1 00:00:00,080 --> 00:00:02,430 The following content is provided under a Creative 2 00:00:02,430 --> 00:00:03,820 Commons license. 3 00:00:03,820 --> 00:00:06,050 Your support will help MIT OpenCourseWare 4 00:00:06,050 --> 00:00:10,150 continue to offer high quality educational resources for free. 5 00:00:10,150 --> 00:00:12,690 To make a donation or to view additional materials 6 00:00:12,690 --> 00:00:16,600 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:16,600 --> 00:00:17,265 at ocw.mit.edu. 8 00:00:26,140 --> 00:00:28,920 PROFESSOR: So today was a little different than yesterday. 9 00:00:28,920 --> 00:00:30,530 So I thought it would be good for us 10 00:00:30,530 --> 00:00:33,480 to just sort of recap what happened. 11 00:00:33,480 --> 00:00:35,860 Let's go back to the sixth graders visit. 12 00:00:35,860 --> 00:00:39,152 Thank you, Jamie, for prepping them for it. 13 00:00:39,152 --> 00:00:40,110 I woke up this morning. 14 00:00:40,110 --> 00:00:42,330 I was like, I didn't prep them for it. 15 00:00:42,330 --> 00:00:44,530 If I were them, I would have been super overwhelmed. 16 00:00:44,530 --> 00:00:45,580 I'm a terrible person. 17 00:00:47,880 --> 00:00:48,919 Was that helpful to you? 18 00:00:48,919 --> 00:00:51,085 What did you guys think about that whole experience? 19 00:00:53,805 --> 00:00:56,130 AUDIENCE: I immediately knew that whatever ideas I had 20 00:00:56,130 --> 00:00:58,694 yesterday was completely off. 21 00:00:58,694 --> 00:01:00,170 And wrong. 22 00:01:00,170 --> 00:01:02,900 180 degrees in the wrong direction. 23 00:01:02,900 --> 00:01:04,400 PROFESSOR: I mean, do take what they 24 00:01:04,400 --> 00:01:08,000 say with a grain of salt. Sixth graders 25 00:01:08,000 --> 00:01:12,150 don't always know how to articulate what they want. 26 00:01:12,150 --> 00:01:17,330 In a pitch, robots always sound cooler than food decomposing. 27 00:01:17,330 --> 00:01:19,930 But there is a way to make that awesome, 28 00:01:19,930 --> 00:01:22,190 if that's really what you're interested in. 29 00:01:22,190 --> 00:01:24,980 So as with everything in this class, 30 00:01:24,980 --> 00:01:27,540 the feedback is ultimately for you 31 00:01:27,540 --> 00:01:31,060 to decide what to do with it. 32 00:01:31,060 --> 00:01:32,650 Was there anything surprising that 33 00:01:32,650 --> 00:01:34,686 came out of the first hour? 34 00:01:39,370 --> 00:01:42,460 I know it's hard to put yourself back into that perspective. 35 00:01:42,460 --> 00:01:45,940 That's what I meant yesterday with the whole thoughtfulness 36 00:01:45,940 --> 00:01:46,600 quality. 37 00:01:46,600 --> 00:01:48,090 One of the values of the class is 38 00:01:48,090 --> 00:01:50,550 being able to take yourself out of the perspective 39 00:01:50,550 --> 00:01:51,780 that you have here. 40 00:01:51,780 --> 00:01:55,490 We were shooting science out loud during the first season 41 00:01:55,490 --> 00:01:58,950 with two grad students who are in AeroAstro. 42 00:01:58,950 --> 00:02:01,520 They were making a video about how engines work. 43 00:02:01,520 --> 00:02:04,610 And we were discussing one of the scenes 44 00:02:04,610 --> 00:02:07,160 that they had planned was to describe a turbine engine. 45 00:02:07,160 --> 00:02:12,360 And I'll go into this more during Thursday's lecture. 46 00:02:12,360 --> 00:02:14,810 But one of the students was trying 47 00:02:14,810 --> 00:02:18,180 to describe that it's the turbine blades that 48 00:02:18,180 --> 00:02:20,000 push the air forward. 49 00:02:20,000 --> 00:02:22,990 And we he was thinking to do an animation with it. 50 00:02:22,990 --> 00:02:25,400 And we thought, this is really complicated. 51 00:02:25,400 --> 00:02:28,160 I couldn't understand what he was trying to say. 52 00:02:28,160 --> 00:02:30,730 And finally, the other student who was there 53 00:02:30,730 --> 00:02:36,210 was like, oh, well there's one Boeing 777 in the hangar 54 00:02:36,210 --> 00:02:37,580 in that building over there. 55 00:02:37,580 --> 00:02:40,530 Like, is it worth filming with it? 56 00:02:40,530 --> 00:02:42,390 And just sort of that mentality of like, 57 00:02:42,390 --> 00:02:46,070 you have access to an actual turbine engine. 58 00:02:46,070 --> 00:02:48,652 And it didn't cross your mind to film it. 59 00:02:48,652 --> 00:02:50,110 And they were awesome to work with. 60 00:02:50,110 --> 00:02:52,410 And you know, that the whole day of shooting 61 00:02:52,410 --> 00:02:55,080 was actually really fun. 62 00:02:55,080 --> 00:02:58,000 But the ability to take yourself out of the things 63 00:02:58,000 --> 00:03:00,650 that your experience all the time, or take for granted. 64 00:03:00,650 --> 00:03:03,610 Creating that window for people who don't necessarily 65 00:03:03,610 --> 00:03:05,930 have access to the world that you live in 66 00:03:05,930 --> 00:03:07,530 is surprisingly difficult to do. 67 00:03:07,530 --> 00:03:10,570 And hopefully the first hour of classes 68 00:03:10,570 --> 00:03:13,430 sort of helped you orient into that new perspective. 69 00:03:13,430 --> 00:03:16,020 But I know that's a challenge for me a lot of times 70 00:03:16,020 --> 00:03:18,090 is, I don't think people are going to think 71 00:03:18,090 --> 00:03:19,320 this is super interesting. 72 00:03:19,320 --> 00:03:22,260 And it's not the content that's not interesting to people. 73 00:03:22,260 --> 00:03:24,450 It's just the delivery. 74 00:03:24,450 --> 00:03:25,450 How you package it up. 75 00:03:27,810 --> 00:03:30,280 PROFESSOR: I think that getting the right angle for-- like, 76 00:03:30,280 --> 00:03:32,590 some of you had really broad topics. 77 00:03:32,590 --> 00:03:33,090 Right? 78 00:03:33,090 --> 00:03:34,890 And the thing that's really hard is 79 00:03:34,890 --> 00:03:37,400 that there are so many things within that topic that 80 00:03:37,400 --> 00:03:39,380 could be really interesting. 81 00:03:39,380 --> 00:03:43,194 And like the food decomposing thing. 82 00:03:43,194 --> 00:03:45,110 Actually think there are a billion really cool 83 00:03:45,110 --> 00:03:47,470 topics in there that could be really fun. 84 00:03:47,470 --> 00:03:51,050 Like cheese is technically mold. 85 00:03:51,050 --> 00:03:53,900 And why is some mold good, and some mold bad. 86 00:03:53,900 --> 00:03:54,400 Right? 87 00:03:54,400 --> 00:03:55,930 And there's some really cool things 88 00:03:55,930 --> 00:03:59,290 like that can do about that. 89 00:03:59,290 --> 00:04:03,360 And getting back to microbiome things, or bacteria, 90 00:04:03,360 --> 00:04:05,340 or there's some really cool stuff in there. 91 00:04:05,340 --> 00:04:07,200 And just like every one of your topics 92 00:04:07,200 --> 00:04:08,560 that you guys brought up. 93 00:04:08,560 --> 00:04:12,080 There's some really cool little pieces 94 00:04:12,080 --> 00:04:13,480 of truths inside of there. 95 00:04:13,480 --> 00:04:15,740 And the hard part is figuring out 96 00:04:15,740 --> 00:04:17,940 how to give-- I mean, this is what writers do, 97 00:04:17,940 --> 00:04:20,080 is having the right angle to your story. 98 00:04:20,080 --> 00:04:20,579 Right? 99 00:04:20,579 --> 00:04:22,850 And so, many-- I think all of what I heard, 100 00:04:22,850 --> 00:04:24,460 I heard many your ideas. 101 00:04:24,460 --> 00:04:26,760 I'm like we're in the right zip code, 102 00:04:26,760 --> 00:04:29,360 but we haven't quite narrowed down the right building yet. 103 00:04:29,360 --> 00:04:29,860 Right? 104 00:04:29,860 --> 00:04:31,310 Or the right street. 105 00:04:31,310 --> 00:04:33,560 And for the hard part is figuring out 106 00:04:33,560 --> 00:04:35,250 within the topic of shipbuilding, 107 00:04:35,250 --> 00:04:39,450 or within the idea of hacking, or building a game, what 108 00:04:39,450 --> 00:04:42,460 is that little cool angle that you're are 109 00:04:42,460 --> 00:04:45,920 going to take to make it really exciting and interesting? 110 00:04:45,920 --> 00:04:48,460 And snare enough and focused enough and that kind of thing 111 00:04:48,460 --> 00:04:49,834 that makes it really interesting. 112 00:04:49,834 --> 00:04:52,977 Because I do think actually that lava sounds cooler 113 00:04:52,977 --> 00:04:55,060 to like a sixth grader because they're like, lava! 114 00:04:55,060 --> 00:04:55,740 That's cook. 115 00:04:55,740 --> 00:04:56,360 Right? 116 00:04:56,360 --> 00:04:58,619 But the food one. 117 00:04:58,619 --> 00:05:00,160 I'm not ready to give up on that yet. 118 00:05:00,160 --> 00:05:02,285 Like, I think there's a lot of cool stuff in there. 119 00:05:02,285 --> 00:05:05,210 And the hard part is figuring out, really 120 00:05:05,210 --> 00:05:07,280 narrowing down your story. 121 00:05:07,280 --> 00:05:09,570 And then figuring out which one has more meat to it. 122 00:05:09,570 --> 00:05:11,170 PROFESSOR: I mean, I think it's a very beautiful story, 123 00:05:11,170 --> 00:05:11,669 actually. 124 00:05:11,669 --> 00:05:14,420 The whole idea of material objects on this earth 125 00:05:14,420 --> 00:05:16,915 transforming in a way that's tangible to us. 126 00:05:16,915 --> 00:05:19,040 And maybe that's just like super romantic sounding. 127 00:05:19,040 --> 00:05:23,840 But I do think that there is-- I loved what Chris said yesterday 128 00:05:23,840 --> 00:05:27,720 about making not just the unfamiliar familiar, 129 00:05:27,720 --> 00:05:29,780 but making the familiar unfamiliar. 130 00:05:29,780 --> 00:05:32,969 And I think that's a lot of what of what VSauce does. 131 00:05:32,969 --> 00:05:34,760 And I think that's a lot of what Veritasium 132 00:05:34,760 --> 00:05:38,660 does is it's taking the things that you see, 133 00:05:38,660 --> 00:05:41,590 and taking the world that you're used to seeing, and showing you 134 00:05:41,590 --> 00:05:43,650 a new lens at looking at it. 135 00:05:43,650 --> 00:05:45,620 And I know that sounds very abstract. 136 00:05:45,620 --> 00:05:48,550 And I'm sure that we've thrown out a lot of things 137 00:05:48,550 --> 00:05:51,260 to think about that you're not maybe quite sure 138 00:05:51,260 --> 00:05:53,230 how to implement on a practical level. 139 00:05:53,230 --> 00:05:56,165 And I promise that that's what we're going to hit next. 140 00:05:56,165 --> 00:05:58,340 And once you guys write a script tonight, 141 00:05:58,340 --> 00:06:00,230 or just try writing it, it'll help 142 00:06:00,230 --> 00:06:02,490 you a lot to sort of understand how 143 00:06:02,490 --> 00:06:04,950 to implement these things practically speaking. 144 00:06:04,950 --> 00:06:05,710 So worry. 145 00:06:05,710 --> 00:06:08,336 I am aware that that might be a frustration that you have. 146 00:06:08,336 --> 00:06:10,960 PROFESSOR: I wonder if we have a little time today to give them 147 00:06:10,960 --> 00:06:13,290 more time to flesh out their ideas a little more. 148 00:06:13,290 --> 00:06:14,123 PROFESSOR: Oh, yeah. 149 00:06:14,123 --> 00:06:14,650 Absolutely. 150 00:06:14,650 --> 00:06:19,320 So I was originally planning on showing you guys 151 00:06:19,320 --> 00:06:21,730 a couple hosting case studies. 152 00:06:21,730 --> 00:06:24,260 But if you would find it more helpful to just 153 00:06:24,260 --> 00:06:26,420 maybe brainstorm script ideas-- 154 00:06:26,420 --> 00:06:27,732 PROFESSOR: I feel like that's where they are right now. 155 00:06:27,732 --> 00:06:28,690 If you think I'm wrong. 156 00:06:28,690 --> 00:06:30,899 But I feel like today made you think a little more. 157 00:06:30,899 --> 00:06:33,190 And now before you go home and have to really implement 158 00:06:33,190 --> 00:06:37,815 some idea, maybe it's worth really making sure each of you 159 00:06:37,815 --> 00:06:39,760 know what you want to do before. 160 00:06:39,760 --> 00:06:40,370 I don't know. 161 00:06:40,370 --> 00:06:42,500 What do you guys think? 