On Jul 31, 1:26 am, "Stathis Papaioannou" <[EMAIL PROTECTED]> wrote:
> > Popper showed that an infinite number of theories is compatible is any
> > given set of finite observations. Mere algorithmic shuffling to
> > calculate Pr(B) probablities according to the Bayes formula won't help
> > much. Successful induction needs principles to set the priors are set
> > correctly.
> Yes, I was partially agreeing with you. Psychotic people often still
> manage very well with deductive reasoning, but they get the big
> picture wrong, obviously and ridiculously wrong. So there must be more
> to discovering truth about the world than mere algorithmic shuffling.
> Stathis Papaioannou- Hide quoted text -
Ah. Good. Glad to hear you agree. Incidentally, there was a feature
in the last edition of 'New Scientist' in the 'Opinion' section, about
what's wrong with 'excessive rationality':
>The idea is that good mathematics is beautiful. Good music and paintings
often have a deep mathematical structure.
No reason to throw away the math.
True Gunther, but working out math ain't my job, and I don't need it
to built an AI any way. AI's an engineering problem, not a science
problem. I'm not terribly concerned about *what is* (science),....
I'm a lot more interested in *what could be* (creative hacking).
There's far too many geeks on Internet messageboards and blogs
babbling away about abstract theories of *what is* (science). This
detracts from the business of actually working on *what could be*
The *what is* of pure math, has a practical counterpart - the *what
could be* of ontology and computer programming ;) We don't need to
understand the pure math to do the ontology and programming ;) Just
good design principles.
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