Machine Learning (ML) as a method of learning is indeed a
machine, i.e. it operates consistently, repeatedly and predictably, by a
designed method, which is made for specific conditions; but its "learning"
part is more like "training" or "verification" rather than
the acquisition of new knowledge that is suggested in this name. Practically
speaking, ML is made to improve prescribed response formulas, not to invent
such formulas, (and I know the statement might be seemed controversial) not
even to correct them.
Here is then my take
on the issue:
Law #1 A dog (or a
cat) chasing its tail for long enough time will eventually catch it.
Law #2 The catching
will heart!
Law #3 Getting painful results will not stop the chase; it will stop only due to boredom or the exhaustion of all energy resources.
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