162 00:06:42,500 --> 00:06:44,180 I'm feeling some anxiety right now 163 00:06:44,180 --> 00:06:45,680 that like it would help to flesh out 164 00:06:45,680 --> 00:06:47,200 your ideas out a little more. 165 00:06:47,200 --> 00:06:47,700 Yes. 166 00:06:47,700 --> 00:06:48,283 PROFESSOR: OK. 167 00:06:48,283 --> 00:06:49,960 We will totally do that. 168 00:06:49,960 --> 00:06:52,350 I did want to show you something. 169 00:06:52,350 --> 00:06:54,990 Because for me personally, it's hard for me 170 00:06:54,990 --> 00:06:57,630 to hear abstract level ideas. 171 00:06:57,630 --> 00:06:59,630 And I just need to see an example 172 00:06:59,630 --> 00:07:02,400 to help understand that. 173 00:07:02,400 --> 00:07:03,520 So. 174 00:07:03,520 --> 00:07:07,630 And again, I'm not saying that the way I necessarily 175 00:07:07,630 --> 00:07:10,860 do things or the way George or any of the teaching staff 176 00:07:10,860 --> 00:07:13,310 do things is necessarily the best way. 177 00:07:13,310 --> 00:07:16,810 Because again, best is not really been defined. 178 00:07:16,810 --> 00:07:20,300 But this was a video we did during second season. 179 00:07:20,300 --> 00:07:23,530 And it was the first biology video that any of us 180 00:07:23,530 --> 00:07:25,917 had worked on, which I was really excited about. 181 00:07:25,917 --> 00:07:27,375 But it did present these challenges 182 00:07:27,375 --> 00:07:31,450 of like how do you create a visually interesting video 183 00:07:31,450 --> 00:07:33,340 that's worth making as a video. 184 00:07:33,340 --> 00:07:35,840 Because again, I mean, I think asking yourself, 185 00:07:35,840 --> 00:07:37,940 like why do I need to make an animation 186 00:07:37,940 --> 00:07:40,370 about synthetic biology when I could just 187 00:07:40,370 --> 00:07:43,430 create a cartoon about it? 188 00:07:43,430 --> 00:07:46,330 As Chris was saying, visual elements, just 189 00:07:46,330 --> 00:07:50,740 pictorial representations of things are very, very engaging. 190 00:07:50,740 --> 00:07:53,210 We really were asking ourselves, like what's 191 00:07:53,210 --> 00:07:58,430 going to be the visual purpose of her explaining 192 00:07:58,430 --> 00:08:01,220 what basically became a little bit about systems biology, 193 00:08:01,220 --> 00:08:02,600 actually. 194 00:08:02,600 --> 00:08:04,940 And one of the things that we really fixated on, 195 00:08:04,940 --> 00:08:07,950 which is an idea of hers, was a metaphor. 196 00:08:07,950 --> 00:08:10,870 And so this is about a four minute long episode. 197 00:08:10,870 --> 00:08:13,630 Would you guys mind if showed it? 198 00:08:13,630 --> 00:08:15,929 And then we can workshops scripts. 199 00:08:15,929 --> 00:08:16,970 But let me turn off this. 200 00:08:19,874 --> 00:08:22,294 Is the light already off? 201 00:08:22,294 --> 00:08:23,730 You guys can see it OK, right? 202 00:08:23,730 --> 00:08:24,230 OK. 203 00:08:30,861 --> 00:08:32,610 So I'll show this to you guys and maybe we 204 00:08:32,610 --> 00:08:37,049 can un-pack what you've think is successful or not successful 205 00:08:37,049 --> 00:08:37,964 about our attempt. 206 00:08:37,964 --> 00:08:38,630 [VIDEO PLAYBACK] 207 00:08:38,630 --> 00:08:40,046 -Paclitaxel is a compound that can 208 00:08:40,046 --> 00:08:45,720 treat cancer-- Paclitaxel is a compound that can treat cancer. 209 00:08:45,720 --> 00:08:48,380 salicylic acid reduces headaches and fevers. 210 00:08:48,380 --> 00:08:50,910 Carotenoids can turn your skin orange. 211 00:08:50,910 --> 00:08:53,580 And miraculin changes your sense of taste. 212 00:08:53,580 --> 00:08:57,140 What do all of these awesome compounds have in common? 213 00:08:57,140 --> 00:08:59,900 They all come from plants! 214 00:08:59,900 --> 00:09:02,184 [MUSIC PLAYING] 215 00:09:09,340 --> 00:09:12,640 More than 100,000 natural compounds occur in plants 216 00:09:12,640 --> 00:09:15,950 and we barely explore them. 217 00:09:15,950 --> 00:09:19,160 These small molecules are called metabolites. 218 00:09:19,160 --> 00:09:22,360 Just like how all the DNA in an organism forms the genome, 219 00:09:22,360 --> 00:09:25,300 all of the metabolites form the metabolome. 220 00:09:25,300 --> 00:09:28,420 Even though it's metabolite can be made from only six elements, 221 00:09:28,420 --> 00:09:30,790 there are so many possibilities that it 222 00:09:30,790 --> 00:09:33,570 would take scientists thousands of years to make each one try 223 00:09:33,570 --> 00:09:36,400 and figure out its usefulness. 224 00:09:36,400 --> 00:09:39,770 Luckily, plants have already done this for us. 225 00:09:39,770 --> 00:09:43,140 Plants have the disadvantage of being rooted to the ground. 226 00:09:43,140 --> 00:09:46,030 So over time they've trial and errored 227 00:09:46,030 --> 00:09:48,760 making lots of compounds to see which ones help 228 00:09:48,760 --> 00:09:50,920 them survive and thrive best. 229 00:09:50,920 --> 00:09:52,420 And because they've been interacting 230 00:09:52,420 --> 00:09:56,690 with other species like us for 100s of thousands of years, 231 00:09:56,690 --> 00:09:59,220 some of their chemicals turn out to be really useful, 232 00:09:59,220 --> 00:10:02,440 both inside and outside our bodies. 233 00:10:02,440 --> 00:10:04,550 But to use plants to their full potential, 234 00:10:04,550 --> 00:10:07,710 we have to know what chemicals they make and how to make them. 235 00:10:07,710 --> 00:10:09,380 Instead of studying every chemical one 236 00:10:09,380 --> 00:10:13,010 by one, what if we could study all of them at once? 237 00:10:13,010 --> 00:10:15,690 We could start by mapping the huge network that 238 00:10:15,690 --> 00:10:17,400 connects metabolites. 239 00:10:17,400 --> 00:10:19,190 In any living organism, molecules 240 00:10:19,190 --> 00:10:20,750 are always on the move. 241 00:10:20,750 --> 00:10:23,380 Being converted and shuttled, decomposed and built 242 00:10:23,380 --> 00:10:24,970 back up again and re-used. 243 00:10:24,970 --> 00:10:27,706 It's just like a subway system! 244 00:10:27,706 --> 00:10:30,116 Except in biology, the people are the chemicals 245 00:10:30,116 --> 00:10:34,470 and the train is the enzyme that converts and moves them. 246 00:10:34,470 --> 00:10:36,410 If you look at a city from above, 247 00:10:36,410 --> 00:10:39,940 how could you map the whole subway system? 248 00:10:39,940 --> 00:10:42,050 Similarly, if we look at a plant, 249 00:10:42,050 --> 00:10:45,800 how could you figure out the entire metabolome network? 250 00:10:45,800 --> 00:10:47,540 To figure out a path and a system, 251 00:10:47,540 --> 00:10:50,020 what we actually need to do is break it. 252 00:10:50,020 --> 00:10:51,800 If we mutate or disrupt a pathway 253 00:10:51,800 --> 00:10:53,890 and see how the metabolite quantities change, 254 00:10:53,890 --> 00:10:57,420 we could figure out the connections between them. 255 00:10:57,420 --> 00:11:00,450 Let's say the train from Central to MIT breaks. 256 00:11:00,450 --> 00:11:02,730 We wouldn't see students arriving at MIT, 257 00:11:02,730 --> 00:11:05,460 and would instead see them building up at Central. 258 00:11:05,460 --> 00:11:06,690 But not only that. 259 00:11:06,690 --> 00:11:08,600 Anyone else traveling along the red line 260 00:11:08,600 --> 00:11:10,160 would also be affected. 261 00:11:10,160 --> 00:11:12,640 So it's the redistribution of people 262 00:11:12,640 --> 00:11:14,800 which reveals the red line subway path, 263 00:11:14,800 --> 00:11:18,050 and tells us where the train broke. 264 00:11:18,050 --> 00:11:21,320 We can use the systems thinking to uncover the plant metabolite 265 00:11:21,320 --> 00:11:22,090 network. 266 00:11:22,090 --> 00:11:25,070 For example, we know about a compound sinapoyl malate 267 00:11:25,070 --> 00:11:27,280 which protects the plant from UV damage 268 00:11:27,280 --> 00:11:31,200 by interacting with UV light, making the plant grow green. 269 00:11:31,200 --> 00:11:34,090 But without it, the plant would glow red. 270 00:11:34,090 --> 00:11:37,170 So if we see a red plant, it's like seeing no people 271 00:11:37,170 --> 00:11:38,755 at the sinapoyl malate station. 272 00:11:38,755 --> 00:11:41,420 But we wouldn't yet know where the train broke, 273 00:11:41,420 --> 00:11:44,100 or what other stations are along the route. 274 00:11:44,100 --> 00:11:46,500 To do that, we can mutate a lot of seeds, 275 00:11:46,500 --> 00:11:49,360 plant them, and choose the reds ones. 276 00:11:49,360 --> 00:11:51,320 [MUSIC PLAYING] 277 00:11:55,730 --> 00:11:58,715 Now we can analyze these samples by using the mass spectrometer. 278 00:12:02,920 --> 00:12:04,740 It measures how much of each metabolite 279 00:12:04,740 --> 00:12:06,680 is present in the sample. 280 00:12:06,680 --> 00:12:10,190 Then we can use a program to see which compounds were effected 281 00:12:10,190 --> 00:12:11,740 and map that part of the network. 282 00:12:11,740 --> 00:12:14,930 It's like reviewing the red line. 283 00:12:14,930 --> 00:12:17,850 Once we figure out how the entire metabolome works, 284 00:12:17,850 --> 00:12:20,920 we can use it to engineer plants to create new bio materials, 285 00:12:20,920 --> 00:12:22,790 medicines, and clean energy. 286 00:12:22,790 --> 00:12:24,415 We might even discover that plants have 287 00:12:24,415 --> 00:12:26,320 the secret to living forever. 288 00:12:26,320 --> 00:12:28,886 We just need to unlock their chemical mysteries. 289 00:12:28,886 --> 00:12:31,266 [MUSIC PLAYING] 290 00:12:32,694 --> 00:12:34,130 [END PLAYBACK] 291 00:12:34,130 --> 00:12:39,670 PROFESSOR: So Anastasia's topic was-- it 292 00:12:39,670 --> 00:12:41,400 was really hard to visualize. 293 00:12:41,400 --> 00:12:43,520 It mean, if you can imagine, our first meeting 294 00:12:43,520 --> 00:12:46,960 she was talking about basically mapping chemical pathways 295 00:12:46,960 --> 00:12:48,450 in plants. 296 00:12:48,450 --> 00:12:51,190 And it's a hard concept to describe verbally. 297 00:12:51,190 --> 00:12:54,214 And I think that there are some things that we did well 298 00:12:54,214 --> 00:12:54,880 with that video. 299 00:12:54,880 --> 00:12:57,440 I still feel like sometimes it's easy to get 300 00:12:57,440 --> 00:13:03,120 lost in the metaphor that it doesn't really do as precise 301 00:13:03,120 --> 00:13:06,160 of a job as it could. 302 00:13:06,160 --> 00:13:09,340 One of the things I did want to hit though because someone had 303 00:13:09,340 --> 00:13:11,054 asked, how do you know if your idea 304 00:13:11,054 --> 00:13:12,490 is too-- was it you who asked, how 305 00:13:12,490 --> 00:13:14,198 do you know your idea is too big, or not? 306 00:13:16,670 --> 00:13:19,110 You're not going to appeal to everyone. 307 00:13:19,110 --> 00:13:22,310 And you're not going to be the perfect video for every viewer. 308 00:13:22,310 --> 00:13:24,620 And that's OK. 309 00:13:24,620 --> 00:13:29,380 I think understanding your niche is one of the biggest lessons 310 00:13:29,380 --> 00:13:31,590 that I learned in producing Science Out Loud. 311 00:13:31,590 --> 00:13:34,280 At the beginning, our intention and our goal 312 00:13:34,280 --> 00:13:37,370 was to be something like SciShow or VSauce. 313 00:13:37,370 --> 00:13:40,790 Something that kids just sort of watch on their own. 314 00:13:40,790 --> 00:13:44,250 And we quickly realized that that won't necessarily be 315 00:13:44,250 --> 00:13:46,480 the case for us and that's OK. 316 00:13:46,480 --> 00:13:49,840 And that we serve a very powerful function being coupled 317 00:13:49,840 --> 00:13:53,540 in classrooms, or after school programs, or parents 318 00:13:53,540 --> 00:13:55,970 watching them with their kids. 319 00:13:55,970 --> 00:13:59,700 And that'll dictate what concessions you might make. 320 00:13:59,700 --> 00:14:03,090 I mean, in this video, we kind of just 321 00:14:03,090 --> 00:14:05,105 said whoever is going to watch it 322 00:14:05,105 --> 00:14:07,230 is going to understand a little bit about chemistry 323 00:14:07,230 --> 00:14:09,540 and biology. 