1 00:00:03,800 --> 00:00:06,680 Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff 2 00:00:06,680 --> 00:00:13,920 Speaker 1: Works dot com. Hey, welcome to Stuff to Blow your Mind. 3 00:00:13,960 --> 00:00:17,000 Speaker 1: My name is Robert Lamb, and I'm Julie Douglas. And 4 00:00:17,400 --> 00:00:20,880 Speaker 1: you know, Julie, neither of us are really math people. 5 00:00:21,680 --> 00:00:24,280 Speaker 1: It's like we don't do a lot of recreational math. Yeah, 6 00:00:24,360 --> 00:00:26,200 Speaker 1: and we know. I'm a math folk. I just started 7 00:00:26,200 --> 00:00:29,120 Speaker 1: to same math and I started to get sweaty palms. Yeah. 8 00:00:30,400 --> 00:00:33,080 Speaker 1: Um and uh, but but but but we both enjoy music, 9 00:00:33,120 --> 00:00:35,760 Speaker 1: different types of music, I think. I mean there's some crossover. 10 00:00:35,840 --> 00:00:38,040 Speaker 1: It's not you know, it's kind of like a ven 11 00:00:38,560 --> 00:00:41,640 Speaker 1: diagram I would imagined. But um, see there you go 12 00:00:42,080 --> 00:00:45,360 Speaker 1: with the math. Yeah goodness, yeah, goodness me because this 13 00:00:45,440 --> 00:00:49,360 Speaker 1: is exactly what we're talking about. Math and music, um, 14 00:00:49,479 --> 00:00:52,640 Speaker 1: kind of lining up with each other, um, describing each other. 15 00:00:52,880 --> 00:00:55,840 Speaker 1: And we end up with this this idea in our head, 16 00:00:56,000 --> 00:00:59,520 Speaker 1: especially uh, those of us who are not math people 17 00:00:59,840 --> 00:01:04,960 Speaker 1: and enjoy music but don't have musical training per se um. 18 00:01:05,040 --> 00:01:07,360 Speaker 1: We end up looking back at it where we see 19 00:01:07,920 --> 00:01:10,520 Speaker 1: mathematicians who are really good at music or musicians that 20 00:01:10,600 --> 00:01:13,280 Speaker 1: have mathematical background, and we start saying, WHOA, what's going 21 00:01:13,319 --> 00:01:15,520 Speaker 1: on here? This seems to be the case, right right, 22 00:01:15,720 --> 00:01:20,039 Speaker 1: And I think you made the great analogy yesterday, like, oh, actors, 23 00:01:20,360 --> 00:01:23,960 Speaker 1: yeah crazy, all actors are crazy. Right. It's like if 24 00:01:24,000 --> 00:01:25,920 Speaker 1: you if you don't have an acting background, you don't 25 00:01:25,920 --> 00:01:27,959 Speaker 1: know many actors, you're not crazy. You don't know many 26 00:01:27,959 --> 00:01:30,160 Speaker 1: crazy people. You see crazy actors, and it's easy to 27 00:01:30,160 --> 00:01:33,639 Speaker 1: make that generality that, wow, they must be All actors 28 00:01:33,720 --> 00:01:36,240 Speaker 1: must be crazy, and their craziness must make them great actors. 29 00:01:36,400 --> 00:01:39,480 Speaker 1: Or maybe their acting makes them great crazies. I don't know. Yeah, yeah, 30 00:01:39,520 --> 00:01:42,320 Speaker 1: it's the that's the dog wagon the tail there. Um. 31 00:01:42,360 --> 00:01:43,840 Speaker 1: So yeah, we're going to try to look at this 32 00:01:44,200 --> 00:01:49,080 Speaker 1: idea of math and music being intertwined in perhaps being 33 00:01:49,160 --> 00:01:53,280 Speaker 1: inherent and um, and we'll try to see if there 34 00:01:53,280 --> 00:01:56,720 Speaker 1: really is a correlation between mathematics and musicians. Yeah. Now, 35 00:01:56,960 --> 00:02:00,680 Speaker 1: just to start off, like some famous mathematicians and slash 36 00:02:00,800 --> 00:02:04,720 Speaker 1: musicians or famous musicianstead have mathematical background. Um. One one hand, 37 00:02:04,760 --> 00:02:09,919 Speaker 1: we have Einstein himself, who was a violinist. Yeah. Um, 38 00:02:10,000 --> 00:02:13,880 Speaker 1: Brian May of Queen was an astrophysicist, um, which I've 39 00:02:13,880 --> 00:02:16,280 Speaker 1: always found kind of interesting. I don't know if it 40 00:02:16,360 --> 00:02:18,720 Speaker 1: really I haven't listened to queen in a long time, 41 00:02:18,720 --> 00:02:22,400 Speaker 1: but I don't