1 00:00:00,080 --> 00:00:02,120 Hey there! I’m Jabril. 2 00:00:02,120 --> 00:00:04,759 John Green Bot: And I am John Green Bot 3 00:00:04,760 --> 00:00:08,160 and welcome to Crash Course Artificial Intelligence. 4 00:00:08,160 --> 00:00:10,780 Now, I want to make sure we’re starting on the same page. 5 00:00:10,780 --> 00:00:12,740 Artificial intelligence is everywhere. 6 00:00:12,750 --> 00:00:17,180 It’s helping banks make loan decisions, and helping doctors diagnose patients, it’s 7 00:00:17,180 --> 00:00:21,450 on our cell phones, autocompleting texts, it’s the algorithm recommending YouTube 8 00:00:21,450 --> 00:00:23,199 videos to watch after this one! 9 00:00:23,199 --> 00:00:26,710 AI already has a pretty huge impact on all of our lives. 10 00:00:26,710 --> 00:00:30,610 So people, understandably, have some polarized feelings about it. 11 00:00:30,610 --> 00:00:35,410 Some of us imagine that AI will change the world in positive ways, it could end car accidents 12 00:00:35,410 --> 00:00:40,120 because we have self-driving cars, or it could give the elderly great, personalized care. 13 00:00:40,120 --> 00:00:44,080 Others worry that AI will lead to constant surveillance by a Big Brother government. 14 00:00:44,080 --> 00:00:46,310 Some say that automation will take all our jobs. 15 00:00:46,310 --> 00:00:50,200 Or the robots might try and kill us all. 16 00:00:50,200 --> 00:00:52,380 No, we’re not worried about you John Green Bot. 17 00:00:52,380 --> 00:00:55,860 But when we interact with AI that’s currently available like Siri... 18 00:00:55,860 --> 00:00:58,020 Hey Siri. 19 00:00:58,020 --> 00:01:00,300 Is AI going to kill us all?” 20 00:01:00,300 --> 00:01:03,500 Siri: “I don’t understand ‘Is AI going to kill us all.’” 21 00:01:03,500 --> 00:01:06,680 … it’s clear that those are still distant futures. 22 00:01:06,680 --> 00:01:11,940 Now to understand where artificial intelligence might be headed, and our role in the AI revolution, 23 00:01:11,940 --> 00:01:15,340 we have to understand how we got to where we are today. 24 00:01:15,340 --> 00:01:24,340 [INTRO] 25 00:01:24,340 --> 00:01:29,120 If you know about artificial intelligence mostly from movies or books, AI probably seems 26 00:01:29,120 --> 00:01:32,640 like this vague label for any machine that can think like a human. 27 00:01:32,640 --> 00:01:37,500 Fiction writers like to imagine a more generalized AI, one that can answer any question we might 28 00:01:37,500 --> 00:01:39,760 have, and do anything a human can do. 29 00:01:39,760 --> 00:01:45,800 But that’s a pretty rigid way to think about AI and it’s not super realistic. 30 00:01:45,800 --> 00:01:49,880 Sorry John Green-bot, you can’t do all that yet. 31 00:01:49,880 --> 00:01:54,880 A machine is said to have artificial intelligence if it can interpret data, potentially learn 32 00:01:54,880 --> 00:01:59,540 from the data, and use that knowledge to adapt and achieve specific goals. 33 00:01:59,540 --> 00:02:04,480 Now, the idea of “learning from the data” is kind of a new approach. 34 00:02:04,480 --> 00:02:05,950 But we’ll get into that more in episode 4. 35 00:02:05,960 --> 00:02:10,480 So let’s say we load up a new program in John Green-bot. 36 00:02:18,280 --> 00:02:22,950 This program looks at a bunch of photos, some of me and some of not of me, and then learns 37 00:02:22,950 --> 00:02:24,120 from those data. 38 00:02:24,120 --> 00:02:28,170 Then, we can show him a new photo, like this selfie of me here in the studio filming this 39 00:02:28,170 --> 00:02:32,360 Crash Course video, and we’ll see if he can recognize that the photo is me. 40 00:02:32,360 --> 00:02:38,160 John Green Bot: You are Jabril. 41 00:02:38,160 --> 00:02:42,340 If he can correctly classify that new photo, we could say that John Green-bot has some 42 00:02:42,340 --> 00:02:43,970 artificial intelligence! 43 00:02:43,970 --> 00:02:49,270 Of course, that’s a very specific input of photos, and a very specific task of classifying 44 00:02:49,270 --> 00:02:53,120 a photo that’s either me or not me. 45 00:02:53,120 --> 00:02:57,390 With just that program John Green-bot can’t recognize or name anyone who /isn’t/ me… 46 00:02:57,390 --> 00:03:01,450 John Green Bot: You are not Jabril. 47 00:03:01,450 --> 00:03:12,980 He can’t navigate to places. 48 00:03:12,980 --> 00:03:16,880 Or hold a meaningful conversation. 