324 00:14:09,540 --> 00:14:12,660 And that is what allowed us to sort of gloss over 325 00:14:12,660 --> 00:14:17,380 some of the details about chemical pathways. 326 00:14:17,380 --> 00:14:21,750 I think that video worked for us, that there 327 00:14:21,750 --> 00:14:24,330 was a reason that we made that video partially 328 00:14:24,330 --> 00:14:27,860 because Anastasia I think is really good on screen. 329 00:14:27,860 --> 00:14:29,960 And that if you didn't have her, and if you 330 00:14:29,960 --> 00:14:32,820 had just a narrated video or an animation, 331 00:14:32,820 --> 00:14:36,050 it would be a very different visual experience. 332 00:14:36,050 --> 00:14:38,260 I don't know if you guys agree with that or not. 333 00:14:38,260 --> 00:14:40,820 But that's sort of how I felt. 334 00:14:41,990 --> 00:14:45,541 The other thing is, she naturally as a person is really 335 00:14:45,541 --> 00:14:46,040 like that. 336 00:14:46,040 --> 00:14:49,150 She's really jazzed about biology. 337 00:14:49,150 --> 00:14:52,370 It's OK if your personality is not like that. 338 00:14:52,370 --> 00:14:54,640 But the way she wrote her script-- I mean, 339 00:14:54,640 --> 00:14:58,290 she was probably one of the best during the day of shoot 340 00:14:58,290 --> 00:14:59,770 just remembering her lines. 341 00:14:59,770 --> 00:15:01,430 Because the way she wrote her script 342 00:15:01,430 --> 00:15:03,380 was the way that she just sort of talks 343 00:15:03,380 --> 00:15:05,180 about that stuff in real life. 344 00:15:05,180 --> 00:15:08,030 And that was a big tip that I wanted to give you guys 345 00:15:08,030 --> 00:15:11,334 before you started scripting, was right things the way 346 00:15:11,334 --> 00:15:12,250 that you would say it. 347 00:15:12,250 --> 00:15:15,190 And George will talk about this a lot tomorrow, as well. 348 00:15:15,190 --> 00:15:18,790 It's a very, very obvious statement 349 00:15:18,790 --> 00:15:22,480 that is very, very difficult to implement. 350 00:15:22,480 --> 00:15:26,010 I don't know if you guys were pay attention to that in some 351 00:15:26,010 --> 00:15:27,380 of the BioBuilder videos. 352 00:15:27,380 --> 00:15:29,621 their purpose is to be very instructional 353 00:15:29,621 --> 00:15:30,620 like Natalie was saying. 354 00:15:30,620 --> 00:15:34,180 It's like a very encyclopedic type of product. 355 00:15:34,180 --> 00:15:37,510 And it works well in schools, but most people 356 00:15:37,510 --> 00:15:39,660 don't talk in their everyday conversation 357 00:15:39,660 --> 00:15:41,970 like those characters did. 358 00:15:41,970 --> 00:15:44,940 And that's OK for their product. 359 00:15:44,940 --> 00:15:48,860 But if your intent is to engage someone like Hank Green does, 360 00:15:48,860 --> 00:15:50,690 then you have to think about the way 361 00:15:50,690 --> 00:15:52,350 that you're writing your script. 362 00:15:52,350 --> 00:15:56,810 And again that may sound like a very abstract tip. 363 00:15:56,810 --> 00:15:58,490 So what I would say is, if you're 364 00:15:58,490 --> 00:16:01,190 struggling with that in your script, 365 00:16:01,190 --> 00:16:03,530 literally read your words aloud. 366 00:16:03,530 --> 00:16:07,100 And then put your script away so that you can't see it. 367 00:16:07,100 --> 00:16:10,630 And just explain your sentence sort 368 00:16:10,630 --> 00:16:14,840 of ad libbed to someone next to you. 369 00:16:14,840 --> 00:16:16,810 So this happens a lot to me. 370 00:16:16,810 --> 00:16:18,840 I actually went through all the exercises 371 00:16:18,840 --> 00:16:21,160 that you guys are going to do this month myself 372 00:16:21,160 --> 00:16:24,470 to sort of see if what I was saying made sense. 373 00:16:24,470 --> 00:16:27,630 And George and I created an episode about snot. 374 00:16:27,630 --> 00:16:29,964 And the writing process for me was a lot harder for me 375 00:16:29,964 --> 00:16:32,130 than I thought it would be, even though I've coached 376 00:16:32,130 --> 00:16:33,350 so many people through it. 377 00:16:33,350 --> 00:16:35,860 And it was because I fell into this habit 378 00:16:35,860 --> 00:16:37,720 of being super newscastery. 379 00:16:37,720 --> 00:16:40,390 And that's my personal habit that-- I'll say things like, 380 00:16:40,390 --> 00:16:42,350 you think this would do this. 381 00:16:42,350 --> 00:16:44,120 But turns out, it doesn't. 382 00:16:44,120 --> 00:16:45,302 Right? 383 00:16:45,302 --> 00:16:46,760 And I would say, this sounds awful. 384 00:16:46,760 --> 00:16:48,520 And George would take my script away 385 00:16:48,520 --> 00:16:51,840 and he would say, Elizabeth, what is so cool about snot? 386 00:16:51,840 --> 00:16:53,690 And I'd say, well it's awesome because you 387 00:16:53,690 --> 00:16:55,357 think that it's just like this crap that 388 00:16:55,357 --> 00:16:56,315 flows out of your body. 389 00:16:56,315 --> 00:16:58,900 But it turns out that has like all these really amazing things 390 00:16:58,900 --> 00:17:00,220 about it. 391 00:17:00,220 --> 00:17:02,610 And he would say, well you should just say that. 392 00:17:02,610 --> 00:17:07,050 So as you script, or as you try to think of ideas, 393 00:17:07,050 --> 00:17:07,930 turn to your partner. 394 00:17:07,930 --> 00:17:11,950 And just tell them as you would tell anyone what it is 395 00:17:11,950 --> 00:17:14,959 you're trying to convey, what it is you're excited about. 396 00:17:14,959 --> 00:17:17,000 Do you need to do-- want to add anything to that? 397 00:17:17,000 --> 00:17:19,650 PROFESSOR: Well, I think right now 398 00:17:19,650 --> 00:17:22,890 we've got about 35 minutes before the end of class. 399 00:17:22,890 --> 00:17:24,405 And I suspect we have some wrap up 400 00:17:24,405 --> 00:17:26,530 that we need to do to talk about what to do tonight 401 00:17:26,530 --> 00:17:28,329 and what to do to get ready for tomorrow. 402 00:17:28,329 --> 00:17:31,450 So that really puts us more at 20, 25 minutes. 403 00:17:31,450 --> 00:17:32,750 Right? 404 00:17:32,750 --> 00:17:35,090 I feel like maybe what we need to do 405 00:17:35,090 --> 00:17:37,710 is old school actually have each of one of you 406 00:17:37,710 --> 00:17:40,080 think with paper and pen and brainstorm a little. 407 00:17:40,080 --> 00:17:42,540 And then come back together as a group a little bit, 408 00:17:42,540 --> 00:17:45,480 so that you have some time to really conceptualized. 409 00:17:45,480 --> 00:17:47,980 Like if I were to do this on my own, 410 00:17:47,980 --> 00:17:53,000 I'm just saying like, I would actually do an old school 411 00:17:53,000 --> 00:17:54,940 spiderweb to get my ideas out. 412 00:17:54,940 --> 00:17:57,520 Which is-- put this guy down here. 413 00:17:57,520 --> 00:18:00,280 I would actually probably put my topic in the middle 414 00:18:00,280 --> 00:18:02,020 and start brainstorming everything 415 00:18:02,020 --> 00:18:07,730 that I can about it to just keep me thinking about what, like-- 416 00:18:07,730 --> 00:18:11,060 and then to maybe realize if shipbuilding is in the middle 417 00:18:11,060 --> 00:18:14,736 here and we talked about ships, like what specifically 418 00:18:14,736 --> 00:18:16,110 within ships am I thinking about? 419 00:18:16,110 --> 00:18:18,180 Did we want to talk about sea sickness? 420 00:18:18,180 --> 00:18:21,280 All right, then if I wanted to talk sea sickness, 421 00:18:21,280 --> 00:18:23,020 what would I put in my video? 422 00:18:23,020 --> 00:18:23,520 Right? 423 00:18:23,520 --> 00:18:25,410 And to really visualize for yourself, 424 00:18:25,410 --> 00:18:28,630 all the topics, concept, things you would want to film. 425 00:18:28,630 --> 00:18:30,480 And then start getting a sense for yourself 426 00:18:30,480 --> 00:18:32,410 of whether or not this is a doable concept. 427 00:18:32,410 --> 00:18:35,120 And you may realize that actually this 428 00:18:35,120 --> 00:18:37,500 is the branch I want to keep exploring, 429 00:18:37,500 --> 00:18:39,600 as opposed to this whole big thing. 430 00:18:39,600 --> 00:18:41,922 And if this were my brain, that's how this would work. 431 00:18:41,922 --> 00:18:44,130 But if there's a different way that your brain works, 432 00:18:44,130 --> 00:18:46,840 we want you-- I would think that you should use 433 00:18:46,840 --> 00:18:48,930 this time a little bit solo. 434 00:18:48,930 --> 00:18:52,360 And then we'll have a chance to maybe bounce some ideas off. 435 00:18:52,360 --> 00:18:54,190 So I feel like people, at least what 436 00:18:54,190 --> 00:18:56,535 I heard from people was that this morning was 437 00:18:56,535 --> 00:18:57,160 really helpful. 438 00:18:57,160 --> 00:18:58,576 But it made you realize you really 439 00:18:58,576 --> 00:19:00,210 need to narrow your topic and really 440 00:19:00,210 --> 00:19:02,170 think it through a little bit. 441 00:19:02,170 --> 00:19:04,690 So maybe what we do is we spend about 10 minutes quietly 442 00:19:04,690 --> 00:19:08,430 working on our own to really flesh out our concepts. 443 00:19:08,430 --> 00:19:11,180 And then we get back together as a group. 444 00:19:11,180 --> 00:19:12,130 Do you need paper. 445 00:19:12,130 --> 00:19:13,092 I have paper. 446 00:19:13,092 --> 00:19:15,050 Does anyone need-- you need some paper and pen? 447 00:19:15,050 --> 00:19:17,550 I'll go grab them in my office. 448 00:19:17,550 --> 00:19:18,320 I'll go get some. 449 00:19:18,320 --> 00:19:19,236 PROFESSOR: Real quick. 450 00:19:19,236 --> 00:19:21,150 I mean, there are so many strategies. 451 00:19:21,150 --> 00:19:23,250 And some people have different preferences 452 00:19:23,250 --> 00:19:24,800 of beginning to script. 453 00:19:24,800 --> 00:19:26,940 I wasn't going to share this until tonight. 454 00:19:26,940 --> 00:19:29,940 But maybe it would help to do it right now. 455 00:19:29,940 --> 00:19:32,030 So when I was sitting down to script 456 00:19:32,030 --> 00:19:33,914 the snot episode-- and again, I'm 457 00:19:33,914 --> 00:19:35,830 not saying that this is the best way to do it. 458 00:19:35,830 --> 00:19:38,420 Nor am I saying it's the right way to do it. 459 00:19:38,420 --> 00:19:41,202 But I was fixated on the idea that your body 460 00:19:41,202 --> 00:19:42,410 makes a gallon of snot a day. 461 00:19:42,410 --> 00:19:45,950 That was really the seed that began the idea of the episode. 462 00:19:45,950 --> 00:19:48,190 So George, who you'll meet tomorrow, 463 00:19:48,190 --> 00:19:51,100 said, well just list every amazing thing 464 00:19:51,100 --> 00:19:52,850 about snot that you want to talk about. 465 00:19:52,850 --> 00:19:56,360 So I didn't even start with an idea of a story or anything. 466 00:19:56,360 --> 00:20:03,330 All I did was list every sort of fact 467 00:20:03,330 --> 00:20:06,460 about mucus that I was interested in. 468 00:20:06,460 --> 00:20:08,690 And this is sort of the same concept of having a web. 469 00:20:08,690 --> 00:20:10,220 I just put in a list. 470 00:20:10,220 --> 00:20:13,270 But it doesn't really matter. 471 00:20:13,270 --> 00:20:16,850 And as I was going through-- and some of this 472 00:20:16,850 --> 00:20:19,830 was stuff that I had learned in a class I took as an undergrad. 473 00:20:19,830 --> 00:20:23,720 So I was looking through my old notes, basically. 474 00:20:23,720 --> 00:20:25,850 There was a lot of stuff in here. 475 00:20:25,850 --> 00:20:30,270 And I ended up taking out maybe 2/3 of it for the final script. 476 00:20:30,270 --> 00:20:33,560 But this is what got me started. 477 00:20:33,560 --> 00:20:34,870 Mucus as a problem. 478 00:20:34,870 --> 00:20:36,660 Mucus as a solution to things. 