
Deep Learning might not be a silver bullet - cjauvin
http://lemire.me/blog/2017/01/27/deep-learning-the-silver-bullet/
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webmaven
_> everything evolves by a process akin to natural selection. Nature acquires
an ever growing bag of tricks that are being constantly refined. In effect,
there is an overarching process of trial and error. This is truly general, but
with a major trade-off: it is expensive. Our biology evolved but it took all
of the Earth ecosystem millions of years to produce homo sapiens. Our
technology evolves, but it takes all of the power of human civilization to
keep it going._

This is glossing over the robust modular meta-systems that life and technology
have both developed to preferentially express a broad range of potentially
useful variations.

This makes evolution of life and tech ever more efficient over time, as it
becomes much less likely that any particular random change will produce a non-
viable result.

You might say that the mechanisms of evolution have themselves evolved to
become less expensive.

This isn't about anything as straightforward as error-correction, but really
about increasing the systems' generativity.

Example: a mutation may result in longer legs. This does _not_ require
separate mutations for each affected limb, nor does it require separate
matching mutations to adjust the musculature, ligaments, circulatory system,
skin, nerves, etc. in tandem, because all of those systems are adaptive within
the context of the individual organism.