49 00:03:16,880 --> 00:03:18,400 No. 50 00:03:18,400 --> 00:03:20,440 I just don’t get it. 51 00:03:20,440 --> 00:03:26,440 Why would anyone choose a bagel when you have a perfectly good donut right here? 52 00:03:26,440 --> 00:03:32,440 John Green Bot: You are Jabril 53 00:03:32,440 --> 00:03:39,120 Thanks John Green Bot. 54 00:03:39,160 --> 00:03:44,440 He can’t do most things that humans do, which is pretty standard for AI these days. 55 00:03:44,440 --> 00:03:49,000 But even with this much more limited definition of artificial intelligence, AI still plays 56 00:03:49,000 --> 00:03:51,520 a huge role in our everyday lives. 57 00:03:51,520 --> 00:03:57,569 There are some more obvious uses of AI, like Alexa or Roomba, which is kind of like the 58 00:03:57,569 --> 00:03:59,890 AI from science fiction I guess. 59 00:03:59,890 --> 00:04:02,660 But there are a ton of less obvious examples! 60 00:04:02,660 --> 00:04:07,790 When we buy something in a big store or online, we have one type of AI deciding which and 61 00:04:07,790 --> 00:04:09,950 how many items to stock. 62 00:04:09,950 --> 00:04:14,680 And as we scroll through Instagram, a different type of AI picks ads to show us. 63 00:04:14,680 --> 00:04:20,809 AI helps determine how expensive our car insurance is, or whether we get approved for a loan. 64 00:04:20,809 --> 00:04:23,479 And AI even affects big life decisions. 65 00:04:23,479 --> 00:04:28,099 Like when you submit your college (or job) application AI might be screening it before 66 00:04:28,099 --> 00:04:29,300 a human even sees it. 67 00:04:29,300 --> 00:04:32,990 The way AI and automation is changing everything, from commerce to jobs, is sort of like the 68 00:04:32,990 --> 00:04:35,830 Industrial Revolution in the 18th century. 69 00:04:35,830 --> 00:04:41,550 This change is global, some people are excited about it, and others are afraid of it. 70 00:04:41,550 --> 00:04:46,159 But either way, we all have the responsibility to understand AI and figure out what role 71 00:04:46,159 --> 00:04:48,229 AI will play in our lives. 72 00:04:48,240 --> 00:04:51,439 The AI revolution itself isn’t even that old. 73 00:04:51,440 --> 00:04:55,360 The term artificial intelligence didn’t even exist a century ago. 74 00:04:55,360 --> 00:04:59,200 It was coined in 1956 by a computer scientist named John McCarthy. 75 00:04:59,210 --> 00:05:03,759 He used it to name the “Dartmouth Summer Research Project on Artificial Intelligence.” 76 00:05:03,759 --> 00:05:06,150 Most people call it the “Dartmouth Conference” for short. 77 00:05:06,150 --> 00:05:10,289 Now, this was way more than a weekend where you listen to a few talks, and maybe go to 78 00:05:10,289 --> 00:05:11,740 a networking dinner. 79 00:05:11,740 --> 00:05:15,189 Back in the day, academics just got together to think for a while. 80 00:05:15,189 --> 00:05:19,729 The Dartmouth Conference lasted eight weeks and got a bunch of computer scientists, cognitive 81 00:05:19,729 --> 00:05:22,779 psychologists, and mathematicians to join forces. 82 00:05:22,779 --> 00:05:26,689 Many of the concepts that we’ll talk about in Crash Course AI, like artificial neural 83 00:05:26,689 --> 00:05:31,009 networks, were dreamed up and developed during this conference and in the few years that 84 00:05:31,009 --> 00:05:32,009 followed. 85 00:05:32,009 --> 00:05:36,809 But because these excited academics were really optimistic about artificial intelligence, 86 00:05:36,809 --> 00:05:38,389 they may have oversold it a bit. 87 00:05:38,389 --> 00:05:43,419 For example, Marvin Minsky was a talented cognitive scientist who was part of the Dartmouth 88 00:05:43,419 --> 00:05:44,499 Conference. 89 00:05:44,499 --> 00:05:49,689 But he also had some ridiculously wrong predictions about technology, and specifically AI. 90 00:05:49,689 --> 00:05:54,449 In 1970, he claimed that in "three to eight years we will have a machine with the general 91 00:05:54,449 --> 00:05:57,000 intelligence of an average human being." 92 00:05:57,000 --> 00:05:58,729 And, uh, sorry Marvin. 93 00:05:58,729 --> 00:06:01,289 We’re not even close to that now. 94 00:06:01,289 --> 00:06:05,059 Scientists at the Dartmouth Conference seriously underestimated how much data and computing 95 00:06:05,059 --> 00:06:08,680 power an AI would need to solve complex, real world problems. 