479 00:20:36,660 --> 00:20:39,500 Just like random, cool facts about mucus. 480 00:20:39,500 --> 00:20:42,440 The research that's happening. 481 00:20:42,440 --> 00:20:46,320 And just the process of going through all of these things 482 00:20:46,320 --> 00:20:48,040 helped me discover a story. 483 00:20:48,040 --> 00:20:49,720 And just the process did. 484 00:20:49,720 --> 00:20:53,240 So if you would find it helpful to do sort of a brain dump idea 485 00:20:53,240 --> 00:20:55,700 in the next 10 minutes, feel free to do that. 486 00:20:55,700 --> 00:20:57,640 Again, we're not saying that you have 487 00:20:57,640 --> 00:20:59,580 to do any of these methods. 488 00:20:59,580 --> 00:21:02,920 But this is what's helped me personally 489 00:21:02,920 --> 00:21:04,400 in the practice of doing this. 490 00:21:04,400 --> 00:21:07,380 So feel free to do something like this. 491 00:21:07,380 --> 00:21:11,470 I had some ideas of demos I could do. 492 00:21:11,470 --> 00:21:12,290 Ted Ed. 493 00:21:12,290 --> 00:21:14,670 When they recruit people to write scripts, 494 00:21:14,670 --> 00:21:16,570 they have a requirement that you have 495 00:21:16,570 --> 00:21:18,185 a sharable fact in your video. 496 00:21:18,185 --> 00:21:20,560 So what's the fact in the video that's going to go viral? 497 00:21:20,560 --> 00:21:23,270 So I was brainstorming, what could be some shareable facts 498 00:21:23,270 --> 00:21:24,820 in the script? 499 00:21:24,820 --> 00:21:30,600 And then I was thinking about what's the point? 500 00:21:30,600 --> 00:21:31,810 Mucus is alive. 501 00:21:31,810 --> 00:21:34,620 that actually ended up not making the final video at all. 502 00:21:34,620 --> 00:21:36,930 But the exercise and the act of doing that 503 00:21:36,930 --> 00:21:38,930 helped me figure out what the point of the video 504 00:21:38,930 --> 00:21:41,260 was going to be. 505 00:21:41,260 --> 00:21:44,590 PROFESSOR: So let's maybe spend like 5 to 10 minutes 506 00:21:44,590 --> 00:21:48,740 of just quiet time for you to really think about your topic. 507 00:21:48,740 --> 00:21:52,145 And then maybe we can like slowly check in with people, 508 00:21:52,145 --> 00:21:53,520 and then maybe come back together 509 00:21:53,520 --> 00:21:55,478 and see if people are struggling with anything. 510 00:21:57,990 --> 00:21:59,900 I assume that from you're head nods that 511 00:21:59,900 --> 00:22:00,936 sounds like a good plan? 512 00:22:00,936 --> 00:22:01,436 Yes. 513 00:22:01,436 --> 00:22:03,687 OK. 514 00:22:03,687 --> 00:22:07,180 [NO SPEECH] 515 00:24:56,341 --> 00:24:58,210 PROFESSOR: Do you know of omnivores? 516 00:24:58,210 --> 00:24:58,710 What is it? 517 00:24:58,710 --> 00:24:59,472 Not omnivores. 518 00:24:59,472 --> 00:25:00,180 What's it called? 519 00:25:00,180 --> 00:25:00,805 Opportunivores. 520 00:25:03,060 --> 00:25:04,012 AUDIENCE: No. 521 00:25:04,012 --> 00:25:04,970 PROFESSOR: No. 522 00:25:04,970 --> 00:25:09,016 They're people who like running food. 523 00:25:09,016 --> 00:25:09,775 It's like a-- 524 00:25:09,775 --> 00:25:10,360 AUDIENCE: They discover? 525 00:25:10,360 --> 00:25:11,980 PROFESSOR: So I have this great story 526 00:25:11,980 --> 00:25:15,326 I'll have to give you if this is what you decide to do. 527 00:25:15,326 --> 00:25:17,050 A non-fiction piece that was written 528 00:25:17,050 --> 00:25:21,745 by a journalist exploring people who actually live off 529 00:25:21,745 --> 00:25:24,135 of people's decomposing food scraps. 530 00:25:24,135 --> 00:25:25,819 AUDIENCE: Oh, so like freegans? 531 00:25:25,819 --> 00:25:26,610 PROFESSOR: I guess. 532 00:25:26,610 --> 00:25:28,432 Is that another work for it? 533 00:25:28,432 --> 00:25:31,915 Like I know-- I actually do know some people 534 00:25:31,915 --> 00:25:34,040 who their diets is basically composed of free food. 535 00:25:34,040 --> 00:25:34,410 PROFESSOR: Right? 536 00:25:34,410 --> 00:25:35,576 And like what is fermenting? 537 00:25:35,576 --> 00:25:37,380 Fermenting if like beer and cheese. 538 00:25:37,380 --> 00:25:42,030 And like fermenting is a whole other concept in here, right? 539 00:25:42,030 --> 00:25:44,888 Which is actually a really cool concept. 540 00:25:44,888 --> 00:25:45,388 I know. 541 00:25:45,388 --> 00:25:49,284 I kind of was like there's a lot of things like beer and cheese. 542 00:25:49,284 --> 00:25:51,232 And I was like, what isn't there anything 543 00:25:51,232 --> 00:25:52,693 of that I'm interested in? 544 00:25:52,693 --> 00:25:55,160 I guess the conflict I have right now is that is 545 00:25:55,160 --> 00:25:57,076 seems people are more interested in volcanoes. 546 00:25:57,076 --> 00:26:00,120 And that's easier because I actually know a lot about this. 547 00:26:00,120 --> 00:26:02,370 This would be something I'd have to learn about a lot. 548 00:26:02,370 --> 00:26:02,989 PROFESSOR: OK. 549 00:26:02,989 --> 00:26:05,155 AUDIENCE: But that's kind of what I want to do more. 550 00:26:05,155 --> 00:26:05,738 PROFESSOR: OK. 551 00:26:05,738 --> 00:26:08,037 AUDIENCE: Is I want to learn a topic as opposed to just 552 00:26:08,037 --> 00:26:09,120 going in with what I know. 553 00:26:09,120 --> 00:26:12,742 PROFESSOR: What makes you excited about this topic? 554 00:26:12,742 --> 00:26:14,450 AUDIENCE: I don't know anything about it. 555 00:26:14,450 --> 00:26:19,180 And I think that's something that happens a lot. 556 00:26:19,180 --> 00:26:22,880 Whether it's because my dorm hall's 557 00:26:22,880 --> 00:26:24,922 terrible at maintaining our fridge. 558 00:26:24,922 --> 00:26:26,381 And there's always things in there. 559 00:26:26,381 --> 00:26:27,463 PROFESSOR: That's rotting? 560 00:26:27,463 --> 00:26:28,510 AUDIENCE: That's rotting. 561 00:26:28,510 --> 00:26:29,740 And I'm looking at it, and it's like wow. 562 00:26:29,740 --> 00:26:31,680 This is the-- how did this beautiful broccoli 563 00:26:31,680 --> 00:26:35,173 turn into this black muck? 564 00:26:35,173 --> 00:26:38,675 And different things like that. 565 00:26:38,675 --> 00:26:40,800 That's actually something that fascinates me a lot. 566 00:26:40,800 --> 00:26:44,175 Like the transformation. 567 00:26:44,175 --> 00:26:45,650 PROFESSOR: And like why do things-- 568 00:26:45,650 --> 00:26:47,150 AUDIENCE: And like different things. 569 00:26:47,150 --> 00:26:49,602 Why things-- some things decompose in different ways 570 00:26:49,602 --> 00:26:54,160 like where if meats starts to rot, then even if you cook it, 571 00:26:54,160 --> 00:26:56,034 it's not going-- that's not good. 572 00:26:56,034 --> 00:26:56,950 You just can't eat it. 573 00:26:56,950 --> 00:27:01,690 But some things you can kind of like say, well, if you cook it 574 00:27:01,690 --> 00:27:04,280 well enough, it'll be fine. 575 00:27:04,280 --> 00:27:07,580 And also like the whole concept of how you prevent this. 576 00:27:07,580 --> 00:27:09,522 you know like these-- I was looking at it 577 00:27:09,522 --> 00:27:11,230 and there's like all these different ways 578 00:27:11,230 --> 00:27:14,450 that you could prevent-- just like they have the three 579 00:27:14,450 --> 00:27:17,164 topics of like killing things. 580 00:27:17,164 --> 00:27:19,060 How to like bacteria and fungi that cause it. 581 00:27:19,060 --> 00:27:22,378 And it's like attacking like preventing 582 00:27:22,378 --> 00:27:23,800 like their functions. 583 00:27:23,800 --> 00:27:25,510 I think they're like their enzymes. 584 00:27:25,510 --> 00:27:29,814 And then there's more like controlling a growth. 585 00:27:29,814 --> 00:27:31,730 PROFESSOR: So maybe-- I mean I love this story 586 00:27:31,730 --> 00:27:33,989 that you picked. 587 00:27:33,989 --> 00:27:36,030 PS remind me sometime to tell you about the story 588 00:27:36,030 --> 00:27:38,130 I wrote for Backpacker magazine where 589 00:27:38,130 --> 00:27:40,670 I took a whole backpacks worth of food 590 00:27:40,670 --> 00:27:43,580 and saw what rotted over the course of a week 591 00:27:43,580 --> 00:27:45,800 to see what the best foods are to take hiking. 592 00:27:45,800 --> 00:27:48,465 So I did a piece on this in my earlier days 593 00:27:48,465 --> 00:27:49,520 and it was really fun. 594 00:27:49,520 --> 00:27:51,630 But I actually found that there were 595 00:27:51,630 --> 00:27:57,294 maggots that showed up in the completely sealed bologna. 596 00:27:57,294 --> 00:27:58,585 And it grossed me out entirely. 597 00:27:58,585 --> 00:28:00,650 Because you like, they must have been there from the start. 598 00:28:00,650 --> 00:28:01,514 That's terrifying. 599 00:28:01,514 --> 00:28:03,680 AUDIENCE: Yeah, that's-- Yeah. 600 00:28:03,680 --> 00:28:05,350 The things that like start and they-- 601 00:28:05,350 --> 00:28:07,592 with meat and like things that the animal has-- 602 00:28:07,592 --> 00:28:08,300 PROFESSOR: Right. 603 00:28:08,300 --> 00:28:10,640 AUDIENCE: Go through the entire process and they survive. 604 00:28:10,640 --> 00:28:11,270 PROFESSOR: Right. 605 00:28:11,270 --> 00:28:12,894 But the story that I love that you just 606 00:28:12,894 --> 00:28:15,220 told me about was you going into your dorm 607 00:28:15,220 --> 00:28:17,550 and seeing that broccoli and being like, why did this 608 00:28:17,550 --> 00:28:18,050 happen? 609 00:28:18,050 --> 00:28:19,460 And what does it smell so bad? 610 00:28:19,460 --> 00:28:22,345 And you can make your whole five minute piece about that. 611 00:28:22,345 --> 00:28:22,970 AUDIENCE: Yeah. 612 00:28:22,970 --> 00:28:24,428 PROFESSOR: Do you know what I mean? 613 00:28:24,428 --> 00:28:28,300 Like just that little anecdote of you looking in your fridge 614 00:28:28,300 --> 00:28:30,530 and seeing this nasty broccoli and being 615 00:28:30,530 --> 00:28:33,040 like, why does this happen? 616 00:28:33,040 --> 00:28:34,400 That's your story. 617 00:28:34,400 --> 00:28:35,185 You know? 618 00:28:35,185 --> 00:28:35,660 AUDIENCE: And I thought-- 619 00:28:35,660 --> 00:28:37,580 PROFESSOR: And then all this comes from that. 620 00:28:37,580 --> 00:28:39,010 AUDIENCE: It's just like a very big topic. 621 00:28:39,010 --> 00:28:40,510 Because I made my video and I looked 622 00:28:40,510 --> 00:28:43,860 and I don't really go that far into anything. 623 00:28:43,860 --> 00:28:45,485 And it's five minutes already. 624 00:28:45,485 --> 00:28:45,985 You know? 625 00:28:45,985 --> 00:28:46,350 And I've-- 626 00:28:46,350 --> 00:28:48,433 PROFESSOR: But if you were to really narrowly look 627 00:28:48,433 --> 00:28:51,390 at what's going on what that broccoli, 628 00:28:51,390 --> 00:28:53,700 that's actually a really great five minute piece. 629 00:28:53,700 --> 00:28:56,620 AUDIENCE: Because like, I mean, I looked on YouTube. 630 00:28:56,620 --> 00:28:58,580 They have this time-lapse of things decaying. 631 00:28:58,580 --> 00:29:00,770 But there's nothing ever explains why, or how, 632 00:29:00,770 --> 00:29:01,750 or what does it. 633 00:29:01,750 --> 00:29:02,504 PROFESSOR: Right. 634 00:29:02,504 --> 00:29:04,170 AUDIENCE: Like, basically the only thing 635 00:29:04,170 --> 00:29:06,169 that there is on the internet in like video form 636 00:29:06,169 --> 00:29:07,350 is watching things. 637 00:29:07,350 --> 00:29:08,475 But there's no explanation. 638 00:29:08,475 --> 00:29:11,660 PROFESSOR: Of like why does it become so darn smelly? 639 00:29:11,660 --> 00:29:12,421 Right? 640 00:29:12,421 --> 00:29:14,670 AUDIENCE: You know, I can go and read academic papers. 641 00:29:14,670 --> 00:29:16,410 But academic papers are academic papers. 642 00:29:16,410 --> 00:29:16,670 PROFESSOR: Yeah. 643 00:29:16,670 --> 00:29:19,003 But also the question-- I mean, if you think about this, 644 00:29:19,003 --> 00:29:21,710 if your center becomes instead of food decomposition, 645 00:29:21,710 --> 00:29:23,220 but broccoli. 