remember there being much astrophysics UM injected 42 00:02:22,440 --> 00:02:26,960 Speaker 1: into the song. Yeah, maybe it was all happening just 43 00:02:26,960 --> 00:02:29,400 Speaker 1: with the music, just with the guitars, you know, because 44 00:02:30,080 --> 00:02:33,760 Speaker 1: and he he has returned to this discipline. Yes, yeah, yeah, yes, yeah, 45 00:02:34,000 --> 00:02:37,120 Speaker 1: there have been some interesting articles about it in recent years. UM. 46 00:02:37,280 --> 00:02:41,080 Speaker 1: Then we have people like Dan Snaith a k a 47 00:02:41,200 --> 00:02:45,520 Speaker 1: Caribou who has a mathematics background, though I've seen interviews 48 00:02:45,520 --> 00:02:48,160 Speaker 1: where he's very dismissive of the idea that there's any 49 00:02:48,240 --> 00:02:51,200 Speaker 1: really connectivity between the two. I think it was like 50 00:02:51,240 --> 00:02:54,320 Speaker 1: a was it an interview on data transmission? I can't 51 00:02:54,320 --> 00:02:56,480 Speaker 1: remember me it was linked to on data transmission UM 52 00:02:56,760 --> 00:02:59,600 Speaker 1: that code out UK where someone asked him about in 53 00:02:59,639 --> 00:03:04,600 Speaker 1: Cariboo was like you know math, yeah, math, math, different things. 54 00:03:05,400 --> 00:03:08,720 Speaker 1: So it's kind of disappointing. You can imagine the the interviewers, 55 00:03:08,880 --> 00:03:11,680 Speaker 1: you know, kind of slumping down, you know when he 56 00:03:11,840 --> 00:03:15,040 Speaker 1: got that answer. But other ones are Garfuncle had a 57 00:03:15,040 --> 00:03:17,640 Speaker 1: master's degree in mathematics, which I was not aware of. 58 00:03:17,800 --> 00:03:19,919 Speaker 1: I wasn't. I was surprised by that one. Yeah, I mean, 59 00:03:19,960 --> 00:03:22,840 Speaker 1: certainly his hair seems to indicate some sort of like 60 00:03:23,040 --> 00:03:27,919 Speaker 1: science lab type situation. But but no, he and again 61 00:03:27,960 --> 00:03:30,320 Speaker 1: I can't think of any Garfuncle songs where where I 62 00:03:30,320 --> 00:03:32,600 Speaker 1: have listened to him and be like, wow, bright Eyes 63 00:03:32,680 --> 00:03:36,000 Speaker 1: is such a mathematical song, you know. And again maybe 64 00:03:36,000 --> 00:03:41,320 Speaker 1: I'm I'm missing the finer corners of his discography, but yeah, um. 65 00:03:41,360 --> 00:03:44,320 Speaker 1: And then another one that comes to mind, uh is 66 00:03:44,640 --> 00:03:47,680 Speaker 1: a chat by the name of Rupert Way, who DJ 67 00:03:47,840 --> 00:03:50,400 Speaker 1: is under the name dj Irk. Yeah, and I actually 68 00:03:50,440 --> 00:03:53,720 Speaker 1: interviewed him for the blogs a little while back, and uh, 69 00:03:53,800 --> 00:03:57,640 Speaker 1: he has like a PhD in uh, some kind of 70 00:03:57,680 --> 00:04:00,840 Speaker 1: type of mathematics that dynamic systems something. It kind of 71 00:04:01,440 --> 00:04:03,640 Speaker 1: it just goes right over my head when when he 72 00:04:03,680 --> 00:04:06,640 Speaker 1: told me what it was. But but yeah, And there're 73 00:04:06,680 --> 00:04:08,360 Speaker 1: just a few there. Do you have any that I'm 74 00:04:08,440 --> 00:04:11,040 Speaker 1: leaving off? No, No, that that sounds Um, those are 75 00:04:11,080 --> 00:04:12,440 Speaker 1: some of the big ones, I think. And I was 76 00:04:12,480 --> 00:04:15,840 Speaker 1: I was actually revisiting your interview with him, and he 77 00:04:15,920 --> 00:04:19,599 Speaker 1: was talking. You were asking him about the connection between 78 00:04:19,640 --> 00:04:23,000 Speaker 1: Mathew music and I think he was saying that he 79 00:04:23,040 --> 00:04:26,040 Speaker 1: doesn't it doesn't really help anymore than it does with 80 00:04:26,040 --> 00:04:31,279 Speaker 1: what he says, say around trip a trip around the supermarket. 