96 00:06:08,680 --> 00:06:13,729 See, an artificial intelligence doesn’t really “know” anything when it’s first 97 00:06:13,729 --> 00:06:15,479 created, kind of like a human baby. 98 00:06:15,479 --> 00:06:20,319 Babies use their senses to perceive the world and their bodies to interact with it, and 99 00:06:20,319 --> 00:06:23,099 they learn from the consequences of their actions. 100 00:06:23,099 --> 00:06:27,350 My baby niece might put a strawberry in her mouth and decide that it’s tasty. 101 00:06:27,350 --> 00:06:30,889 And then she might put play-doh in her mouth and decide that it’s gross. 102 00:06:30,889 --> 00:06:36,379 Babies experience millions of these data-gathering events as they learn to speak, walk, think, 103 00:06:36,379 --> 00:06:37,470 and not eat play-doh. 104 00:06:37,470 --> 00:06:42,080 Now, most kinds of artificial intelligence don’t have things like senses, a body, or 105 00:06:42,080 --> 00:06:46,729 a brain that can automatically judge a lot of different things like a human baby does. 106 00:06:46,729 --> 00:06:49,699 Modern AI systems are just programs in machines. 107 00:06:49,699 --> 00:06:52,599 So we need to give AI a lot of data. 108 00:06:52,599 --> 00:06:57,550 Plus, we have to label the data with whatever information the AI is trying to learn, like 109 00:06:57,550 --> 00:06:59,869 whether food tastes good to humans. 110 00:06:59,869 --> 00:07:04,309 And then, the AI needs a powerful enough computer to make sense of all the data. 111 00:07:04,320 --> 00:07:07,120 All of this just wasn’t available in 1956. 112 00:07:07,120 --> 00:07:12,569 Back then, an AI could maybe tell the difference between a triangle and a circle, but it definitely 113 00:07:12,569 --> 00:07:16,039 couldn’t recognize my face in a photo like John Green-bot did earlier! 114 00:07:16,039 --> 00:07:22,099 So until about 2010 or so, the field was basically frozen in what’s called the AI Winter. 115 00:07:22,099 --> 00:07:27,690 Still there were a lot of changes in the last half a century that led us to the AI Revolution. 116 00:07:27,690 --> 00:07:32,399 As a friend once said: “History reminds us that revolutions are not so much events 117 00:07:32,399 --> 00:07:33,960 as they are processes.” 118 00:07:33,960 --> 00:07:38,880 The AI Revolution didn’t begin with a single event, idea, or invention. 119 00:07:38,880 --> 00:07:43,379 We got to where we are today because of lots of small decisions, and two big developments 120 00:07:43,379 --> 00:07:44,400 in computing. 121 00:07:44,400 --> 00:07:48,830 The first development was a huge increase in computing power and how fast computers 122 00:07:48,840 --> 00:07:50,200 could process data. 123 00:07:50,200 --> 00:07:53,760 To see just how huge, let’s go to the Thought Bubble. 124 00:07:53,760 --> 00:07:59,589 During the Dartmouth Conference in 1956, the most advanced computer was the IBM 7090. 125 00:07:59,589 --> 00:08:04,789 It filled a whole room, stored data on basically giant cassette tapes, and took instructions 126 00:08:04,789 --> 00:08:06,860 using paper punch cards. 127 00:08:06,860 --> 00:08:12,360 Every second, the IBM 7090 could do about 200,000 operations. 128 00:08:12,360 --> 00:08:17,400 But if you tried to do that it would take you 55 and a half hours! 129 00:08:17,409 --> 00:08:21,479 Assuming you did one operation per second, and took no breaks. 130 00:08:21,479 --> 00:08:22,479 That’s right. 131 00:08:22,480 --> 00:08:25,200 Not. Even. For. Snacks. 132 00:08:25,240 --> 00:08:28,960 At the time, that was enough computing power to help with the U.S. Air Force's Ballistic 133 00:08:28,960 --> 00:08:30,120 Missile Warning System. 134 00:08:30,120 --> 00:08:34,960 But AI needs to do a lot more computations with a lot more data. 135 00:08:34,960 --> 00:08:39,720 The speed of a computer is linked to the number of transistors it has to do operations. 136 00:08:39,720 --> 00:08:44,600 Every two years or so since 1956, engineers have doubled the number of transistors that 137 00:08:44,600 --> 00:08:46,760 can fit in the same amount of space. 138 00:08:46,760 --> 00:08:49,190 So computers have gotten much faster. 139 00:08:49,200 --> 00:08:54,720 When the first iPhone was released in 2007, it could do about 400 million operations per second. 