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Artificial Intelligence Is Already Weirdly Inhuman

nautil.us

41–50 of 84 posts

Re: Artificial Intelligence Is Already Weirdly Inhuman

#41
post #22

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…

> I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. What do you think you're made of?

There are many specialized areas of the human brain.

It's not a single, unidirectional, backpropagated, simple-coefficient, neural net. It is not a recurrent neural network, nor is it a single instance of any particular NN-derived or NN-ish network.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#42

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…

At the risk of nitpicking, I'm going to specifically address your statement of "It feels like an ostrich" To my mind, that's EXACTLY how humans do it. A baby is not instructed, "it has 2 legs, feathers, and is tall, therefore it is an ostrich", there's quite a bit more "LOOK OSTRICH /present input of ostrich/" prior to the point of being able to generate any justification. As sister posts have pointed out, I tend to…

Using the word "feels" (or "thinks") is a too much of a personification of a neural network. You cannot forget that under the hood, it is cranking through a bunch of math functions. You always get the same output from the same input. That function is not going to change on its own, and it is not going to suddenly gain new abilities to express itself in words. It is not a human, so there is no point in assuming it will behave or grow like a human.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#44

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding.

I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base.

I don't claim this to be any amazing insight, but I strongly suspect that the human brain works on some combination of both probabilistic methods and something like the symbolic logic of GOFAI. How many "systems" there are, and how they interact, is an open question, but I really do think there's "some there, there".

Which reminds me, I need to get back to reading "Thinking, Fast and Slow", which I started a while back and got distracted away from.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#45

Sigh. The phrase "neural network" is getting tossed around these days with some type of sensationalist flair, an almost romanticized notion of this impending explosion of super-human phenomena. As Alex Smola says with much frustration in one his classes, "it's only math!" It's a fancy term for straightforward mathematics. Bloggers are so often making them out to be much more than they are.

Sigh. The phrase "neural network" is getting tossed around these days with some type of sensationalist flair, an almost romanticized notion of this impending explosion of super-human phenomena.

It's all cyclical. This is at least the second, if not the third, wave of hype for Neural Networks. I remember a period back in the mid to late 90's when this stuff was quite the rage.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#46

Neural Networks do not think. They perform a series of computations, and arrive at a result. It is not intelligence. It is a very useful tool for solving problems that can be quantified and that we can generate a lot of data from, but ultimately, it is still human intelligence that is interpreting the problem and result.

Human brains do not think. They perform a series of computations, and arrive at a result. It is not intelligence. It is a very useful tool for solving problems that can be translated into neural inputs.

Sufficiently advanced robotics is indistinguishable from life. - Adapted from Arthur C. Clarke.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#47

Neural Networks do not think. They perform a series of computations, and arrive at a result. It is not intelligence. It is a very useful tool for solving problems that can be quantified and that we can generate a lot of data from, but ultimately, it is still human intelligence that is interpreting the problem and result.

Human brains do not think. They perform a series of computations, and arrive at a result. It is not intelligence. It is a very useful tool for solving problems that can be translated into neural inputs.

And what evidence do you have that human neurons do any kind of computation at all?

Generally, they are stimulated by some sensation until they reach a certain threshold that causes them to fire. That is the basic kind of functionality that nodes in a neural network try to simulate.

But human neurons are not dependent on numbers and change in much more complex ways than a few parameters. The brain requires a lot less data than these networks to learn new concepts. And the concepts that these networks learn are all ideas that humans came up with.

A network does not hold an opinion, it takes in inputs and gives outputs. I do not mean to say that we cannot make a network to simulate a brain, but that is not what we have right now.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#48
post #38

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…

IANANR (I Am Not A Neuro-Researcher), but it seems to me the "only" step you're requiring is that of self-consciousness. We can explain why we think it's an ostrich because we can point our neural networks at themselves, and say, "what sort of thinking process does this look like? Oh, it looks like visual pattern recognition of certain features like a long hairless neck, bird features, etc, so that's why I think it's…

To clarify, I'm not saying human-like AI is impossible or unreasonably far off.

The author seems to be implying that what current NNs show is a viable form of intelligence that just happens to "think" in a different way that we need to figure out.

I'm saying this particular manifestation of trained behavior is not viable for expanding into human-level intelligence, as there's no hope of meta-cognition (I don't use the term "self-consciousness" purely because it's overloaded with unreasonable fields). NNs would have to fundamentally change or be replaced in order to gain such. When we do achieve machine conceptual cognition & meta-cognition, it will be a system that will not "think" like feed-forward trained NNs, even if it shares some history or composition with that architecture.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#49
I think the "static is a cheetah" example just highlights that the neural net is not identifying the best features with which to identify a cheetah. Or alternatively, if, during training, the neural net was only fed pictures of nature with or without cheetahs in them, then what it's really telling you is not the probability that a picture contains a cheetah, but rather the conditional probability that a picture contains a cheetah given that it is a picture of nature. In other words, that picture of static is most likely well outside the domain of the training set, so classifying it involves a large extrapolation, with all the attendant amplification of errors.

Perhaps what we need is a classifier that can tell when a picture is significantly outside of its training experience and say "I've never seen anything like that before" instead of giving an arbitrary classification.

Re: Artificial Intelligence Is Already Weirdly Inhuman

#50

I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…

At the risk of nitpicking, I'm going to specifically address your statement of "It feels like an ostrich" To my mind, that's EXACTLY how humans do it. A baby is not instructed, "it has 2 legs, feathers, and is tall, therefore it is an ostrich", there's quite a bit more "LOOK OSTRICH /present input of ostrich/" prior to the point of being able to generate any justification. As sister posts have pointed out, I tend to…

I think one of the major differences is that humans use multiple independent algorithms when it comes to deciding if there's an ostrich in the picture. And most of these are far more sophisticated than the NNs. So in practice the way we solve classification problems is fundamentally different, even though it may seem/feel somewhat similar.

Most prominently there's object recognition (telling things apart from the background, recognizing parts of objects, etc.), size/distance determination (which uses over a dozen separate algorithms: https://en.wikipedia.org/wiki/Depth_perception). We can also reconstruct a 3d model from a 2d image and compare that to our idea of what ostriches look like in 3 dimensions.

So even if it is done unconsciously, we recognize an ostrich because (among other things) it's the size of an ostrich. The NN has no idea what size is, let alone the size of an ostrich relative to other things.

I think the next big breakthrough in machine learning is in ensembles containing NNs trained for completely different things, but acting in a complementary fashion.

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