81 00:04:31,000 --> 00:04:35,240 Speaker 1: I've obviously taken that out of context. Uh, but he 82 00:04:35,279 --> 00:04:39,000 Speaker 1: did say something about mental agility, good memory, good numerous 83 00:04:39,080 --> 00:04:41,120 Speaker 1: e and a lot of determination, he says, or what 84 00:04:41,200 --> 00:04:44,360 Speaker 1: really counts. And although these are math related I'm quoting him, 85 00:04:44,600 --> 00:04:48,080 Speaker 1: they are not math specific. There are lots of overriding 86 00:04:48,160 --> 00:04:52,480 Speaker 1: instinctive and emotional factors too, which I thought was interesting 87 00:04:52,600 --> 00:04:56,200 Speaker 1: because he's he's sort of saying, yeah, all of this helps, 88 00:04:56,279 --> 00:04:59,720 Speaker 1: but it does not make you a musician per se, 89 00:05:00,000 --> 00:05:02,560 Speaker 1: because there are some factors that you just can't that 90 00:05:02,680 --> 00:05:05,560 Speaker 1: don't fit into the mathematical model, so to speak. Right. Yeah, 91 00:05:05,600 --> 00:05:09,320 Speaker 1: his answer was far more insightful than caribous. Yeah, yeah, yeah, 92 00:05:09,760 --> 00:05:12,560 Speaker 1: he actually he went on to say some very interesting stuff. Actually, 93 00:05:12,600 --> 00:05:14,680 Speaker 1: So if you haven't checked out Robert's blog on that 94 00:05:15,120 --> 00:05:18,200 Speaker 1: with with dj Oric, should definitely check that out. Yeah yeah, 95 00:05:18,200 --> 00:05:21,520 Speaker 1: I'll throw the link up. But but yeah, you end 96 00:05:21,640 --> 00:05:23,719 Speaker 1: up in the in this this situation where the the 97 00:05:23,760 --> 00:05:26,719 Speaker 1: answer is kind of yeah, kind of yeah, but also 98 00:05:27,480 --> 00:05:31,480 Speaker 1: not really um and and there's no real firm answer 99 00:05:31,480 --> 00:05:36,080 Speaker 1: because I mean, when you break it down, UM, I 100 00:05:36,080 --> 00:05:38,440 Speaker 1: mean we we've discussed in the past, like mathematics, what 101 00:05:38,600 --> 00:05:41,200 Speaker 1: is it is the human invention that just is so 102 00:05:41,279 --> 00:05:44,520 Speaker 1: clever that it describes everything in the universe? Or is 103 00:05:44,560 --> 00:05:48,039 Speaker 1: it a discovery? Did we find the secret language of 104 00:05:48,040 --> 00:05:51,040 Speaker 1: the universe and we're so awesome because we found it? Again, 105 00:05:51,200 --> 00:05:54,080 Speaker 1: humans end up looking pretty awesome. Either way, you spend 106 00:05:54,080 --> 00:05:57,599 Speaker 1: that but if but but but either way, you're talking 107 00:05:57,640 --> 00:06:02,000 Speaker 1: about a system of numbers that can describe everything. So 108 00:06:02,120 --> 00:06:03,719 Speaker 1: it stands to reason that it would be able to 109 00:06:03,720 --> 00:06:07,520 Speaker 1: describe music, right, Right, And yes, so there are definitely 110 00:06:07,560 --> 00:06:09,719 Speaker 1: some similarities with that because you would ask the same 111 00:06:09,720 --> 00:06:11,839 Speaker 1: thing about music in a sense, right, it is music 112 00:06:11,920 --> 00:06:14,120 Speaker 1: something that we discovered is just sort of inherent in 113 00:06:14,120 --> 00:06:17,800 Speaker 1: in us. And then we've talked about even our fingers before, Right, 114 00:06:17,839 --> 00:06:20,320 Speaker 1: we've got five fingers on each hand, and how that's 115 00:06:20,360 --> 00:06:22,640 Speaker 1: determined our currency in the way that we count in 116 00:06:22,720 --> 00:06:26,080 Speaker 1: number systems, and same thing with music. It's it's determined 117 00:06:26,080 --> 00:06:29,440 Speaker 1: the way that we have, Uh, created scales, and we 118 00:06:29,640 --> 00:06:33,839 Speaker 1: created instruments. Yeah, like strings vibrated a certain frequency and 119 00:06:33,880 --> 00:06:36,919 Speaker 1: you can measure those mathematically. Sound waves can also be 120 00:06:36,960 --> 00:06:40,120 Speaker 1: described by mathematical equations. Uh. I mean it comes down 121 00:06:40,120 --> 00:06:43,080 Speaker 1: to like scientists of any discipline, they use mathematics to 122 00:06:43,160 --> 00:06:49,040 