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AI is mostly about curve fitting (2018)

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Re: AI is mostly about curve fitting (2018)

#3

Post by crazygringo »

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.

I was say fundamentally no -- and Douglas Hofstadter is probably the foremost spokesperson against intelligence being curve fitting.

General intelligence is primarily about developing useful conceptual categories (not mapping to existing ones) and drawing cause-and-effect inferences that assist us in achieving goals.

Curve fitting is just another name for pattern recognition, mapping to previously defined categories. I would personally argue there's no intelligence there whatsoever. Intelligence can't exist without a foundation of pattern recognition, but it isn't the same thing.

Intelligence is fundamentally goal-directed and able to reason, while curve-fitting is fundamentally not.

(There is also unsupervised learning in deep learning, which doesn't use previously defined categories, but since it is similarly non-goal-directed, I would still argue that this is merely dimension reduction as opposed to intelligence -- useful for sure, but not the same.)

Re: AI is mostly about curve fitting (2018)

#4

Post by codingslave »

crazygringo wrote: post #3
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.

I was say fundamentally no -- and Douglas Hofstadter is probably the foremost spokesperson against intelligence being curve fitting. General intelligence is primarily about developing useful conceptual categories (not mapping to existing ones) and drawing cause-and-effect inferences that assist us in achieving goals . Curve fitting is just another name for pattern recognition, mapping to previously defined categories…

We dont know anything about AGI, and we arent sure how it would work. Its impossible to make assertions like this

Re: AI is mostly about curve fitting (2018)

#5

Post by petra »

crazygringo wrote: post #3
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.

I was say fundamentally no -- and Douglas Hofstadter is probably the foremost spokesperson against intelligence being curve fitting. General intelligence is primarily about developing useful conceptual categories (not mapping to existing ones) and drawing cause-and-effect inferences that assist us in achieving goals . Curve fitting is just another name for pattern recognition, mapping to previously defined categories…

Reinforcement learning is unsupervised and goal directed.

Re: AI is mostly about curve fitting (2018)

#6

Post by ur-whale »

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.

First, no AI that I know of has at its disposal a full blown model of the world it operates in, whereas most human brains do, and even if the model is imperfect, it is capable of producing fairly accurate simulations (what-if scenarios).

Second, deep learning model, however much we'd like to think they do, aren't capable of doing proper causal inference in a general setting (that is, within the confines of the model) and are therefore far from capable of doing what humans do and will remain so limited for a long time to come.

AGI will require the curve-fitting of deep learning, a general model of the world, the causal inference capabilities of something like AlphaGo, but in a general setting, not the super limited world AlphaGo operates in.

So no, AGI will require much more than just curve-fitting abilities.

Re: AI is mostly about curve fitting (2018)

#7

Post by quikoa »

codingslave wrote: post #4
crazygringo wrote: post #3

Earlier quoted context omitted.

I was say fundamentally no -- and Douglas Hofstadter is probably the foremost spokesperson against intelligence being curve fitting. General intelligence is primarily about developing useful conceptual categories (not mapping to existing ones) and drawing cause-and-effect inferences that assist us in achieving goals . Curve fitting is just another name for pattern recognition, mapping to previously defined categories…

We dont know anything about AGI, and we arent sure how it would work. Its impossible to make assertions like this

Yea I think we just don't know enough. Even if curve fitting alone wouldn't be sufficient it may very well play a crucial role in the agi algorithm.

Re: AI is mostly about curve fitting (2018)

#9

Post by psv1 »

I tend to avoid using the term AI at all and I mostly agree with the article, but I still don't see this as any kind of drawback. Computers are great at curve-fitting and there are many good use-cases for these tasks. We just need to be clear that we are very far from the sci-fi vision of a single computer which can understand, learn and know everything. Which is absolutely fine.

Re: AI is mostly about curve fitting (2018)

#10

Post by zozbot234 »

crazygringo wrote: post #3
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.

I was say fundamentally no -- and Douglas Hofstadter is probably the foremost spokesperson against intelligence being curve fitting. General intelligence is primarily about developing useful conceptual categories (not mapping to existing ones) and drawing cause-and-effect inferences that assist us in achieving goals . Curve fitting is just another name for pattern recognition, mapping to previously defined categories…

It's not like there's a huge difference. Causal inference is a special case of curve-fitting, where one chooses what variables should enter into the fit according to a causal graph.
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