646 00:29:23,220 --> 00:29:23,930 The broccoli. 647 00:29:23,930 --> 00:29:24,480 Right? 648 00:29:24,480 --> 00:29:25,902 Looking at that broccoli. 649 00:29:25,902 --> 00:29:27,360 So many questions come out of that. 650 00:29:27,360 --> 00:29:30,010 Like when is it not OK to eat it? 651 00:29:30,010 --> 00:29:30,850 It looks nasty. 652 00:29:30,850 --> 00:29:32,380 But is it still safe to eat it? 653 00:29:32,380 --> 00:29:34,260 I'm like what's happening in there? 654 00:29:34,260 --> 00:29:37,322 And how long can I expect my broccoli to last? 655 00:29:37,322 --> 00:29:39,030 There's this cool people you might end up 656 00:29:39,030 --> 00:29:41,640 wanting to talk to you. 657 00:29:41,640 --> 00:29:45,130 That I went to an innovation conference last year 658 00:29:45,130 --> 00:29:47,065 the-- I'll have to look up the name. 659 00:29:47,065 --> 00:29:51,200 These people made this device to be able to tell you when you're 660 00:29:51,200 --> 00:29:52,885 food is rotting in your fridge. 661 00:29:52,885 --> 00:29:54,510 And it's an innovation that's happening 662 00:29:54,510 --> 00:29:55,885 on campus that you could actually 663 00:29:55,885 --> 00:29:57,550 go talk to those people. 664 00:29:57,550 --> 00:29:59,490 That they've actually really, really 665 00:29:59,490 --> 00:30:01,430 thought deeply about food waste. 666 00:30:01,430 --> 00:30:04,540 And created a device that attach to your fridge 667 00:30:04,540 --> 00:30:07,170 to tell you like bananas are going bad in three days. 668 00:30:07,170 --> 00:30:08,160 You know? 669 00:30:08,160 --> 00:30:09,500 And they are people on campus. 670 00:30:09,500 --> 00:30:11,000 So I have to think about their name, 671 00:30:11,000 --> 00:30:12,625 but there's this really cool lab that's 672 00:30:12,625 --> 00:30:15,164 actually really exploring this topic that you could talk to. 673 00:30:15,164 --> 00:30:16,580 AUDIENCE: And then I actually just 674 00:30:16,580 --> 00:30:18,231 had a random idea that was completely 675 00:30:18,231 --> 00:30:20,036 unrelated to everything I had before. 676 00:30:20,036 --> 00:30:22,286 Which is the concept of a world without decomposition, 677 00:30:22,286 --> 00:30:23,535 and what that would look like. 678 00:30:23,535 --> 00:30:25,300 PROFESSOR: Why do things die? 679 00:30:25,300 --> 00:30:26,360 Or sort of-- 680 00:30:26,360 --> 00:30:28,527 AUDIENCE: A world in which things did not decompose. 681 00:30:28,527 --> 00:30:30,151 PROFESSOR: What would that looked like? 682 00:30:30,151 --> 00:30:30,830 AUDIENCE: Yeah. 683 00:30:30,830 --> 00:30:32,230 PROFESSOR: Which better gets to the question, 684 00:30:32,230 --> 00:30:32,980 why do things die? 685 00:30:32,980 --> 00:30:33,604 AUDIENCE: Yeah. 686 00:30:33,604 --> 00:30:34,450 PROFESSOR: Right? 687 00:30:34,450 --> 00:30:36,075 AUDIENCE: Well, I mean things would die 688 00:30:36,075 --> 00:30:37,620 but then they would just sit there. 689 00:30:37,620 --> 00:30:38,328 PROFESSOR: Right? 690 00:30:38,328 --> 00:30:39,960 Why do things decompose? 691 00:30:39,960 --> 00:30:42,890 AUDIENCE: And if they had to be broken down by other 692 00:30:42,890 --> 00:30:44,722 means than just bacteria and fungi. 693 00:30:44,722 --> 00:30:46,180 PROFESSOR: The decomposition cycle. 694 00:30:46,180 --> 00:30:46,680 Right? 695 00:30:46,680 --> 00:30:49,750 AUDIENCE: Without a need for carbon and nitrogen cycles. 696 00:30:49,750 --> 00:30:51,940 PROFESSOR: That's much conceptually harder 697 00:30:51,940 --> 00:30:55,280 than a concrete broccoli. 698 00:30:55,280 --> 00:30:58,160 But you can allude to this in the exploration 699 00:30:58,160 --> 00:30:59,045 of that broccoli. 700 00:30:59,045 --> 00:31:00,045 Do you know what I mean? 701 00:31:00,045 --> 00:31:00,330 AUDIENCE: Yeah. 702 00:31:00,330 --> 00:31:02,800 PROFESSOR: By looking at one thing really, really deeply, 703 00:31:02,800 --> 00:31:06,780 you actually allow yourself the ability to abstract from it. 704 00:31:06,780 --> 00:31:09,470 That-- think for a few minutes about that broccoli. 705 00:31:09,470 --> 00:31:10,940 A little more. 706 00:31:10,940 --> 00:31:13,500 Cool 707 00:31:13,500 --> 00:31:15,790 How are you doing? 708 00:31:15,790 --> 00:31:17,414 AUDIENCE: After talking to [INAUDIBLE], 709 00:31:17,414 --> 00:31:19,410 I realized probably my initial idea 710 00:31:19,410 --> 00:31:27,144 is I want to go into talking about how 711 00:31:27,144 --> 00:31:28,392 we go from [INAUDIBLE]. 712 00:31:33,714 --> 00:31:34,380 PROFESSOR: Time? 713 00:31:34,380 --> 00:31:35,378 AUDIENCE: Yeah. 714 00:31:35,378 --> 00:31:36,376 I will think of that. 715 00:31:36,376 --> 00:31:40,867 And then another topic, closely related topic [INAUDIBLE]. 716 00:31:40,867 --> 00:31:45,358 The one I submitted was the pre-conceptual time traveling. 717 00:31:47,860 --> 00:31:49,630 PROFESSOR: Is time travel even possible? 718 00:31:49,630 --> 00:31:50,100 Is that the question? 719 00:31:50,100 --> 00:31:50,330 AUDIENCE: No. 720 00:31:50,330 --> 00:31:50,829 Not really. 721 00:31:50,829 --> 00:31:54,220 More along the lines of problems with time traveling. 722 00:31:54,220 --> 00:31:56,658 Like for example, there's the grandfather paradox. 723 00:31:56,658 --> 00:32:00,081 And then the idea and theory of the multiverse universe. 724 00:32:00,081 --> 00:32:04,000 And multiverse theory [INAUDIBLE]. 725 00:32:04,000 --> 00:32:05,820 PROFESSOR: But I mean, even like the idea 726 00:32:05,820 --> 00:32:10,480 of like is time travel possible is a really cool concept. 727 00:32:10,480 --> 00:32:12,180 AUDIENCE: But it's really broad. 728 00:32:12,180 --> 00:32:12,680 Right? 729 00:32:12,680 --> 00:32:16,142 AUDIENCE: That's why I decided not to delve into time travel, 730 00:32:16,142 --> 00:32:16,850 if it's possible. 731 00:32:16,850 --> 00:32:19,720 Rather looking at what happened-- 732 00:32:19,720 --> 00:32:21,280 why concepts for then. 733 00:32:21,280 --> 00:32:22,310 I think maybe it's-- 734 00:32:22,310 --> 00:32:23,085 PROFESSOR: I think you're still too broad. 735 00:32:23,085 --> 00:32:24,120 AUDIENCE: Yeah. 736 00:32:24,120 --> 00:32:26,495 PROFESSOR: What-- to tell me more about what you actually 737 00:32:26,495 --> 00:32:27,955 do in your studies. 738 00:32:27,955 --> 00:32:29,330 AUDIENCE: That's what you think-- 739 00:32:29,330 --> 00:32:31,100 PROFESSOR: But what about-- like, 740 00:32:31,100 --> 00:32:32,891 there's got to be something in there that's 741 00:32:32,891 --> 00:32:35,802 really exciting to you that you could explore. 742 00:32:35,802 --> 00:32:36,760 AUDIENCE: I mean, yeah. 743 00:32:36,760 --> 00:32:41,257 But I really doubt kids would even 744 00:32:41,257 --> 00:32:47,110 really want to see how a computer does information. 745 00:32:47,110 --> 00:32:48,631 Because mostly I do AI. 746 00:32:48,631 --> 00:32:51,692 So, it's lot-- It's to do a lot with like filtering 747 00:32:51,692 --> 00:32:55,225 of information and deciding what we do with our information. 748 00:32:55,225 --> 00:32:58,950 PROFESSOR: But I mean, this came up with a different group. 749 00:32:58,950 --> 00:33:01,649 Which is when type-- filtering information's actually 750 00:33:01,649 --> 00:33:02,440 really interesting. 751 00:33:02,440 --> 00:33:04,330 Like when I Google something, how 752 00:33:04,330 --> 00:33:08,270 does my computer know what to send me? 753 00:33:08,270 --> 00:33:10,370 That's actually a really interesting question. 754 00:33:10,370 --> 00:33:10,870 Right? 755 00:33:10,870 --> 00:33:13,822 If I'm using Google Shopper, how does it know-- 756 00:33:13,822 --> 00:33:15,030 AUDIENCE: Identify what you-- 757 00:33:15,030 --> 00:33:15,970 PROFESSOR: You know? 758 00:33:15,970 --> 00:33:19,282 And explaining that like a system. 759 00:33:19,282 --> 00:33:22,103 That's actually interesting. 760 00:33:22,103 --> 00:33:24,436 AUDIENCE: Bringing that layman terms can be challenging. 761 00:33:24,436 --> 00:33:26,720 PROFESSOR: But important. 762 00:33:26,720 --> 00:33:27,710 Right? 763 00:33:27,710 --> 00:33:29,270 AUDIENCE: That would be quite hard. 764 00:33:29,270 --> 00:33:31,395 PROFESSOR: I mean, is it possible to pick something 765 00:33:31,395 --> 00:33:35,160 that you do that's conceptually hard but to really flesh it 766 00:33:35,160 --> 00:33:38,080 out to challenge yourself to think about how 767 00:33:38,080 --> 00:33:40,780 to describe that or show that. 768 00:33:40,780 --> 00:33:42,140 Like the train concept. 769 00:33:42,140 --> 00:33:43,240 A little bit hard. 770 00:33:43,240 --> 00:33:44,310 But I kind of got it. 771 00:33:44,310 --> 00:33:45,269 Right? 772 00:33:45,269 --> 00:33:47,685 Is there something that you could-- something in your work 773 00:33:47,685 --> 00:33:49,185 that you're passionate about and you 774 00:33:49,185 --> 00:33:52,730 know a lot about that you think is actually 775 00:33:52,730 --> 00:33:56,710 really useful for the public to know, as well. 776 00:33:56,710 --> 00:33:59,110 AUDIENCE: That's really hard to think about. 777 00:33:59,110 --> 00:34:01,186 I honestly don't think anything's 778 00:34:01,186 --> 00:34:04,500 that relevant to the public. 779 00:34:04,500 --> 00:34:07,490 PROFESSOR: What do you want to do with your degree? 780 00:34:07,490 --> 00:34:08,989 AUDIENCE: Probably robotics, itself. 781 00:34:08,989 --> 00:34:09,572 PROFESSOR: OK. 782 00:34:09,572 --> 00:34:10,960 Robots are really cool topics. 783 00:34:10,960 --> 00:34:14,198 So what about-- what about robots? 784 00:34:14,198 --> 00:34:16,300 AUDIENCE: They contain information. 785 00:34:16,300 --> 00:34:18,929 Probably how they input-- how they take input 786 00:34:18,929 --> 00:34:20,820 and how they decide what to do. 787 00:34:20,820 --> 00:34:23,300 PROFESSOR: Great this is an awesome topic. 788 00:34:23,300 --> 00:34:25,319 Can you think of one very specific question 789 00:34:25,319 --> 00:34:27,300 that you could answer, ask a robot, 790 00:34:27,300 --> 00:34:30,040 and how it would be able to figure out the answer it? 791 00:34:30,040 --> 00:34:30,540 Yes or no? 792 00:34:30,540 --> 00:34:35,524 Have you ever design a simple robot or a simple machine? 793 00:34:35,524 --> 00:34:37,420 AUDIENCE: Really rudimentary. 794 00:34:37,420 --> 00:34:42,909 PROFESSOR: Or like is there any way of very simply showing 795 00:34:42,909 --> 00:34:44,789 how a machine makes a decision? 796 00:34:50,303 --> 00:34:51,719 I'm trying-- you know what I mean? 797 00:34:51,719 --> 00:34:53,094 What I'm trying to push you to do 798 00:34:53,094 --> 00:34:55,250 is think about it robotics were exciting to you, 799 00:34:55,250 --> 00:34:56,295 is there one teeny-- 800 00:34:56,295 --> 00:34:58,530 AUDIENCE: The concept behind them are quite abstract. 801 00:34:58,530 --> 00:35:00,430 That's the thing. 802 00:35:00,430 --> 00:35:04,600 They're really like mathematically behaving. 803 00:35:04,600 --> 00:35:05,850 That's why I'm thinking of it. 804 00:35:05,850 --> 00:35:08,603 I'm not sure how really it can be brought across. 805 00:35:08,603 --> 00:35:12,054 Or whether is should be brought across in that space. 806 00:35:12,054 --> 00:35:15,330 So I was actually exploring something maybe a bit more. 807 00:35:15,330 --> 00:35:19,330 Maybe more on like a pain. 808 00:35:19,330 --> 00:35:22,582 I was a medic back in the military. 809 00:35:22,582 --> 00:35:24,760 So dealt with a lot. 810 00:35:24,760 --> 00:35:26,913 Like every day we see people coming in 811 00:35:26,913 --> 00:35:28,296 and looking for pain killers. 812 00:35:28,296 --> 00:35:32,432 So maybe a bit more like for people to understand better. 813 00:35:32,432 --> 00:35:34,515 PROFESSOR: Like do I take and Advil or an aspirin? 814 00:35:34,515 --> 00:35:35,730 Like do I take a-- 815 00:35:35,730 --> 00:35:36,522 AUDIENCE: They're roughly the same thing. 