Speaker 1: describe the physical world. Changing physical world of movable opjects, 123 00:06:49,560 --> 00:06:54,880 Speaker 1: and they predict the outcome of physical process, so you 124 00:06:54,920 --> 00:06:57,799 Speaker 1: know there's gonna be some cross over there. But then again, 125 00:06:57,839 --> 00:07:00,000 Speaker 1: an equation is not going to be able to describ 126 00:07:00,040 --> 00:07:03,480 Speaker 1: have a piece of music, and uh, I mean there 127 00:07:03,480 --> 00:07:07,320 Speaker 1: are a certain mathematical well, well you can there are 128 00:07:07,360 --> 00:07:10,360 Speaker 1: equations that can describe some of the mathematical structures that 129 00:07:10,400 --> 00:07:12,680 Speaker 1: are inherent in music, but you're not going to be 130 00:07:12,760 --> 00:07:14,960 Speaker 1: able to like to say, um, yeah, I want to 131 00:07:14,960 --> 00:07:18,360 Speaker 1: listen to that. Um, you know that can concerto by 132 00:07:18,720 --> 00:07:20,320 Speaker 1: so and so, But I don't have time for the 133 00:07:20,360 --> 00:07:23,960 Speaker 1: full thing. Just send me the equation. Well, and it's 134 00:07:23,960 --> 00:07:27,880 Speaker 1: interesting too, because the each equation you could interpret in 135 00:07:27,880 --> 00:07:31,040 Speaker 1: a different way as a musician, right yeah. But I 136 00:07:31,040 --> 00:07:33,600 Speaker 1: mean so there's that's the part of it that's like, well, okay, 137 00:07:33,600 --> 00:07:37,320 Speaker 1: here's here's the precise language. Um that you know, and 138 00:07:37,560 --> 00:07:43,360 Speaker 1: again drawing parallels to math, Math has a universal precise language. Right. 139 00:07:43,680 --> 00:07:46,600 Speaker 1: But once you know, you give this equation of music 140 00:07:46,640 --> 00:07:49,560 Speaker 1: to someone, they might perform it in a completely different 141 00:07:49,600 --> 00:07:52,640 Speaker 1: way or take liberties with it that you wouldn't necessarily 142 00:07:52,680 --> 00:07:56,880 Speaker 1: see in math. But again again talking about similarities, Um, 143 00:07:57,160 --> 00:07:59,880 Speaker 1: both disciplines gravitate towards symmetry. Right. You see this in 144 00:08:00,080 --> 00:08:04,280 Speaker 1: music all the time. Um, of course there's there's cacophony, right, 145 00:08:05,440 --> 00:08:08,520 Speaker 1: Uh yeah, noise music and all that. I mean that's 146 00:08:08,560 --> 00:08:10,280 Speaker 1: the thing too. It's like music when you're talking about 147 00:08:10,280 --> 00:08:11,800 Speaker 1: like what is music? Yeah, there's some there are there 148 00:08:11,920 --> 00:08:14,760 Speaker 1: certain types of music that are very mathematical sounding, and 149 00:08:14,840 --> 00:08:17,400 Speaker 1: you can break down you can you know, apply some 150 00:08:17,400 --> 00:08:20,040 Speaker 1: some number to the numbers to the music theory of 151 00:08:20,040 --> 00:08:22,000 Speaker 1: it all, and it makes perfect sense. But then you 152 00:08:22,200 --> 00:08:24,600 Speaker 1: pull out some sort of like noise artist where they're 153 00:08:24,680 --> 00:08:28,280 Speaker 1: using very abstract sounds music that uh, to quote my wife, 154 00:08:28,360 --> 00:08:32,360 Speaker 1: sounds like someone through a xylophone down a stairwell. And 155 00:08:32,800 --> 00:08:35,520 Speaker 1: then it's gonna be hard to say like, oh, well, mathematically, 156 00:08:35,559 --> 00:08:38,800 Speaker 1: this is what's going on there. But then again, you 157 00:08:38,800 --> 00:08:42,000 Speaker 1: could also make the counter argument that even a chaotic system, um, 158 00:08:42,040 --> 00:08:45,400 Speaker 1: there's math going on there. Can you can go back 159 00:08:45,400 --> 00:08:48,400 Speaker 1: and forth. And now the ancient Greeks they definitely thought 160 00:08:48,400 --> 00:08:51,160 Speaker 1: there was there were numbers tied up in music, that 161 00:08:51,320 --> 00:08:54,840 Speaker 1: math and music were very closely related. Is this uh 162 