Hello Wilfred,

 LL>> In 2012, a Stanford college professor (Andrew Ng) put together a team
 LL>> of students who built a deep-learning system that analyzed 10 million
 LL>> YouTube video stills and, without any human input at all, created a
 LL>> correct understanding of a cat.

 WvV> I "studied" hardly a dozen cats in my live time, and I probably
understand
 WvV> them just as well... As far as you can understand cats. ;)

How do you know what you think you saw was a cat?  I mean,
just because something has pointy ears, fur, and a tail does
not necessarily mean that it is a cat.  Although it could be.

Generative Adversarial Networks (GANs) - A photo of a cat
is introduced.  This is the definition of a cat.  One network
generates images of cats that it shows to another network.
That other network's job is to determine whether the first
is showing a cat or something that looks like a cat.  With
time, the analysis gets better and better.

That can tell you what a cat is.  But can anyone, or anything,
truly understand cats?

--Lee

-- 
Erections, That's Our Game

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