All language subtitles for 13-Lecture 1 Segment 13 What can AI do - Decision Making.en

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:01,629 --> 00:00:05,870 Okay, so you just saw a tour of the areas of AI. And we'll go into these 2 00:00:05,870 --> 00:00:09,210 throughout the course in a little more depth. But really AI is all around you in a way 3 00:00:09,210 --> 00:00:11,999 that doesn't always categorize so neatly. 4 00:00:11,999 --> 00:00:15,419 In general applied AI is automation of some kind. There's some kind of decision problem you want to 5 00:00:15,419 --> 00:00:18,179 automate, something that's too hard for you to do by hand and you want 6 00:00:18,179 --> 00:00:19,139 computer assistance. 7 00:00:19,139 --> 00:00:23,309 So scheduling--airline rallying, military planning--things like that, regularly done 8 00:00:23,309 --> 00:00:24,109 by AI. 9 00:00:24,109 --> 00:00:28,429 Route planning--every time you go get a traffic map, that's AI. 10 00:00:28,429 --> 00:00:31,869 The search algorithms aren't so different than the kinds of things we'll do when we study search. 11 00:00:31,869 --> 00:00:33,580 Medical diagnosis. 12 00:00:33,580 --> 00:00:36,530 You can input your symptoms. There are medical diagnosis systems that will then 13 00:00:36,530 --> 00:00:40,020 try to figure out the underlying diagnosis. These systems actually in many cases 14 00:00:40,020 --> 00:00:43,810 are very good. There are even cases where they can be better than humans. 15 00:00:43,810 --> 00:00:46,700 Web search engines. Some of you may have used a web search engine... 16 00:00:46,700 --> 00:00:49,730 This has got AI everywhere. It's got some natural language in the text, 17 00:00:49,730 --> 00:00:52,760 there's machine learning in figuring out how to rank results using 18 00:00:52,760 --> 00:00:55,809 multiple kinds of features. It's kind of AI everywhere in these things. 19 00:00:55,809 --> 00:00:58,820 Spam classifiers: you may have noticed that the amount of spam you've got your life, 20 00:00:58,820 --> 00:00:59,809 probably, 21 00:00:59,809 --> 00:01:01,319 shot up while you were young, 22 00:01:01,319 --> 00:01:03,680 right, as kind of people learned how to spam, 23 00:01:03,680 --> 00:01:07,000 and then recently I think it's been under much better control and that has to do 24 00:01:07,000 --> 00:01:09,140 with a lot better, both machine learning 25 00:01:09,140 --> 00:01:13,170 and AI techniques for spam classification. 26 00:01:13,170 --> 00:01:14,810 Automated help-desks, that's AI. 27 00:01:14,810 --> 00:01:18,140 Fraud detection on your credit card, product recommendations when 28 00:01:18,140 --> 00:01:21,520 you go to Amazon--all this stuff is AI. So there are a lot of things 29 00:01:21,520 --> 00:01:25,180 that don't really boil down to challenging a grandmaster at chess, but are 30 00:01:25,180 --> 00:01:28,780 equally applicable to industry's problems today, that come from the 31 00:01:28,780 --> 00:01:30,720 techniques that you're gonna learn about in this course. 2931

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