The Automated Composer System at
http://www.asahi-net.or.jp/~HB9T-KTD/music/mus1e.html
got me thinking...what if part of how AI can get implemented, is as a
series of generators of things that most businesses treat as
intellectural property? For example, music: this is but one of the
music generators out there, which basically take centuries-old (or
sometimes much more recent) rules that music students learn, refined
over time into an algorithm, and translate into code. And yet it is
just an extension of these rules, to levels which have not yet been as
refined, that masters of music (big name bands) follow in generating
their art; it seems possible that a neural net, building on a
semi-flexible, semi-rigid (semi-crystal?) foundation of the basic rules,
could listen to these masters over and over until it was able to
generate entirely new tunes which no one (except maybe the band itself)
could not tell from the music makers' actual work.
I know that research similar to this has gone on under the title of
"expert systems" - but those are usually expensive and proprietary
systems. What if, for fields which people without much cash dabble in,
there were a system for a novice to translate the rules he/she learned
into code, then share that code with other hobbyist friends (a few of
which might have some insights into a rarely-used rule, which said
friend could add as a code patch)?
I don't just mean standard "open source" here, though that is a large
part of it. I also mean an easier way to translate human knowledge to
algorithm to code, plus a standard interface for a neural net to plug
into, to brute-force innovation, once the humans generating the base had
exhausted the easy, and possibly even the moderately difficult, wins.
Maybe I'm just rambling here...but this seems like a way people could
automate almost any craft that has been done by anyone for several
years, since a necessary part of building experience is forming an
internal model of the domain. Get a good translation of said domain
into code, and...
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