816 00:35:36,522 --> 00:35:37,021 Yeah. 817 00:35:37,021 --> 00:35:37,910 Something like that. 818 00:35:37,910 --> 00:35:40,229 What is the difference in two kinds of medication? 819 00:35:40,229 --> 00:35:42,020 And why do we take one more than the other? 820 00:35:42,020 --> 00:35:43,936 But we just assume more useful than the other. 821 00:35:43,936 --> 00:35:45,370 I don't think so. 822 00:35:45,370 --> 00:35:48,355 It's more like-- it's like doctor, MD. 823 00:35:48,355 --> 00:35:48,855 You know? 824 00:35:48,855 --> 00:35:49,355 OK. 825 00:35:49,355 --> 00:35:51,320 A bit more explanatory around there. 826 00:35:51,320 --> 00:35:53,790 So I was thinking of something like that. 827 00:35:53,790 --> 00:35:57,445 PROFESSOR: But I'd hate to use to not talk about robots when 828 00:35:57,445 --> 00:35:59,070 that's what you're studying, and that's 829 00:35:59,070 --> 00:36:03,126 what you're passionate about, just because it's hard. 830 00:36:03,126 --> 00:36:05,450 AUDIENCE: I don't think it's because its hard. 831 00:36:05,450 --> 00:36:08,360 I mean, if it were to be an instructional video for someone 832 00:36:08,360 --> 00:36:11,740 at my level, maybe it's not un-doable. 833 00:36:11,740 --> 00:36:14,570 PROFESSOR: But is there anything within robots 834 00:36:14,570 --> 00:36:16,891 that you think is a cool idea. 835 00:36:16,891 --> 00:36:17,390 Simple. 836 00:36:17,390 --> 00:36:19,330 A simple, simple, simple something. 837 00:36:19,330 --> 00:36:22,690 So not everything about how a robot works. 838 00:36:22,690 --> 00:36:27,714 But even how to get-- just something very simple. 839 00:36:27,714 --> 00:36:29,130 I don't know your world old enough 840 00:36:29,130 --> 00:36:32,730 to be able to help you think about what is that thing. 841 00:36:32,730 --> 00:36:34,690 But I challenge you to think for a few minutes 842 00:36:34,690 --> 00:36:39,760 really deeply about what within the robots 843 00:36:39,760 --> 00:36:41,580 is a simple enough concept? 844 00:36:41,580 --> 00:36:42,760 Do you have an idea? 845 00:36:42,760 --> 00:36:43,850 AUDIENCE: I actually-- just listening in 846 00:36:43,850 --> 00:36:45,110 and I know something I think is really cool. 847 00:36:45,110 --> 00:36:46,118 PROFESSOR: What? 848 00:36:46,118 --> 00:36:49,460 AUDIENCE: I very basic on-- but this might still 849 00:36:49,460 --> 00:36:50,412 be too complex. 850 00:36:50,412 --> 00:36:53,101 But probability based maps. 851 00:36:53,101 --> 00:36:54,934 AUDIENCE: Probability-based maps as in based 852 00:36:54,934 --> 00:36:58,190 on the probability of what-- something happening 853 00:36:58,190 --> 00:37:00,610 that you predict what that is? 854 00:37:00,610 --> 00:37:02,062 AUDIENCE: Like when the robot has 855 00:37:02,062 --> 00:37:05,934 to construct a map of an area it doesn't know. 856 00:37:05,934 --> 00:37:06,902 AUDIENCE: Oh, mapping. 857 00:37:06,902 --> 00:37:08,354 Yuck. 858 00:37:08,354 --> 00:37:09,806 Not my favorite project. 859 00:37:09,806 --> 00:37:10,774 Done before. 860 00:37:10,774 --> 00:37:12,649 Yeah. 861 00:37:12,649 --> 00:37:14,440 PROFESSOR: But if you can think-- maybe you 862 00:37:14,440 --> 00:37:17,030 brainstorm for a second about robots 863 00:37:17,030 --> 00:37:22,267 to see if you can get narrow enough that it's a concept. 864 00:37:22,267 --> 00:37:24,600 PROFESSOR: I mean, I think that there's a seedling here. 865 00:37:24,600 --> 00:37:25,272 Right? 866 00:37:25,272 --> 00:37:29,850 But like what is the relate-ability and the drama 867 00:37:29,850 --> 00:37:30,906 that's hooking people in? 868 00:37:30,906 --> 00:37:31,406 Right? 869 00:37:31,406 --> 00:37:33,194 Because I personally think that it's 870 00:37:33,194 --> 00:37:36,042 fascinating that we live in the 21st century with all 871 00:37:36,042 --> 00:37:37,270 these super computers. 872 00:37:37,270 --> 00:37:41,261 Yet this seemingly basic problem of you 873 00:37:41,261 --> 00:37:42,892 have constraints x, y, z. 874 00:37:42,892 --> 00:37:45,390 You can only work four hours in the day. 875 00:37:45,390 --> 00:37:49,650 You need to make chairs and you need to make tables. 876 00:37:49,650 --> 00:37:52,100 What's the optimal number of chairs and tables to make? 877 00:37:52,100 --> 00:37:55,210 Like, that seems like a question that we would be able to solve. 878 00:37:55,210 --> 00:37:59,250 And the fact that we theoretically actually can't is 879 00:37:59,250 --> 00:37:59,750 interesting. 880 00:37:59,750 --> 00:38:02,551 Except there's not enough at stake in that example. 881 00:38:02,551 --> 00:38:03,051 Right? 882 00:38:03,051 --> 00:38:05,973 Like people will say, oh, we lose a couple 883 00:38:05,973 --> 00:38:07,260 cents on making chairs. 884 00:38:07,260 --> 00:38:09,210 Like, that's no big deal. 885 00:38:09,210 --> 00:38:12,790 But if you say something like, because integer programs can't 886 00:38:12,790 --> 00:38:14,790 be solved right now, this is what's 887 00:38:14,790 --> 00:38:20,180 preventing us from knowing-- like this is the reason, or one 888 00:38:20,180 --> 00:38:23,312 of the reasons why companies can only 889 00:38:23,312 --> 00:38:28,510 achieve like certain profit margins, for instance. 890 00:38:28,510 --> 00:38:31,315 What would happen if we can solve integer programs? 891 00:38:31,315 --> 00:38:35,540 Like what would happen to humanity, I guess? 892 00:38:35,540 --> 00:38:36,908 You know? 893 00:38:36,908 --> 00:38:37,702 AUDIENCE: Hm. 894 00:38:37,702 --> 00:38:38,660 PROFESSOR: Do you know? 895 00:38:38,660 --> 00:38:40,402 I mean, I don't know. 896 00:38:40,402 --> 00:38:43,755 AUDIENCE: It's just means that-- when 897 00:38:43,755 --> 00:38:45,756 they say you can't solve a problem, 898 00:38:45,756 --> 00:38:49,632 just saying that you can't solve is easier 899 00:38:49,632 --> 00:38:53,790 than the-- you actually can solve it. 900 00:38:53,790 --> 00:38:55,870 By the way to solve it is to just go 901 00:38:55,870 --> 00:38:57,900 through every single point on the graph 902 00:38:57,900 --> 00:38:59,400 PROFESSOR: So it's very inefficient. 903 00:38:59,400 --> 00:39:00,650 AUDIENCE: It's just complete-- 904 00:39:00,650 --> 00:39:03,503 PROFESSOR: So like it limits us to the types of problems 905 00:39:03,503 --> 00:39:04,044 we can solve. 906 00:39:04,044 --> 00:39:05,466 AUDIENCE: Yes. 907 00:39:05,466 --> 00:39:07,840 AUDIENCE: You can solve it for like very small variables. 908 00:39:07,840 --> 00:39:08,930 Like in this case, it's two variables. 909 00:39:08,930 --> 00:39:09,834 So you can solve it. 910 00:39:09,834 --> 00:39:10,500 PROFESSOR: Yeah. 911 00:39:10,500 --> 00:39:12,550 But you can't solve until you proof the problems. 912 00:39:12,550 --> 00:39:14,285 AUDIENCE: The more variables than-- actually I 913 00:39:14,285 --> 00:39:15,410 was mentioning this before. 914 00:39:15,410 --> 00:39:19,175 I think it's called it n problem. 915 00:39:19,175 --> 00:39:19,800 AUDIENCE: What? 916 00:39:19,800 --> 00:39:22,860 You know how you were saying as long as the number of variables 917 00:39:22,860 --> 00:39:26,225 increased, the number of times you must try exponentially 918 00:39:26,225 --> 00:39:30,000 that you can't really solve the problem. 919 00:39:30,000 --> 00:39:32,773 AUDIENCE: There's a concept called NPI. 920 00:39:32,773 --> 00:39:34,220 Or NP. 921 00:39:34,220 --> 00:39:36,895 So it's about categorizing a problem. 922 00:39:36,895 --> 00:39:39,320 How difficult a problem is. 923 00:39:39,320 --> 00:39:41,497 And if it's harder than this problem-- 924 00:39:41,497 --> 00:39:42,830 PROFESSOR: I think that's very-- 925 00:39:42,830 --> 00:39:47,522 AUDIENCE: Like problem in the world can be made into a type 926 00:39:47,522 --> 00:39:49,447 of problem called a-- I'm forgetting like-- 927 00:39:49,447 --> 00:39:50,822 PROFESSOR: You should write this. 928 00:39:50,822 --> 00:39:53,456 I think like maybe this might be specific enough. 929 00:39:53,456 --> 00:39:54,080 AUDIENCE: Yeah. 930 00:39:54,080 --> 00:39:56,120 This sounds really-- because-- 931 00:39:56,120 --> 00:41:48,110 [INTERPOSING VOICES] 932 00:43:52,050 --> 00:43:55,310 PROFESSOR: You don't have to baby anything down 933 00:43:55,310 --> 00:43:56,130 for the audience. 934 00:43:56,130 --> 00:43:56,400 You know what I mean? 935 00:43:56,400 --> 00:43:58,627 Like you don't have to talk to them like they're ten. 936 00:43:58,627 --> 00:44:00,960 AUDIENCE: Because that helps encourage the conversations 937 00:44:00,960 --> 00:44:01,850 afterward, too. 938 00:44:01,850 --> 00:44:05,650 Because like when I watch a video about something 939 00:44:05,650 --> 00:44:08,640 that I'm unfamiliar with, if I want to learn more 940 00:44:08,640 --> 00:44:11,980 I'll go out and search the words that I don't know. 941 00:44:11,980 --> 00:44:13,580 Like as you with the sixth graders, 942 00:44:13,580 --> 00:44:15,360 maybe they kept asking questions. 943 00:44:15,360 --> 00:44:17,050 If they're curious about something 944 00:44:17,050 --> 00:44:19,680 they'll keep wanting to know about things. 945 00:44:19,680 --> 00:44:22,889 And so-- and they're are a lot more intel-- 946 00:44:22,889 --> 00:44:24,680 you think sixth grade was way too long ago. 947 00:44:24,680 --> 00:44:27,320 But they were very like they're actually intelligent. 948 00:44:27,320 --> 00:44:29,430 They're actually curious. 949 00:44:29,430 --> 00:44:33,220 So you don't want to take out things 950 00:44:33,220 --> 00:44:34,800 that you're saying just because you 951 00:44:34,800 --> 00:44:36,970 think it's too intelligent for them, 952 00:44:36,970 --> 00:44:39,710 or it's too far above their level. 953 00:44:39,710 --> 00:44:42,160 Because if you transition well into it, 954 00:44:42,160 --> 00:44:44,970 if you script it properly, and do the proper build up-- here's 955 00:44:44,970 --> 00:44:46,380 your introduction. 956 00:44:46,380 --> 00:44:48,910 Now these are the details I'm going to talk about. 957 00:44:48,910 --> 00:44:52,350 Then they'll remember some of those details, 958 00:44:52,350 --> 00:44:55,079 and look up the things that they still want to know. 959 00:44:55,079 --> 00:44:57,120 AUDIENCE: Is it OK if we just use the vocabulary, 960 00:44:57,120 --> 00:45:01,549 but instead of the-- because to say what a problem can become 961 00:45:01,549 --> 00:45:02,590 two separate [INAUDIBLE]. 962 00:45:02,590 --> 00:45:04,144 Like a lot of-- 963 00:45:04,144 --> 00:45:04,810 PROFESSOR: Yeah. 964 00:45:04,810 --> 00:45:08,640 So for tonight's assignment, we're 965 00:45:08,640 --> 00:45:10,540 going to have you guys just write 966 00:45:10,540 --> 00:45:12,360 a rough draft of a script. 967 00:45:12,360 --> 00:45:14,630 And at this point, I think it's OK 968 00:45:14,630 --> 00:45:18,690 if you want to err on the side of having too much jargon. 969 00:45:18,690 --> 00:45:19,390 That's OK. 970 00:45:19,390 --> 00:45:21,093 Because George and I are going to workshop all the scripts 971 00:45:21,093 --> 00:45:21,910 with you tomorrow. 972 00:45:21,910 --> 00:45:22,880 And we'll-- 973 00:45:22,880 --> 00:45:24,270 It's always a fine balance. 974 00:45:24,270 --> 00:45:26,651 Because you don't want to sit and define everything. 975 00:45:26,651 --> 00:45:27,150 Right? 976 00:45:27,150 --> 00:45:29,441 Like, it's OK to challenge your audience. 977 00:45:29,441 --> 00:45:33,120 You don't want to alienate them by talking in a language 978 00:45:33,120 --> 00:45:34,630 that they don't understand. 979 00:45:34,630 --> 00:45:35,440 Right? 980 00:45:35,440 --> 00:45:36,910 So it's a balance between that. 981 00:45:36,910 --> 00:45:40,390 I think for tonight, we want you just like get something 982 00:45:40,390 --> 00:45:41,500 on paper. 