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AI is mostly about curve fitting (2018)

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Re: AI is mostly about curve fitting (2018)

#161

Post by Invictus0 »

lordnacho wrote: post #90
umarniz wrote: post #38

I think intelligence has for some time already been boiled down to curve fitting, even for humans. Our current accepted definition of intelligence in schools is to get a score that is higher than the average to be considered sufficiently intelligent to proceed to the next grade. I feel anything that we develop for AI would fundamentally always be inspired by our own experiences and hence curve fitting is something we…

> I think intelligence has for some time already been boiled down to curve fitting, even for humans. No, the book actually makes an important point about this. For instance, let's take a counterfactual. How do you know what would have happened if Barcelona had played Lionel Messi in goal over the latest season? They've never done this, there are no data points for you to fit. The situation almost never arises that an…

If we say that goalkeeping requires certain skills, and being an outfielder also requires certain skills, these skills being graphed on a chart, its simple to see that Messi would not perform well as a goalkeeper, and this is still curvefitting. If it turns out that the goalkeeper and outfielder have a lot of overlapping skills, we might fall back and refer to a probability curve of things that normally happen; "players require practice to excel in their position" would seem to fall on that curve.

The fact is that everything in the world can be reduced down to curves. It's just a matter of your perspective.

Re: AI is mostly about curve fitting (2018)

#162

Post by projektfu »

ecorithm wrote: post #160
projektfu wrote: post #159

Earlier quoted context omitted.

Ok things may have changed since I studied ethology

Right, to be fair to you this was a hotly debated topic in ethology (and still is to an extent), however I would say most modern ethologist have come out on the side of embracing evolutionary parsimony and viewing our human experience as a valuable asset to understanding animals (especially mammals). Probably the most cited paper regarding this debate is by Marc Bekoff, "Cognitive Ethology: Slayers, Skeptics, and Pro…

Phew, I'm surprised to see such an emotionally-charged article on the subject. Everyone who is uncomfortable with anthropomorphism is biased and misguided in some way, but extremist proponents are merely overly enthusiastic.

I do wonder about the theoretical bird scientist trying to figure out the "fixed action patterns" of other animals. If anthropomorphism is the way to go, surely it goes in the other direction in some way.

Re: AI is mostly about curve fitting (2018)

#163

Post by projektfu »

roenxi wrote: post #152
dghughes wrote: post #115

Earlier quoted context omitted.

Or people who say "The computer thinks...". No it's a machine that only does what people make it do.

We've seen that threshold crossed with neural agents like AlphaGo which can be reasonably described as thinking. It decides if moves are good or bad after a little pause for processing, its decisions improve with time, it has an opinion on the state of play, the opinion is formed using basically the same data as a human, different iterations of the neural network can have a different opinion but there is a link betwe…

Chess is one of those areas where humans have developed computer-like abilities, such as exhaustive search. What's interesting is the appearance of intuition-like movement in modern chess computers, but is it ... intuition?

Re: AI is mostly about curve fitting (2018)

#164

Post by manx »

zby wrote: post #145
galangalalgol wrote: post #2

Depending on how complex a curve, and how many dimensions it is in, couldn't you argues that is essentially what our brains do as well? Not that I am defending the massive hype field that is ML today, but curve fitting is a form of intelligence.

What our brains do is curve fitting plus experiments . Causality is learned through experiments - and as children we do a lot of experiments (with moving our limbs etc). With just observations you can have only correlations. For example you can correlate smoke with fire, but only through experiment you can learn that it is fire that causes smoke not the other way around.

This is exactly what I thought, but was not able to put into words. Thank you.

Re: AI is mostly about curve fitting (2018)

#165

Post by drongoking »

roenxi wrote: post #152
dghughes wrote: post #115

Earlier quoted context omitted.

Or people who say "The computer thinks...". No it's a machine that only does what people make it do.

We've seen that threshold crossed with neural agents like AlphaGo which can be reasonably described as thinking. It decides if moves are good or bad after a little pause for processing, its decisions improve with time, it has an opinion on the state of play, the opinion is formed using basically the same data as a human, different iterations of the neural network can have a different opinion but there is a link betwe…

> We've seen that threshold crossed with neural agents like AlphaGo which can be reasonably described as thinking.

