Hmm...

The biggest deficiency in related work, that I am aware of, has to do
with an inability to handle context. Symbols are ambiguous and
more-or-less meaningless without context.

Meanwhile, reports on brain activity when a person is reacting to a
joke suggests that the brain uses a sort of hypothesis/confirm/reject
mechanism for handling linguistic recognition - perhaps somewhat
related to simulated annealing (but with something approximating a
scheduled cutoff)?

Then again, given how clueless and awful people can be, I'm not
entirely sure that machine learning by itself is necessarily going to
always be a fruitful activity - I imagine that any such effort will
need support from (presumably mediocre but not entirely inadequate)
fallback mechanisms.

Still, interesting to hear about.

Thanks,

-- 
Raul


On Mon, Nov 9, 2015 at 1:29 PM, Skip Cave <[email protected]> wrote:
> In reference to the recent discussions on Machine Learning and AI, I
> ran across this interesting article..
>
> Shortened URL:
> http://goo.gl/6daIhc
>
> Full URL
> http://techcrunch.com/2015/11/09/google-open-sources-the-machine-learning-tech-behind-google-photos-search-smart-reply-and-more/
>
> Skip
> ----------------------------------------------------------------------
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