983 00:45:41,500 --> 00:45:43,910 And so don't get too stressed about that. 984 00:45:43,910 --> 00:45:47,290 Really focus on what the overarching story's 985 00:45:47,290 --> 00:45:47,990 going to be. 986 00:45:47,990 --> 00:45:49,573 AUDIENCE: This is day two of the class 987 00:45:49,573 --> 00:45:53,155 and scripts take like a long time to write and refine and-- 988 00:45:53,155 --> 00:45:54,530 PROFESSOR: So we're not expecting 989 00:45:54,530 --> 00:45:55,488 perfection or anything. 990 00:45:57,502 --> 00:45:59,960 AUDIENCE: I'm just concerned about like something like this 991 00:45:59,960 --> 00:46:01,610 because there's no like visual elements 992 00:46:01,610 --> 00:46:02,760 like what you were saying. 993 00:46:02,760 --> 00:46:05,516 PROFESSOR: So do you want me to show you the computer-- Or have 994 00:46:05,516 --> 00:46:05,850 you see the computer? 995 00:46:05,850 --> 00:46:06,350 AUDIENCE: Yeah. 996 00:46:06,350 --> 00:46:07,280 I've seen-- You're talking about the one 997 00:46:07,280 --> 00:46:07,980 where he puts like these pin balls. 998 00:46:07,980 --> 00:46:08,476 PROFESSOR: With the balls. 999 00:46:08,476 --> 00:46:08,976 Yeah. 1000 00:46:14,440 --> 00:46:17,580 I don't know any videos on top of my head. 1001 00:46:17,580 --> 00:46:19,110 But what you might want to try doing 1002 00:46:19,110 --> 00:46:21,570 is just looking on YouTube for maybe 1003 00:46:21,570 --> 00:46:24,356 like VSauce of Veritasium videos that 1004 00:46:24,356 --> 00:46:26,410 were about computer engineering and see 1005 00:46:26,410 --> 00:46:28,090 what they used visually. 1006 00:46:28,090 --> 00:46:32,440 Sometimes it's just their persona like on screen. 1007 00:46:32,440 --> 00:46:34,312 VSauce does that a lot because he 1008 00:46:34,312 --> 00:46:36,310 talks a lot about psychological concepts 1009 00:46:36,310 --> 00:46:38,090 that are sort of hard to visualize. 1010 00:46:38,090 --> 00:46:40,410 And it's just him on screen talking. 1011 00:46:40,410 --> 00:46:44,750 He's just visually engaging that way. 1012 00:46:44,750 --> 00:46:45,250 I do agree. 1013 00:46:45,250 --> 00:46:49,130 This is going to be hard to-- it's going 1014 00:46:49,130 --> 00:46:51,370 to be hard to visualize. 1015 00:46:51,370 --> 00:46:54,290 But maybe this is a place where animations could help. 1016 00:46:54,290 --> 00:46:59,730 And I always think animation should be used sparingly. 1017 00:46:59,730 --> 00:47:02,560 People have a tendency to rely on animation 1018 00:47:02,560 --> 00:47:05,380 because think it's like cheaper, or easier to make. 1019 00:47:05,380 --> 00:47:08,749 And when Josh come in, maybe he and I and you 1020 00:47:08,749 --> 00:47:11,290 can talk a little bit more about how you would implement that 1021 00:47:11,290 --> 00:47:13,430 exactly. 1022 00:47:13,430 --> 00:47:17,914 But having a person with just an animated overlay like you 1023 00:47:17,914 --> 00:47:19,580 saw at the beginning of that video, that 1024 00:47:19,580 --> 00:47:22,770 can be a really simple solution to a way 1025 00:47:22,770 --> 00:47:27,180 to engage people visually. 1026 00:47:27,180 --> 00:47:28,915 But I think the idea is-- personally, 1027 00:47:28,915 --> 00:47:31,834 I think the idea is very fascinating. 1028 00:47:31,834 --> 00:47:37,780 The notion that we live in a world where we think we've 1029 00:47:37,780 --> 00:47:41,150 achieved so much technological prowess. 1030 00:47:41,150 --> 00:47:46,500 But a problem that seems so basic like that understanding 1031 00:47:46,500 --> 00:47:49,370 how to solve four, five, six things 1032 00:47:49,370 --> 00:47:52,350 is actually incredibly challenging. 1033 00:47:52,350 --> 00:47:54,770 And this is why. 1034 00:47:54,770 --> 00:47:57,175 This is the thing that we can conceptualize in our minds 1035 00:47:57,175 --> 00:47:58,127 as human. 1036 00:47:58,127 --> 00:47:59,960 But when you try to get a computer to do it, 1037 00:47:59,960 --> 00:48:03,240 like it's actually impossible. 1038 00:48:03,240 --> 00:48:04,870 It's impossible. 1039 00:48:04,870 --> 00:48:08,340 I went to this talk awhile back given 1040 00:48:08,340 --> 00:48:15,560 by one of the guys who runs the Humanoid Robots Group at MIT. 1041 00:48:15,560 --> 00:48:18,130 And he was saying how it's so hard 1042 00:48:18,130 --> 00:48:20,754 to program a humanoid robot, a bi-pedal robot 1043 00:48:20,754 --> 00:48:22,720 to walk like a human behaves. 1044 00:48:22,720 --> 00:48:25,940 And it's because we walk every day. 1045 00:48:25,940 --> 00:48:26,560 Right? 1046 00:48:26,560 --> 00:48:28,430 And we don't think anything of it. 1047 00:48:28,430 --> 00:48:31,600 But to model the movement of your knee 1048 00:48:31,600 --> 00:48:33,820 bending and putting your foot down, 1049 00:48:33,820 --> 00:48:38,190 it's actually possible to mathematically model 1050 00:48:38,190 --> 00:48:40,736 with a precision of reality. 1051 00:48:40,736 --> 00:48:42,611 And I don't remember the exact math about it. 1052 00:48:42,611 --> 00:48:44,360 But I remember hearing this notion that 1053 00:48:44,360 --> 00:48:49,260 like there's no way in math for us to model something 1054 00:48:49,260 --> 00:48:51,080 that we do in reality every day. 1055 00:48:51,080 --> 00:48:51,920 Right? 1056 00:48:51,920 --> 00:48:56,510 So even if we create like the world's biggest super computer, 1057 00:48:56,510 --> 00:48:59,810 a robot is never going come close to what the human body 1058 00:48:59,810 --> 00:49:02,060 can achieve in their sleep. 1059 00:49:02,060 --> 00:49:02,560 You know? 1060 00:49:02,560 --> 00:49:07,540 And I thought that was such an interesting concept 1061 00:49:07,540 --> 00:49:11,150 that humans are still like so complex, 1062 00:49:11,150 --> 00:49:13,885 even with all the advances we've made in robotics. 1063 00:49:16,960 --> 00:49:18,510 And that was a theme that we tried 1064 00:49:18,510 --> 00:49:22,350 hit in one of our episodes, actually. 1065 00:49:22,350 --> 00:49:24,230 Does that help a little bit? 1066 00:49:24,230 --> 00:49:25,120 I don't know. 1067 00:49:25,120 --> 00:49:28,335 Maybe you just have more questions. 1068 00:49:28,335 --> 00:49:31,209 So at the end of the whole treatise, 1069 00:49:31,209 --> 00:49:35,520 we each will come with a video and post it 1070 00:49:35,520 --> 00:49:36,970 PROFESSOR: Mhm. 1071 00:49:36,970 --> 00:49:37,560 AUDIENCE: OK. 1072 00:49:37,560 --> 00:49:38,520 PROFESSOR: Yep. 1073 00:49:38,520 --> 00:49:39,950 It'll be great. 1074 00:49:39,950 --> 00:49:41,704 AUDIENCE: Can I just picture-- 1075 00:49:41,704 --> 00:49:43,045 AUDIENCE: Sure. 1076 00:49:43,045 --> 00:49:47,710 AUDIENCE: So I mean, I have one of an algorithm. 1077 00:49:47,710 --> 00:49:49,503 And like the simplest algorithm I 1078 00:49:49,503 --> 00:49:52,230 can think of this is one search. 1079 00:49:52,230 --> 00:49:54,841 So I was just thinking like wal-- You know, wal-- 1080 00:49:54,841 --> 00:49:55,840 or whatever you call it. 1081 00:49:59,800 --> 00:50:00,730 Where is Waldo? 1082 00:50:00,730 --> 00:50:01,980 PROFESSOR: Oh, Where is Waldo? 1083 00:50:01,980 --> 00:50:02,605 AUDIENCE: Yeah. 1084 00:50:02,605 --> 00:50:06,680 So like just-- it would probably be like just some guy 1085 00:50:06,680 --> 00:50:07,930 just hiding in the building. 1086 00:50:07,930 --> 00:50:10,660 And then he'll be like, what's the best way to find Waldo? 1087 00:50:10,660 --> 00:50:11,430 PROFESSOR: Yeah. 1088 00:50:11,430 --> 00:50:11,880 AUDIENCE: Yeah. 1089 00:50:11,880 --> 00:50:12,970 Then we'll just be running around. 1090 00:50:12,970 --> 00:50:13,470 Row 1091 00:50:13,470 --> 00:50:14,236 PROFESSOR: Yeah. 1092 00:50:14,236 --> 00:50:15,810 AUDIENCE: Yeah, like-- so first wave, 1093 00:50:15,810 --> 00:50:17,090 open every door in the university 1094 00:50:17,090 --> 00:50:18,180 and you just keep going that way. 1095 00:50:18,180 --> 00:50:18,888 PROFESSOR: Right. 1096 00:50:18,888 --> 00:50:21,510 AUDIENCE: Then there's another way where you keep going up. 1097 00:50:21,510 --> 00:50:24,881 Yeah but then I start to realize that the energy might 1098 00:50:24,881 --> 00:50:26,130 break down somewhere half way. 1099 00:50:26,130 --> 00:50:32,330 Because the algorithm on the [INAUDIBLE] 1100 00:50:32,330 --> 00:50:35,140 was a binary search which is just like, you cut half. 1101 00:50:35,140 --> 00:50:37,960 And then you see whether, is Waldo on the right side 1102 00:50:37,960 --> 00:50:38,894 or the left side? 1103 00:50:38,894 --> 00:50:40,060 And then you cut half again. 1104 00:50:40,060 --> 00:50:41,032 And less, and less. 1105 00:50:41,032 --> 00:50:43,950 PROFESSOR: I think that's very interesting. 1106 00:50:43,950 --> 00:50:49,332 What is the final application of search algorithms? 1107 00:50:49,332 --> 00:50:50,040 AUDIENCE: Google. 1108 00:50:50,040 --> 00:50:50,430 PROFESSOR: Like Google? 1109 00:50:50,430 --> 00:50:51,055 AUDIENCE: Yeah. 1110 00:50:51,055 --> 00:50:52,700 PROFESSOR: Yeah. 1111 00:50:52,700 --> 00:50:55,845 I think as long as you relate it back to the big picture 1112 00:50:55,845 --> 00:50:58,069 of like why that's such an awesome thing. 1113 00:50:58,069 --> 00:50:59,610 Because what you don't want happening 1114 00:50:59,610 --> 00:51:01,400 is people to think like, OK, cool. 1115 00:51:01,400 --> 00:51:02,155 I get that. 1116 00:51:02,155 --> 00:51:03,030 It's a binary search. 1117 00:51:03,030 --> 00:51:04,404 He split things in half and half. 1118 00:51:04,404 --> 00:51:05,490 So what? 1119 00:51:05,490 --> 00:51:06,456 Like why should I care? 1120 00:51:06,456 --> 00:51:06,942 Right? 1121 00:51:06,942 --> 00:51:07,430 AUDIENCE: Yeah. 1122 00:51:07,430 --> 00:51:09,055 PROFESSOR: You should care because it's 1123 00:51:09,055 --> 00:51:13,915 like what drives the most used website in the world. 1124 00:51:13,915 --> 00:51:15,920 And I think relating it back to that-- 1125 00:51:15,920 --> 00:51:18,350 like that's what we tried to do with the switches video. 1126 00:51:18,350 --> 00:51:20,720 Is like, OK I get that the billiard ball 1127 00:51:20,720 --> 00:51:23,070 hit with the switch on or off. 1128 00:51:23,070 --> 00:51:25,866 But we tied it back at the very end 1129 00:51:25,866 --> 00:51:29,845 to say like this toy has 20 switches 1130 00:51:29,845 --> 00:51:32,565 but most computer have like billions of switches. 1131 00:51:32,565 --> 00:51:34,930 And that's what makes a semi-conductor. 1132 00:51:34,930 --> 00:51:38,400 And that's what makes every modern electronic possible. 1133 00:51:38,400 --> 00:51:41,860 As long as you relate back to the big picture, to the thing 1134 00:51:41,860 --> 00:51:44,800 that people relate to, the thing that people use every day. 1135 00:51:44,800 --> 00:51:48,523 I think that can be powerful. 1136 00:51:48,523 --> 00:51:49,064 AUDIENCE: OK. 1137 00:51:51,850 --> 00:51:54,455 PROFESSOR: I mean, I also-- I like this path in GPS thing. 1138 00:51:54,455 --> 00:51:58,360 Like how exactly does a GPS work? 1139 00:51:58,360 --> 00:51:59,950 How do you find your way? 1140 00:51:59,950 --> 00:52:01,520 You know? 1141 00:52:01,520 --> 00:52:04,250 Knowing what-- knowing your location in GPS? 1142 00:52:04,250 --> 00:52:07,665 I know but I was-- like mapping a path, that's 1143 00:52:07,665 --> 00:52:08,830 a different problem. 1144 00:52:08,830 --> 00:52:09,600 PROFESSOR: OK 1145 00:52:09,600 --> 00:52:09,985 AUDIENCE: Yeah. 1146 00:52:09,985 --> 00:52:10,484 GPS-- 1147 00:52:10,484 --> 00:52:13,390 PROFESSOR: It's like how does Google Maps know? 1148 00:52:13,390 --> 00:52:15,740 AUDIENCE: Oh, I see what you mean. 1149 00:52:15,740 --> 00:52:17,504 PROFESSOR: We are about out of time. 1150 00:52:17,504 --> 00:52:19,295 Maybe we should get everyone back together. 1151 00:52:19,295 --> 00:52:20,128 PROFESSOR: Oh, yeah. 1152 00:52:20,128 --> 00:52:20,720 Sorry. 1153 00:52:20,720 --> 00:52:22,000 Thank you, Danny. 