00:08:55,000 --> 00:08:59,200 Speaker 1: pithe Pythi versus yeah, yeah, yeah, like because he use 163 00:08:59,200 --> 00:09:01,360 Speaker 1: all about the ratio of yeah, yeah, and his his 164 00:09:01,400 --> 00:09:05,920 Speaker 1: whole like system of of education. Um. They considered music 165 00:09:05,960 --> 00:09:09,000 Speaker 1: to be a strictly mathematical disciple in involving number of relationships, 166 00:09:09,080 --> 00:09:11,560 Speaker 1: ratios and proportions, and so if you break it down, 167 00:09:11,600 --> 00:09:15,839 Speaker 1: it would basically be a subdivision to quantitative mathematics in 168 00:09:16,880 --> 00:09:22,080 Speaker 1: Pithagorean time. So yeah, harmonica ratios proportions central in the 169 00:09:22,120 --> 00:09:26,360 Speaker 1: Greek's understanding too musical, okay, yeah, And so just to 170 00:09:26,360 --> 00:09:28,040 Speaker 1: back up a little bit to the five tone or 171 00:09:28,040 --> 00:09:31,160 Speaker 1: the pentatonic scale developed about three thousand years ago in China, 172 00:09:31,640 --> 00:09:35,880 Speaker 1: and then the Greeks they have the seven tone scale, right, um. 173 00:09:35,920 --> 00:09:39,040 Speaker 1: And then then we're talking about the twelve tone scale, right, 174 00:09:39,040 --> 00:09:41,840 Speaker 1: And this is when we're talking about Pythagora is really 175 00:09:41,880 --> 00:09:44,680 Speaker 1: obsessing on these ratios. And I won't go into the 176 00:09:44,720 --> 00:09:46,880 Speaker 1: math behind it, but that's how we sort of came 177 00:09:46,960 --> 00:09:50,400 Speaker 1: up with these varying skills. And it wasn't till around 178 00:09:50,480 --> 00:09:53,160 Speaker 1: I think Box time where they took one of those 179 00:09:53,280 --> 00:09:55,679 Speaker 1: ratios that was a bit off and and tinkered with 180 00:09:55,720 --> 00:09:59,400 Speaker 1: it and they came up with the final twelve tones. Um. 181 00:09:59,520 --> 00:10:03,240 Speaker 1: So again there's there's a system behind there. There's math 182 00:10:03,360 --> 00:10:07,240 Speaker 1: that's driving the way that we are expressing music, which 183 00:10:07,280 --> 00:10:10,560 Speaker 1: is pretty interesting, all right, But what exactly is going 184 00:10:10,559 --> 00:10:14,120 Speaker 1: on in the brain? Right? Yes? Yes, so let's uh, 185 00:10:14,200 --> 00:10:16,120 Speaker 1: let's take a quick break, and when we come back, 186 00:10:16,240 --> 00:10:18,920 Speaker 1: we will look at math and music in the human mind. 187 00:10:24,080 --> 00:10:27,600 Speaker 1: This presentation is brought to you by Intel sponsors of tomorrow, 188 00:10:32,160 --> 00:10:39,240 Speaker 1: and we're back music brains. What's happened? Yes, um, so, 189 00:10:41,080 --> 00:10:44,680 Speaker 1: obviously scientists have looked at the brain and analyze what 190 00:10:44,760 --> 00:10:47,480 Speaker 1: exactly is going on when we think about music or 191 00:10:47,600 --> 00:10:52,360 Speaker 1: contemplate music versus contemplating math, and they have Scientists actually 192 00:10:52,360 --> 00:10:55,240 Speaker 1: looked at brain injuries that suggest a single region in 193 00:10:55,280 --> 00:10:58,320 Speaker 1: the left hemisphere of the brain gives rise to sequential 194 00:10:58,360 --> 00:11:02,280 Speaker 1: analytic processing, which is used for both doing algebra and 195 00:11:02,320 --> 00:11:05,120 Speaker 1: reading music. All right, But then on the other hand, 196 00:11:05,120 --> 00:11:07,000 Speaker 1: there was a two thousand eight study from the University 197 00:11:07,000 --> 00:11:12,080 Speaker 1: of Arkansas that used a human Information Processing Survey instrument 198 00:11:12,160 --> 00:11:16,480 Speaker 1: or a HIPS instrument to measure hemispheric collaterality. They used 199 00:11:16,480 --> 00:11:18,720 Speaker 1: a hundred and one participants asked them to discuss their 200 00:11:18,720 --> 00:11:21,520 Speaker 1: prowess in first math and then in music, and their 201 00:11:21,600 --> 00:11:25,920 