizes.

Did you publish a paper on these experiments? I'm not familiar with the boolean circuit problem, but I wonder if it's an instance where the NP hardness comes from specific edge cases, and whether your experiment tested said edge cases. Compare with the fact that the C++ compiler is Turing complete: its Turing completeness arises from compiling extremely contrived bizzarro code that would never come up in practice. So…

There may be some way the problem set I used is computationally tractable, but I am not aware of such. I have not published the work yet.

But, the bigger point is why are not others doing this kind of research? It does not seem out of the realm of conceptual possibility, since someone as myself came up with a test. And the question is prior to all the big AI projects we currently have going on.

Re: Cyc

#163
post #156

Earlier quoted context omitted.

So they may, but that would not follow logically. If the lowest level of physics is all computable then the higher physical levels must also be computable. Thus, if a higher level is not computable, it is not physical. We have never found anything at the lowest level that is not computable. None of it is even at the level of a Turing machine, unlike human produced computers.

Any chaotic system (highly sensitive to initial conditions) is practically uncomputable for us, because we have neither the computational power nor the ability to measure the initial conditions sufficiently accurately. Whether there is some lowest level at which everything is quantized, or it's real numbers all the way down, is an open question. I don't think your argument will seem compelling to anyone who doesn't a…

I would argue it is the other way around. If people are truly unbiased whether we are computable or not, then they would give my argument consideration. It is those with a priori computational bias that will not be phased by what I say.

Re: Cyc

#164
post #150

Earlier quoted context omitted.

It's possible for the mind to solve more halting problems than any finite computer, yet still not be as powerful as a complete halting oracle. Thus, the fact we haven't solved every problem does not count as evidence against the mind being a halting oracle.

Actually it does. While it's logically possible, evidence for a hypothesis A is still provided by any data that is more likely under hypothesis A than under hypothesis B. The hypothesis that the mind is computable but is using heuristics, of various levels of sophistication, explains the data better and is more parsimonious than your hypothesis, because we already have reason to believe that the mind uses heuristics…

In that setup the evidence makes the uncomputable partial Oracle the most likely hypothesis, since the space of uncomputable partial oracles is much much larger (infinitely so) than either computable minds or perfect halting oracles.

Re: Cyc

#165
post #151

Earlier quoted context omitted.

I've never solved a problem while completely unconscious. I've occasionally had insights while dreaming, and there is some intuitive aspect to thought that is difficult or impossible to explicitly articulate. But, every instance of problem solving I engage in is connected with conscious thought.

I don't know what "completely unconscious" means, but it doesn't sound like what I was describing. I think I agree that my problem solving is connected with conscious thought, but the heavy lifting is mostly (or at least frequently) done by something that "I" am not aware of in detail. When someone is explaining something complicated, pretty often, maybe not always, my (conscious) mind is pretty blank. I can say "yea…

Every instance of problem solving I encounter involves conscious intentionality. As an analogy, when I get a drink from the fridge, there is a lot going on in my body to make that happen that I do not consciously control. But, overall it is taking place due to my conscious intentional control. I argue the same is going on in the mind, a lot of subconscious things going on that I do not directly control, but the overall effect is directed by my conscious control.

Re: Cyc

#166
post #165

Earlier quoted context omitted.

I don't know what "completely unconscious" means, but it doesn't sound like what I was describing. I think I agree that my problem solving is connected with conscious thought, but the heavy lifting is mostly (or at least frequently) done by something that "I" am not aware of in detail. When someone is explaining something complicated, pretty often, maybe not always, my (conscious) mind is pretty blank. I can say "yea…

Every instance of problem solving I encounter involves conscious intentionality. As an analogy, when I get a drink from the fridge, there is a lot going on in my body to make that happen that I do not consciously control. But, overall it is taking place due to my conscious intentional control. I argue the same is going on in the mind, a lot of subconscious things going on that I do not directly control, but the overa…

That doesn't seem like a good analogy to me, because intrinsically problem solving is about something you don't understand in the first place, whereas reaching for something you do already understand what you are doing.

