Re: learning with constraints

JC:
I suspect we can learn just by being
exposed to an input with constraint as an
automatic result of the way we are wired.


GS:
I'm sorry, this sounds like gibberish.
Is that deliberate?


JC: What I was thinking of was the acquisition
of knowledge. For example a favorite beginner
text processing program is to count the
frequency of each character in a text string.
Then to count how frequently one character
is followed by another.

Thus we can say the program has *learnt* how
frequently each character occurs and has
*learnt* how often each character is followed
by each other character.



GS: You can call a sow's ear a "silk purse" and putting it in quotes doesn't
make it any less stupid.



JC: This learning is the result of how the system
(computer) is wired (program) and being given
(exposed to) an input with constraint.



GS: Why worry about wiring? After all, if I put a rain gauge out in my yard
it "learns" how much rain has fallen. No? Yeah, that's the ticket! It
"knows" how much rain has fallen. What is wrong with you that you cling so
tenaciously to such ridiculous notions?



JC: An input
without constraint would make every character
and sequence of characters equally likely and
therefore what would there be to learn?



GS: There's no "constraint" on the input in the original.

JC: There is no reward system involved, it is just
the consequence of the wiring (program) and
the type of input (non random).



GS: You must have left something out of the original description. The input
could be random and the program could still count the frequency of each
letter and the conditional probability of each letter following every other
letter. But who cares? The whole thing is ridiculous.



"JGCASEY" <jgkjcasey@xxxxxxxxxxxx> wrote in message


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