Speaker 1: finding suggested that math is a left hemisphere preference and 202 00:11:26,000 --> 00:11:30,640 Speaker 1: music is a right hemisphere preference. Okay, well, it's interesting, 203 00:11:30,760 --> 00:11:33,320 Speaker 1: right because we've talked about music before and how it 204 00:11:33,360 --> 00:11:35,560 Speaker 1: affects the brain, and we've found that there is no 205 00:11:35,720 --> 00:11:38,800 Speaker 1: one music center, um, so it's sort of spread up 206 00:11:38,840 --> 00:11:41,640 Speaker 1: throughout the brain. But to to know that's obviously engaging 207 00:11:41,679 --> 00:11:43,840 Speaker 1: in a part of the brain that is that's tracking 208 00:11:44,200 --> 00:11:47,599 Speaker 1: um math is interesting. And likewise, there have been a 209 00:11:47,679 --> 00:11:50,720 Speaker 1: number of studies which sort of say different things about 210 00:11:51,240 --> 00:11:57,160 Speaker 1: exactly how musical education affects one's mathematical prowess. Um. They 211 00:11:57,200 --> 00:11:59,280 Speaker 1: have been studies they've found that people with musical training 212 00:11:59,320 --> 00:12:03,199 Speaker 1: outperform people who don't have musical training. Um. But then 213 00:12:03,240 --> 00:12:05,600 Speaker 1: there's uh, there's stuff like for instance, there was the 214 00:12:05,920 --> 00:12:09,320 Speaker 1: Montreal Montreal Piano Project. All right, half the children were 215 00:12:09,360 --> 00:12:11,920 Speaker 1: giving piano lessons for three years, and after two years, 216 00:12:12,280 --> 00:12:16,280 Speaker 1: the piano playing kids were outscoring the others on spatial ability. 217 00:12:16,640 --> 00:12:20,319 Speaker 1: So the argument here was that yeah, learning music helps you, 218 00:12:20,760 --> 00:12:23,600 Speaker 1: um helps you with math because it's reinforcing the brain 219 00:12:23,640 --> 00:12:26,960 Speaker 1: circuits that power spatial thinking, which comes in handy not 220 00:12:27,040 --> 00:12:29,600 Speaker 1: only for knowing what keys match up with what note, 221 00:12:29,920 --> 00:12:33,800 Speaker 1: but also in geometry, physics, and chemistry, all right, But 222 00:12:33,840 --> 00:12:37,920 Speaker 1: then opposing that we have um um a study from 223 00:12:37,960 --> 00:12:41,640 Speaker 1: the University of Toronto. Uh, and this one, this one 224 00:12:41,679 --> 00:12:44,400 Speaker 1: was pretty cool too. They took six year olds, all right, 225 00:12:44,960 --> 00:12:48,280 Speaker 1: and they took weekly piano and singing lessons throughout the 226 00:12:48,320 --> 00:12:51,840 Speaker 1: school year, and they exhibited an average i Q increase 227 00:12:51,880 --> 00:12:55,520 Speaker 1: of seven h point zero points. Right. The other six 228 00:12:55,600 --> 00:12:58,520 Speaker 1: year olds who took either weekly drama lessons or received 229 00:12:58,520 --> 00:13:01,800 Speaker 1: no extra trick curricular lessons displayed an average i Q 230 00:13:02,040 --> 00:13:06,079 Speaker 1: rise of four point three points. So that's another one 231 00:13:06,080 --> 00:13:08,760 Speaker 1: that also seems to indicate, all right, they're they're learning 232 00:13:08,880 --> 00:13:11,560 Speaker 1: music and this is helping them with their scores. But 233 00:13:11,800 --> 00:13:15,040 Speaker 1: I also think, like non scientifically, that maybe the drama 234 00:13:15,080 --> 00:13:17,640 Speaker 1: kids were just having more fun and didn't have as 235 00:13:17,720 --> 00:13:21,280 Speaker 1: much time to really play with the studying all that much. Huh, 236 00:13:21,360 --> 00:13:24,720 Speaker 1: all right, yeah, they were too busy emoting. And then 237 00:13:24,760 --> 00:13:26,360 Speaker 1: the kids who didn't get anything, they were just setting 238 00:13:26,360 --> 00:13:30,000 Speaker 1: around in study hall like destroying desks with tiny axes 239 00:13:30,080 --> 00:13:32,760 Speaker 1: or something. They weren't having new experiences. And we just 240 00:13:32,760 --> 