Re: [Maxima-discuss] ML for symbolic math

[Peter v. S. <pet...@gm...>]

Hello,
John Searle wrote a small book about the position of AI an thinking. To my
delight he had a talk about this on YouTube:
https://m.youtube.com/watch?v=rHKwIYsPXLg
I think that the distinctions he uses could clear the discussion so far. In
short: can a computer think? Yes, a machine like a human can think. But not
so for silicon made computers.
Although humans claim to think, it is only in Descartes' Regulae ad
directionem ingenii that for the first time a way of thinking was shown. It
was so dangerous to publish this that Descartes ordered it to be published
after his death. Since then many more ways of thinking were discovered.
Once known they can be codified to a program. But as no one knows how our
consciousness works, it is a far cry from thinking.
Of course there are other ways to come to the same result than with these
codifications. Neural networks in computers are  an example. In my view
they are mimicking parts of our biology. They can make hits and mistakes
like we, but much faster. That can be very useful in helpdesks, car
driving, in reaction in a battlefield,etc.
In fact this is already prepared a long time: I can in principle understand
the algorithms in Maxima, but it takes more time than I am want to spend.
For most users: what is the difference? Well, for some it can be dangerous:
if a hedge fund uses neural networks to sail for a big profit, it can be to
their luck or their big loss.
I look forward to Rubi for Maxima, that is rule coded, because it feels
safe 100%. But what for 99.8%? Would I still do that?
The answer is "yes" because even the best algorithms can go beserk. Humans,
helpdesks must come in. As happens.
With friendly greetings,
Peter

Op wo 2 okt. 2019 22:13 schreef Gunter Königsmann <gu...@pe...>:

> In my experience Blockchain, xxxML and AI are buzzwords that stand for
> claims that are often hard to believe: You could say Mathematics itself
> is a try to find a language that contains only a few handfuls of words,
> not a lot of grammatical rules and in which you can solve many a problem
> just by reformulating it. If you find a less ambiguous way to express
> the things you can epress as an equation you can claim this to be a ML.
> But you didn't gain anything magic mathematics didn't originally contain.
>
> If you use a lot of raw computing power and beat a human being in doing
> anything that can be solved using raw computing power you have won a
> chess game. But if the program just looks forward many steps and looks
> if what you do looks like winning (like big blue did) or if you train an
> AI that does the same except you don't know which criterion it chose as
> "looks like winning" that looks like magic. But it doesn't tell the
> computer is intelligent. And when you then find out that your artificial
> "intelligence" when trained to look for street signs just looks for the
> lower edge, ignores the number and thinks this must be a Stop sign. Or
> if it is completely confused by noise you see what AI is: A mechanism
> that mimics the magic our brain uses for getting a first impression of
> whatever you look at or hear in the first moment.
>
> Showing a trained mathematician an expression and asking this persion
> "Does this look familiar? What do you think the integral looks like"
> definitively is a valid method that might be faster or more exact than
> using a list of integral tables and trying things out. But it isn't a
> silver bullet. Asking an AI will have similar, but not exactly the same
> result as you try to imitate a brain but don't actually use it.
>
> Giving an AI a list of valid operations that cannot go wrong, a bunch of
> equations and telling it to find an algorithm that solves most of these
> problems using educated guesses woud be another approach. This approach
> might actually result in creative algorithms as you can tell the AI to
> use 1000 years of CPU time and an AI is fast. It can result in
> algorithms that only work for this set of data or it can result in
> algorithms that are hideously complex and maybe if anyone finds out what
> they actually do something quite simple and obvious. If such an
> algorithm actually works perhaps it will be documented good enough that
> we can translate it into lisp code.
>
> That is at least my opinion.
>
>
>
>
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