1154 00:52:22,000 --> 00:52:23,858 PROFESSOR: I don't have too much to say. 1155 00:52:23,858 --> 00:52:27,280 Except for just the daily assignment. 1156 00:52:27,280 --> 00:52:29,060 So another daily blog. 1157 00:52:29,060 --> 00:52:32,217 Thank you all for posting your stuff on Tumblr yesterday. 1158 00:52:32,217 --> 00:52:34,800 Keep in mind that you don't have to do a text post like I did. 1159 00:52:34,800 --> 00:52:36,555 I just did that as an example. 1160 00:52:36,555 --> 00:52:38,980 But if you guys want to do a video blog. 1161 00:52:38,980 --> 00:52:41,250 If you want to just vlog on your laptop webcam, 1162 00:52:41,250 --> 00:52:42,720 that's totally fine. 1163 00:52:42,720 --> 00:52:44,680 But if you end up taking pictures 1164 00:52:44,680 --> 00:52:47,130 of any of the lectures, or taking videos 1165 00:52:47,130 --> 00:52:50,070 during the lecture, you're free to post those, too. 1166 00:52:50,070 --> 00:52:51,891 And just post them with a hashtag day 1167 00:52:51,891 --> 00:52:55,024 two and your Kerberos ID. 1168 00:52:55,024 --> 00:52:56,470 All the stuff that is on Tumblr. 1169 00:52:56,470 --> 00:52:59,362 I'd also do the day two thing. 1170 00:52:59,362 --> 00:53:03,540 And then a quick 200 or 300 rough script 1171 00:53:03,540 --> 00:53:07,300 based on some of the stuff we talked about now. 1172 00:53:07,300 --> 00:53:11,550 Don't worry about being too jargony in this. 1173 00:53:11,550 --> 00:53:15,810 This is really about pulling the overarching story. 1174 00:53:15,810 --> 00:53:17,852 We're going to work out the details of what's 1175 00:53:17,852 --> 00:53:18,852 the best wording to use. 1176 00:53:18,852 --> 00:53:21,212 We're going to work out some of the minutiae a bit 1177 00:53:21,212 --> 00:53:23,572 tomorrow during our scripting workshop. 1178 00:53:23,572 --> 00:53:27,866 For tonight, think about what's the point of the video, 1179 00:53:27,866 --> 00:53:30,860 and what the overarching story of the video is. 1180 00:53:30,860 --> 00:53:32,555 Those are really the things I want 1181 00:53:32,555 --> 00:53:34,852 you to think about tonight. 1182 00:53:34,852 --> 00:53:36,534 If you get so stuck, and you just 1183 00:53:36,534 --> 00:53:39,498 can't think of something to write, 1184 00:53:39,498 --> 00:53:42,956 write down some facts like I was showing earlier. 1185 00:53:42,956 --> 00:53:44,332 Just come to class with something 1186 00:53:44,332 --> 00:53:45,622 that we can work with tomorrow. 1187 00:53:45,622 --> 00:53:47,896 Because tomorrow's going to be a really informal day. 1188 00:53:47,896 --> 00:53:49,872 [INAUDIBLE] and I are just going to workshop 1189 00:53:49,872 --> 00:53:53,824 and then table read some of this stuff that we've written. 1190 00:53:53,824 --> 00:53:56,436 And figure out how to implement the theoretical things 1191 00:53:56,436 --> 00:53:58,186 that we were talking about in the last two 1192 00:53:58,186 --> 00:54:00,740 days in a more practical sense. 1193 00:54:00,740 --> 00:54:02,963 So does anyone have any questions 1194 00:54:02,963 --> 00:54:06,168 about those assignments? 1195 00:54:06,168 --> 00:54:06,668 Yes. 1196 00:54:06,668 --> 00:54:08,995 AUDIENCE: Can you also bring back the canvas tomorrow? 1197 00:54:08,995 --> 00:54:09,578 PROFESSOR: No. 1198 00:54:09,578 --> 00:54:11,245 Tomorrow will just workshopping. 1199 00:54:11,245 --> 00:54:14,154 You will need them back at least on Friday. 1200 00:54:14,154 --> 00:54:16,110 I'll send you guys an email the night before 1201 00:54:16,110 --> 00:54:19,010 and the day we meet in the final class. 1202 00:54:19,010 --> 00:54:21,550 PROFESSOR: When I-- just as something to think about. 1203 00:54:21,550 --> 00:54:24,570 When I walked around and led to some of you guys more deeply, 1204 00:54:24,570 --> 00:54:26,510 I feel like a lot of you are sort 1205 00:54:26,510 --> 00:54:29,690 of struggling with this same concept of broad 1206 00:54:29,690 --> 00:54:31,270 versus detailed. 1207 00:54:31,270 --> 00:54:38,420 And my two cents on it is that by asking a broad question 1208 00:54:38,420 --> 00:54:42,560 but going very narrowly in with one example, 1209 00:54:42,560 --> 00:54:46,250 you actually end up being able to bring people back 1210 00:54:46,250 --> 00:54:48,200 up to that broader framework. 1211 00:54:48,200 --> 00:54:49,880 So if you pick something-- like we 1212 00:54:49,880 --> 00:54:51,470 talked about food composition. 1213 00:54:51,470 --> 00:54:53,640 And we started exploring further. 1214 00:54:53,640 --> 00:54:56,870 Maybe talking about why a piece of broccoli rots. 1215 00:54:56,870 --> 00:54:59,960 And when is it too rotten for me to eat that I get sick? 1216 00:54:59,960 --> 00:55:02,340 Is actually the perfect focus for him 1217 00:55:02,340 --> 00:55:05,480 to ask all these other questions about food composition. 1218 00:55:05,480 --> 00:55:08,560 And that by focusing really narrowly on that broccoli, 1219 00:55:08,560 --> 00:55:11,640 we actually get to ask a lot more questions. 1220 00:55:11,640 --> 00:55:12,290 Right? 1221 00:55:12,290 --> 00:55:13,440 Like with shipbuilding. 1222 00:55:13,440 --> 00:55:16,650 Why does something really sink or float? 1223 00:55:16,650 --> 00:55:18,970 But that question diving really narrowly 1224 00:55:18,970 --> 00:55:21,800 into one scenario of one ship sinking. 1225 00:55:21,800 --> 00:55:23,380 And why does it do this? 1226 00:55:23,380 --> 00:55:27,030 It allows us to be able to ask some broader questions. 1227 00:55:27,030 --> 00:55:28,570 Why-- the braces. 1228 00:55:28,570 --> 00:55:29,240 The opposite. 1229 00:55:29,240 --> 00:55:29,740 Right? 1230 00:55:29,740 --> 00:55:31,970 I want to talk about braces and what they do to your teeth. 1231 00:55:31,970 --> 00:55:33,720 But all right, let's think about if that's 1232 00:55:33,720 --> 00:55:35,990 a specific example, what's the question that we're 1233 00:55:35,990 --> 00:55:36,990 trying to think through? 1234 00:55:36,990 --> 00:55:38,980 And I feel all into a kind of in that place 1235 00:55:38,980 --> 00:55:42,110 right now where you're trying to figure out what specific 1236 00:55:42,110 --> 00:55:46,530 story do I tell in order to get these bigger, bigger concepts? 1237 00:55:46,530 --> 00:55:50,120 The narrower you are in that microcosm, 1238 00:55:50,120 --> 00:55:52,550 the easier it is to extrapolate out. 1239 00:55:52,550 --> 00:55:56,240 Because it lets you really dive deeply into that topic. 1240 00:55:56,240 --> 00:55:58,670 So if you have a really, really broad topic still, 1241 00:55:58,670 --> 00:56:01,100 see if you can get it really narrow. 1242 00:56:01,100 --> 00:56:04,330 And then from that it allows you to get broad again. 1243 00:56:04,330 --> 00:56:05,380 If that makes sense. 1244 00:56:05,380 --> 00:56:06,970 PROFESSOR: And that's why I personally 1245 00:56:06,970 --> 00:56:08,890 like going with the whole just trying 1246 00:56:08,890 --> 00:56:11,950 to list out as many facts as I can with this snot thing. 1247 00:56:11,950 --> 00:56:15,120 Because it was just sort of, snot is awesome. 1248 00:56:15,120 --> 00:56:15,780 OK. 1249 00:56:15,780 --> 00:56:17,990 Like, you know, why is it awesome? 1250 00:56:17,990 --> 00:56:19,530 What does that even mean? 1251 00:56:19,530 --> 00:56:21,540 And so I'm listing out all these specific things 1252 00:56:21,540 --> 00:56:23,030 that people study about it. 1253 00:56:23,030 --> 00:56:27,680 And that helped me delve into the tangible examples 1254 00:56:27,680 --> 00:56:28,480 that I gave. 1255 00:56:28,480 --> 00:56:30,490 That allowed me, at the end, to go back 1256 00:56:30,490 --> 00:56:34,030 out to the story of this material that 1257 00:56:34,030 --> 00:56:37,679 protects you every day, and is amazing and awesome. 1258 00:56:37,679 --> 00:56:39,970 PROFESSOR: And I know we're just about-- we're actually 1259 00:56:39,970 --> 00:56:41,110 over time, so I apologize. 1260 00:56:41,110 --> 00:56:43,440 But I realize that some of you may not 1261 00:56:43,440 --> 00:56:46,110 know how to implement Elizabeth's task of asking you 1262 00:56:46,110 --> 00:56:47,900 to actually write your script. 1263 00:56:47,900 --> 00:56:51,040 And that may be an overwhelming task. 1264 00:56:51,040 --> 00:56:52,540 Is that feeling like that right now? 1265 00:56:52,540 --> 00:56:55,040 Like sitting down and actually putting something on paper, 1266 00:56:55,040 --> 00:56:56,290 you don't know where to start? 1267 00:56:56,290 --> 00:57:01,430 Or do you feel like you know to at least dump something down? 1268 00:57:01,430 --> 00:57:05,660 Sort of like you know, Paul, colon, says this. 1269 00:57:05,660 --> 00:57:07,170 Picture of something in here. 1270 00:57:07,170 --> 00:57:08,469 Like just jot it down. 1271 00:57:08,469 --> 00:57:09,510 Don't worry about format. 1272 00:57:09,510 --> 00:57:10,998 Don't worry about any of that. 1273 00:57:10,998 --> 00:57:12,870 PROFESSOR: We're going to go over all the details tomorrow. 1274 00:57:12,870 --> 00:57:13,754 We just need an idea. 1275 00:57:13,754 --> 00:57:14,420 PROFESSOR: Yeah. 1276 00:57:14,420 --> 00:57:17,460 Just dump-- so when she says script, 1277 00:57:17,460 --> 00:57:19,510 that word may be intimidating right now, 1278 00:57:19,510 --> 00:57:21,760 because a script can look certain ways 1279 00:57:21,760 --> 00:57:22,710 in different genres. 1280 00:57:22,710 --> 00:57:25,200 Like a film script looks very different from a theater 1281 00:57:25,200 --> 00:57:26,830 script, versus this kind of transcript. 1282 00:57:26,830 --> 00:57:30,060 Don't worry about anything other than getting 1283 00:57:30,060 --> 00:57:31,320 some ideas on paper. 1284 00:57:31,320 --> 00:57:35,292 And we'll deal with all of the other stuff later. 1285 00:57:35,292 --> 00:57:36,254 If that makes sense. 1286 00:57:38,317 --> 00:57:40,150 PROFESSOR: And I'll stick around afterwards, 1287 00:57:40,150 --> 00:57:41,960 if anyone wants to talk specifically. 1288 00:57:41,960 --> 00:57:43,160 Yeah? 1289 00:57:43,160 --> 00:57:45,101 And just upload all that stuff to Tumblr. 1290 00:57:45,101 --> 00:57:46,600 PROFESSOR: And we're both available. 1291 00:57:46,600 --> 00:57:48,150 And we're all available via email. 1292 00:57:48,150 --> 00:57:50,965 So if any of you are struggling tonight, 1293 00:57:50,965 --> 00:57:53,520 and you need bounce an idea off of one of us, 1294 00:57:53,520 --> 00:57:55,170 don't hesitate to do that. 1295 00:57:55,170 --> 00:57:58,060 I do not check email usually until after 8:00 PM 1296 00:57:58,060 --> 00:57:59,260 when my son goes to bed. 1297 00:57:59,260 --> 00:58:00,410 But I will respond. 1298 00:58:00,410 --> 00:58:02,790 So if you have a question or anything, 1299 00:58:02,790 --> 00:58:04,470 don't hesitate to bounce ideas off. 1300 00:58:04,470 --> 00:58:07,970 And I do really get back to you guys, as does-- do all of us. 1301 00:58:10,270 --> 00:58:11,270 So that's all for today. 1302 00:58:11,270 --> 00:58:13,470 You guys can pack up and leave. 1303 00:58:13,470 --> 00:58:16,930 But really just get ideas down more than anything. 1304 00:58:16,930 --> 00:58:19,345 We will help you with everything else tomorrow. 1305 00:58:19,345 --> 00:58:22,140 PROFESSOR: Even if drawing is the way that helps you. 1306 00:58:22,140 --> 00:58:23,835 Just get something down. 1307 00:58:23,835 --> 00:58:25,210 PROFESSOR: But do get words down. 1308 00:58:25,210 --> 00:58:26,870 We need to have like some words. 1309 00:58:26,870 --> 00:58:28,146 That would be great. 1310 00:58:28,146 --> 00:58:31,264 AUDIENCE: Is the script supposed to go on a tablet, or? 1311 00:58:31,264 --> 00:58:31,930 PROFESSOR: Yeah. 1312 00:58:31,930 --> 00:58:34,300 Yeah. 1313 00:58:34,300 --> 00:58:35,500 PROFESSOR: Good work, guys. 1314 00:58:35,500 --> 00:58:37,050 PROFESSOR: All right.