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Okay, so you just saw a tour of the areas of AI. And we'll go into these
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throughout the course in a little more
depth. But really AI is all around you in a way
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that doesn't always categorize so neatly.
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In general applied AI is automation of
some kind. There's some kind of decision problem you want to
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automate, something that's too hard
for you to do by hand and you want
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computer assistance.
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So scheduling--airline rallying, military
planning--things like that, regularly done
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by AI.
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Route planning--every time you go get a
traffic map, that's AI.
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The search algorithms aren't so different than
the kinds of things we'll do when we study search.
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Medical diagnosis.
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You can input your symptoms. There are
medical diagnosis systems that will then
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try to figure out the underlying
diagnosis. These systems actually in many cases
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are very good. There are even cases where
they can be better than humans.
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Web search engines. Some of you may have
used a web search engine...
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This has got AI everywhere. It's got some natural language in the text,
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there's machine learning in figuring out
how to rank results using
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multiple kinds of features. It's kind of AI
everywhere in these things.
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Spam classifiers: you may have noticed that
the amount of spam you've got your life,
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probably,
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shot up while you were young,
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right, as kind of people learned how to
spam,
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and then recently I think it's been
under much better control and that has to do
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with a lot better, both machine learning
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and AI techniques for spam classification.
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Automated help-desks, that's AI.
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Fraud detection on your
credit card, product recommendations when
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you go to Amazon--all this stuff is AI.
So there are a lot of things
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that don't really boil down to
challenging a grandmaster at chess, but are
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equally applicable to industry's
problems today, that come from the
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techniques that you're gonna learn about
in this course.
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