I don't recall ever reading in a technical paper, or in an interview, a leader in the field of ANNs claim they were thinking. If you have, I'd like to see a reference. Most are fairly honest about the differences between artificial neurons and real ones, and between human cognition and what ANNs are doing with data.

Re: AI is mostly about curve fitting (2018)

#166

Post by mr_toad »

zby wrote: post #145
galangalalgol wrote: post #2

Depending on how complex a curve, and how many dimensions it is in, couldn't you argues that is essentially what our brains do as well? Not that I am defending the massive hype field that is ML today, but curve fitting is a form of intelligence.

What our brains do is curve fitting plus experiments . Causality is learned through experiments - and as children we do a lot of experiments (with moving our limbs etc). With just observations you can have only correlations. For example you can correlate smoke with fire, but only through experiment you can learn that it is fire that causes smoke not the other way around.

Just include time in the model and use lagged features. It’s used all the time in automated time series forecasting.

Re: AI is mostly about curve fitting (2018)

#167

Post by mr_toad »

jonplackett wrote: post #58
Lambdanaut wrote: post #39

Earlier quoted context omitted.

This is kinda just what libraries like pytorch and tensorflow make easy. Architecting neural networks at a higher level and gluing them together.

I guess what I mean is at a much larger scale. Like 1000s of networks or maybe more, like I presume you get in the brain. Is this already what’s happening currently?

On today’s machines you’ll run out of computing power (and money) long before you reached the scale of the human brain.

Re: AI is mostly about curve fitting (2018)

#168

Post by Akababa »

dghughes wrote: post #115
projektfu wrote: post #91

Earlier quoted context omitted.

Anthropomorphizing is dangerous because it leads to metaphor that can both ascribe too much to the subject and create blind spots in the minds of researchers. Saying, for example, "Dogs want love," is fine for the owner but problematic for a researcher because love, as we understand it, is a human state. We'll never really understand what it means for a dog to feel loved. To the ethologist that is not to say that the…

Or people who say "The computer thinks...". No it's a machine that only does what people make it do.

I feel that's just a semantics rabbit hole. "Think" is too broad of a term to be picky about.

Re: AI is mostly about curve fitting (2018)

#169

Post by Akababa »

darksaints wrote: post #117
Veedrac wrote: post #65

The article is less awful than the title. In short, the thesis is that ML seems only able to learn associations, rather than stronger, causal models. It should be fairly obvious that ‘curve fitting’ is a misleading category—these models are clearly learning highly meaningful latent spaces that no prior approaches ever did. But I would agree that the actual high-level ability to make causal inferences seems to be lack…

> But I would agree that the actual high-level ability to make causal inferences seems to be lacking. That should be expected. Humans also lack the ability to make causal inference. The vast majority of us have extremely primitive causal reasoning abilities and get even simple causality wrong. Reasoning about causality in complex systems still isn't a solved problem for humans, and we have entire fields within philos…

I don't quite understand why our ability to teach machines causal reasoning should hinge on the lowest common denominator of human ability. If I interpreted your point correctly, then calculators are an obvious counterexample, and a table of common human arithmetic mistakes doesn't have any bearing on our ability to program calculators.

In terms of causal reasoning for computers, it's more of a "common sense" problem than a reasoning one. In nice, closed systems we can do symbolic computation and automated theorem proving without mistakes. The only reason this doesn't work in the real world is the lack of axioms and consistency.

Re: AI is mostly about curve fitting (2018)

#170

Post by Akababa »

yk wrote: post #136
red75prime wrote: post #88

Earlier quoted context omitted.

> hen you are probably forced to argue that consciousness is very closely related to computation, to the point were a coin flip, or a hello world program has some sliver of consciousness. Why not? Those things have zero-consciousness that is conscious only of itself and which correctly reflects their lack of self-model.

The argument is, if our brains are just a curve fitting machine, then we can dial in the complexity of the computation. Start with a single layer parameter, then two parameter, and so on until we are at the complexity of the brain. By that procedure, we can ask after each parameter, if the machine is now conscious, and I strongly doubt that there is a good answer.

That's an ill-defined question. You can do the same thing with far less vague concepts than consciousness, and I could even ask you the same question about a brain and adding neurons. https://en.wikipedia.org/wiki/Sorites_paradox
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