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The Mathematics of Artificial Intelligence (2022)

arxiv.org

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Re: The Mathematics of Artificial Intelligence (2022)

#4
After a cursory glance, my feeling is that "The Mathematics of Neuronal Networks" would be a better title?

In recent years, the term "Artificial Intelligence" is often used instead of "Neuronal Networks".

I wouldn't be surprised if this will change again. If there is evidence that it will not and Neuronal Networks are for some reason the optimal medium for intelligence, I would love to read about it.

Re: The Mathematics of Artificial Intelligence (2022)

#6
post #4

After a cursory glance, my feeling is that "The Mathematics of Neuronal Networks" would be a better title? In recent years, the term "Artificial Intelligence" is often used instead of "Neuronal Networks". I wouldn't be surprised if this will change again. If there is evidence that it will not and Neuronal Networks are for some reason the optimal medium for intelligence, I would love to read about it.

Came here to say the same thing. This is not a paper on mathematical artificial intelligence, at last as I understand it, not in the way Goertzel or Hutter write about it. I was actually thinking this would be something like Hutter's universal artificial intelligence.

Re: The Mathematics of Artificial Intelligence (2022)

#8
post #4

After a cursory glance, my feeling is that "The Mathematics of Neuronal Networks" would be a better title? In recent years, the term "Artificial Intelligence" is often used instead of "Neuronal Networks". I wouldn't be surprised if this will change again. If there is evidence that it will not and Neuronal Networks are for some reason the optimal medium for intelligence, I would love to read about it.

This is a very good point. To anyone interested in what Artificial Intelligence looked like before neural networks, the "Artificial Intelligence - A Modern Approach" by Stuart Russell and Peter Norvig is a good book on the subject.

Re: The Mathematics of Artificial Intelligence (2022)

#9
Let L(uy,y) = fy denote a parametric partial differential equation with y being a parameter from a high-dimensional parameter space Y ⊆ Rp and uy the associated solution in a Hilbert space H. After a high-fidelity discretization...

These AI folks are clearly very clever, but they don't actually believe that's got anything to do with how human thinking works, right?

Re: The Mathematics of Artificial Intelligence (2022)

#10
post #4

After a cursory glance, my feeling is that "The Mathematics of Neuronal Networks" would be a better title? In recent years, the term "Artificial Intelligence" is often used instead of "Neuronal Networks". I wouldn't be surprised if this will change again. If there is evidence that it will not and Neuronal Networks are for some reason the optimal medium for intelligence, I would love to read about it.

I like to explain that AI > ML > NN.

Now, NNs are the ones getting results at computer vision and natural language, and more. I think most people would say that other ML approaches are computational statistics. The goalpost for AI keeps moving.

If you are truly interested in the math of AI I think PAC Bayes learning is more appropriate and your book is Understanding Machine Learning [1] (not an easy read). A more gentle intro would be Learning From Data [2]. If someone recommends a book/paper it would be awesome, I'm always on the look.

[1] https://www.cs.huji.ac.il/w~shais/UnderstandingMachineLearni... [2] https://work.caltech.edu/telecourse

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