If I use a mechanical grabber aid to reach something, then it isn't figuring out how to do anything. But if I ask Wolfram Alpha the answer to a math problem, it isn't me doing it.

Re: Cyc

#167
post #163

Earlier quoted context omitted.

Any chaotic system (highly sensitive to initial conditions) is practically uncomputable for us, because we have neither the computational power nor the ability to measure the initial conditions sufficiently accurately. Whether there is some lowest level at which everything is quantized, or it's real numbers all the way down, is an open question. I don't think your argument will seem compelling to anyone who doesn't a…

I would argue it is the other way around. If people are truly unbiased whether we are computable or not, then they would give my argument consideration. It is those with a priori computational bias that will not be phased by what I say.

You're right, but people tend to have strong priors one way of the other, often unconsciously. This is one of those classic cases where people with strong, divergent priors will disagree more strongly after seeing the same evidence. So if you want to convince people you'll have to try harder than most to find common ground.

Re: Cyc

#168
post #164

Earlier quoted context omitted.

Actually it does. While it's logically possible, evidence for a hypothesis A is still provided by any data that is more likely under hypothesis A than under hypothesis B. The hypothesis that the mind is computable but is using heuristics, of various levels of sophistication, explains the data better and is more parsimonious than your hypothesis, because we already have reason to believe that the mind uses heuristics…

In that setup the evidence makes the uncomputable partial Oracle the most likely hypothesis, since the space of uncomputable partial oracles is much much larger (infinitely so) than either computable minds or perfect halting oracles.

Well, no. That is the same kind of error as Zeno's paradox.

One assigns a prior to a class of hypotheses, and the cardinality of that set does not change the total probability you assign to the entire hypothesis class.

If one instead assigns a constant non-zero prior to each individual hypothesis of an infinite class, a grievous error has been committed and inconsistent and paradoxical beliefs can be the only result.

Re: Cyc

#169
post #87

Earlier quoted context omitted.

1) Do you think it's possible that Cyc would lead to AGI? 2) Do you think it's possible that Cyc would lead to AI advances that are impressive to the layman like AlphaGo or GPT-2?

These answers are very personal to me. I joined Cycorp because Doug Lenat sold me on it being a more viable path toward something like AGI than I had suspected when I read about it. I left for a number of reasons (e.g. just to pursue other projects) but a big one was slowly coming to doubt that. I could be sold on the idea that Cyc or something Cyc-like could be a piece of the puzzle for AGI. I say "Cyc-like" because…

While the last part of your comment is kind of messy, but this part I agree and find it interesting:

> in the ML case those patterns were hammered out one tiny change at a time until they matched reality, whereas in the human there's a moment where they did something very creative and had an idea and went through a kind of phase transition where they started thinking about the game in different terms.

Phase transition, or the "aha" moment, where things start to logically make sense. Humans have that moment. Knowledge gets crystallized in the same sense water starting to form a crystal structure. The regularity in the structure offers the ability to extrapolate, which is what current ML is known to be poor at.

Re: Cyc

#170
post #55

Earlier quoted context omitted.

How do you deal with the fact that human knowledge is probabilistic? I.e. that it's actually mostly "belief" rather than a "fact", and the "correct" answer heavily depends on the context in a somewhat Bayesian way. Best I can tell we don't yet have math to model this in any kind of a comprehensive way.

Cyc has a few ways of dealing with fallibility. Cyc doesn't do anything Bayesian like assigning specific probabilities to individual beliefs - IIRC they tried something like that and it had the problem where nobody felt very confident about attaching any particular precise number to priors and also the inference chains can be so long and involve so many assertions that anything less than 1 probability for most assert…

What is your opinion about the popular trend of making everything probabilistic, especially in ML, in favor of default logic? For example, does it make sense to say "mammals lay eggs by 98%" because of the Platypuses exception?
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