140 00:08:54,760 --> 00:08:58,560 But ten years later, Apple says the iPhone X’s processor can 141 00:08:58,560 --> 00:09:01,320 do about 600 billion operations per second. 142 00:09:01,320 --> 00:09:05,480 That’s like having the computing power of over a thousand original iPhones in your pocket. 143 00:09:05,490 --> 00:09:10,370 (For all the nerds out there, listen you’re right, it’s not quite that simple - we’re 144 00:09:10,370 --> 00:09:11,990 just talking about FLOPS here) 145 00:09:11,990 --> 00:09:17,550 And a modern supercomputer, which does computational functions like the IBM 7090 did, can do over 146 00:09:17,550 --> 00:09:20,540 30 quadrillion operations per second. 147 00:09:20,540 --> 00:09:25,710 To put it another way, a program that would take a modern supercomputer one second to 148 00:09:25,710 --> 00:09:31,790 compute, would have taken the IBM 7090 4,753 years. 149 00:09:31,790 --> 00:09:33,290 Thanks Thought Bubble! 150 00:09:33,290 --> 00:09:37,200 So computers started to have enough computing power to mimic certain brain functions with 151 00:09:37,200 --> 00:09:43,760 artificial intelligence around 2005, and that’s when the AI winter started to show signs of thawing. 152 00:09:43,760 --> 00:09:48,440 But it doesn’t really matter if you have a powerful computer unless you also have 153 00:09:48,440 --> 00:09:50,360 a lot of data for it to munch on. 154 00:09:50,360 --> 00:09:54,390 The second development that kicked off the AI revolution is something that you’re using 155 00:09:54,390 --> 00:09:57,250 right now: the Internet and social media. 156 00:09:57,250 --> 00:10:01,410 In the past 20 years, our world has become much more interconnected. 157 00:10:01,410 --> 00:10:05,510 Whether you livestream from your phone, or just use a credit card, we’re all participating 158 00:10:05,510 --> 00:10:06,650 in the modern world. 159 00:10:06,650 --> 00:10:11,460 Every time we upload a photo, click a link, tweet a hashtag, tweet without a hashtag, 160 00:10:11,460 --> 00:10:17,280 like a YouTube video, tag a friend on Facebook, argue on Reddit, post on TikTok [R.I.P. 161 00:10:17,280 --> 00:10:22,660 Vine], support a Kickstarter campaign, buy snacks on Amazon, call an Uber from a party, 162 00:10:22,660 --> 00:10:25,720 and basically ANYTHING, that generates data. 163 00:10:25,720 --> 00:10:29,510 Even when we do something that /seems/ like it’s offline, like applying for a loan to 164 00:10:29,510 --> 00:10:35,320 buy a new car or using a passport at the airport those datasets end up in a bigger system. 165 00:10:35,320 --> 00:10:40,260 The AI revolution is happening now, because we have this wealth of data and the computing 166 00:10:40,260 --> 00:10:42,130 power to make sense of it. 167 00:10:42,130 --> 00:10:43,180 And I get it. 168 00:10:43,180 --> 00:10:47,370 The idea that we’re generating a bunch of data but don’t always know how, why, or 169 00:10:47,370 --> 00:10:51,700 if it’s being used by computer programs can be kind of overwhelming. 170 00:10:51,700 --> 00:10:55,760 But through Crash Course AI, we want to learn how artificial intelligence works because 171 00:10:55,760 --> 00:10:58,320 it’s impacting our lives in huge ways. 172 00:10:58,320 --> 00:11:00,650 And that impact will only continue to grow. 173 00:11:00,650 --> 00:11:05,000 With knowledge, we can make small decisions that will help guide the AI revolution, instead 174 00:11:05,000 --> 00:11:08,320 of feeling like we’re riding a rollercoaster we didn’t sign up for. 175 00:11:08,320 --> 00:11:13,550 We’re creating the future of artificial intelligence together, every single day. 176 00:11:13,550 --> 00:11:15,360 Which I think is pretty cool. 177 00:11:15,360 --> 00:11:20,440 Next time, we’ll start to dive into technical ideas like supervised, unsupervised, and reinforcement 178 00:11:20,440 --> 00:11:21,440 learning. 179 00:11:21,440 --> 00:11:24,590 And we’ll discuss what makes a Machine Learning algorithm good. 180 00:11:24,590 --> 00:11:25,590 See you then! 181 00:11:25,590 --> 00:11:28,360 Thanks to PBS for sponsoring Crash Course AI! 182 00:11:28,360 --> 00:11:31,610 If you want to help keep all Crash Course free for everybody, forever, you can join 183 00:11:31,610 --> 00:11:33,880 our community on Patreon. 184 00:11:33,880 --> 00:11:41,960 And if you want to learn more about how computers got so fast, check out our video on Moore’s Law.