00:13:35,480 Speaker 1: talked about this so important is that you need to 241 00:13:35,480 --> 00:13:38,280 Speaker 1: to have new experiences in order to create new pathways. Yeah, 242 00:13:38,400 --> 00:13:42,680 Speaker 1: discussed in our Einstein's Brain podcasts. Alright, so there's there's 243 00:13:42,720 --> 00:13:47,760 Speaker 1: some basis here for some some waltzing, let's say, between 244 00:13:48,280 --> 00:13:51,520 Speaker 1: between the brain and music and maths. What I was 245 00:13:51,720 --> 00:13:55,280 Speaker 1: interested in knowing was whether anybody had ever actually taken 246 00:13:55,720 --> 00:13:59,480 Speaker 1: a piece of music and said, okay, here's here's here's 247 00:13:59,480 --> 00:14:02,240 Speaker 1: some math right here, right, because there are certain pieces 248 00:14:02,280 --> 00:14:03,800 Speaker 1: of music that I hear sometimes and I'm like, god, 249 00:14:03,840 --> 00:14:07,040 Speaker 1: I can I can't. Maybe geometrically, I can see things 250 00:14:07,200 --> 00:14:10,160 Speaker 1: going on in this music, um, which is sort of 251 00:14:10,200 --> 00:14:11,800 Speaker 1: interesting way you're talking about in your mind, not the 252 00:14:12,360 --> 00:14:15,520 Speaker 1: not the visualizer that pops up, yeah, exactly, not in 253 00:14:15,520 --> 00:14:17,520 Speaker 1: front of my computer with you know, I don't have 254 00:14:17,600 --> 00:14:22,720 Speaker 1: like purple splashes. Um. But what I found was that 255 00:14:22,760 --> 00:14:25,960 Speaker 1: there is a book called meta Magical Femus. It's called 256 00:14:26,040 --> 00:14:28,760 Speaker 1: Questing for the Essence of Mind and Pattern by Douglas 257 00:14:28,760 --> 00:14:32,040 Speaker 1: host Daughter And he actually looked at Chopin's music and 258 00:14:32,160 --> 00:14:35,000 Speaker 1: box as well, but he said, Chapon's music is filled 259 00:14:35,040 --> 00:14:38,200 Speaker 1: to the brim that I'm quoting with algebra algebraic tricks 260 00:14:38,200 --> 00:14:41,360 Speaker 1: of cross rhythm. A famous example is in his iconoclastic 261 00:14:41,360 --> 00:14:44,640 Speaker 1: waltz Opus forty two in a flat major written eighteen 262 00:14:44,720 --> 00:14:48,920 Speaker 1: forty and this waltz. The baseline follows the usual oompapa 263 00:14:49,320 --> 00:14:57,280 Speaker 1: convention of the waltz. I don't know if papa, yeah nice, yeah, okay, okay, 264 00:14:57,320 --> 00:14:59,840 Speaker 1: But the melody of the first section completely counters this 265 00:15:00,040 --> 00:15:03,960 Speaker 1: three nuts. It's six six eighth notes. Instead of being 266 00:15:03,960 --> 00:15:06,080 Speaker 1: broken up into three pairs aligned with the left hand 267 00:15:06,320 --> 00:15:10,080 Speaker 1: bounces while playing form two triplets. The initial notes of 268 00:15:10,120 --> 00:15:12,960 Speaker 1: the success of triplets are to be clearly emphasized and prolonged, 269 00:15:13,000 --> 00:15:16,160 Speaker 1: thus creating a higher level melody abstracted out of the 270 00:15:16,320 --> 00:15:20,640 Speaker 1: quietly rippling right hand. Yeah. I think I'm gonna have 271 00:15:20,640 --> 00:15:23,040 Speaker 1: to hear an example and put that together. Yes, yes, 272 00:15:23,080 --> 00:15:25,960 Speaker 1: And he's saying that this melody is composed of two 273 00:15:26,000 --> 00:15:28,400 Speaker 1: notes per measure beating regularly against three notes of a 274 00:15:28,440 --> 00:15:30,800 Speaker 1: waltzing base. And he says it's a marvelous trump let 275 00:15:30,920 --> 00:15:34,880 Speaker 1: aier effect, which which means the oral equivalent to an 276 00:15:34,880 --> 00:15:38,640 Speaker 1: optical illusion. Basically, So let's take a quick listen to 277 00:15:39,680 --> 00:15:43,240 Speaker 1: uh this waltz. It was forty two in a flat major. 278 00:15:53,680 --> 00:15:56,800 Speaker 1: I don't know, did you hear it? Um? Yeah, I 279 00:15:56,880 --> 00:15:59,000 Speaker 1: think I can. I can get a sense of some 280 00:15:59,080 --> 00:16:02,920 Speaker 1: of that coming together. I definitely got the oom Papa. Yes. 281 00:16:03,400 --> 00:16:06,280 Speaker 1: So that's one example where someone has actually tried to 282 00:16:06,320 --> 00:16:10,560 Speaker 1: map this, which is kind of interesting. And um. There 283 00:16:10,600 --> 00:16:14,160 Speaker 1: was another example that I found by mathematician Hence Strob, 284 00:16:14,200 --> 00:16:16,640 Speaker 1: and he talks about modal jazz. And the reason I 285 00:16:16,760 --> 00:16:19,960 Speaker 1: really wanted to look into this is because jazz modal 286 00:16:20,040 --> 00:16:23,880 Speaker 1: jazz is uh is someone like uh, it was like 287 00:16:24,360 --> 00:16:29,680 Speaker 1: Miles Davis. Miles Davis is usually attributed to be the 288 00:16:29,720 --> 00:16:32,640 Speaker 1: person that that sort of creative medal jazz are popularized 289 00:16:32,680 --> 00:16:36,800 Speaker 1: it um, particularly in the fifties. So this modal jazz 290 00:16:36,880 --> 00:16:39,960 Speaker 1: is is said to have a more horizontal structure, whereas 291 00:16:39,960 --> 00:16:43,720 Speaker 1: traditional jazz is structured more vertically, and modal just means 292 00:16:43,720 --> 00:16:45,040 Speaker 1: that he took a bunch of notes and he sort 293 00:16:45,040 --> 00:16:49,000 Speaker 1: of squished them all in this my my horrible understanding 294 00:16:49,040 --> 00:16:53,280 Speaker 1: of both mathematics and UM and music theory. Um. So 295 00:16:53,400 --> 00:16:55,760 Speaker 1: it just seems weird that jazz would like I thought 296 00:16:55,840 --> 00:16:58,920 Speaker 1: jazz was free flowing, man. I thought you can't put 297 00:16:59,000 --> 00:17:02,600 Speaker 1: math on jazz. Jazz as its own rhythm. Yeah, well 298 00:17:02,640 --> 00:17:05,520 Speaker 1: that's the incredible thing. And that's why I love Miles 299 00:17:05,600 --> 00:17:08,240 Speaker 1: Davis is because it does seem like there's a lot 300 00:17:08,280 --> 00:17:12,560 Speaker 1: of um sort of off off the cuff playing, right, 301 00:17:13,040 --> 00:17:14,639 Speaker 1: But I mean, the fact of the matter is is 302 00:17:14,680 --> 00:17:19,560 Speaker 1: that they're taking some some very um concentric like rhythms 303 00:17:19,960 --> 00:17:21,960 Speaker 1: and then they're playing off of that. So what you 304 00:17:22,040 --> 00:17:24,240 Speaker 1: might hear which sounds sort of like, oh wow, man, 305 00:17:24,280 --> 00:17:28,040 Speaker 1: that that cat is just going nuts on the saxophone, Um, 306 00:17:28,119 --> 00:17:30,360 Speaker 1: they are, but but they're doing it in the sort 307 00:17:30,400 --> 00:17:33,359 Speaker 1: of loops, um, these horizontal loops, and they're not doing 308 00:17:33,400 --> 00:17:36,080 Speaker 1: a lot of key changes. So let me try tokay. So, like, 309 00:17:36,400 --> 00:17:39,639 Speaker 1: if you had like a really crazy story that that 310 00:17:39,640 --> 00:17:42,560 Speaker 1: that at its heart followed a traditional story arc, even 311 00:17:42,560 --> 00:17:44,959 Speaker 1: if it involved like art arts from Mars in love 312 00:17:45,040 --> 00:17:47,359 Speaker 1: with each other or something. Yeah, yeah, And everybody knows 313 00:17:47,400 --> 00:17:50,360 Speaker 1: that that once you start, you know, to be good 314 00:17:50,359 --> 00:17:52,719 Speaker 1: at any craft, right, you have to know the absolute basics. 315 00:17:52,760 --> 00:17:55,040 Speaker 1: You have to master it. And um, you know, Myles 316 00:17:55,040 --> 00:17:58,480 Speaker 1: Savis is someone who certainly was master at what he did, 317 00:17:58,920 --> 00:18:01,320 Speaker 1: So that gave him the othery to sort of riff 318 00:18:01,359 --> 00:18:04,840 Speaker 1: off of stuff and um, play with modal notes and 319 00:18:04,840 --> 00:18:06,719 Speaker 1: and do all these sort of different things that actually 320 00:18:06,800 --> 00:18:10,840 Speaker 1: changed people's perception of that music itself. So what I 321 00:18:10,840 --> 00:18:13,560 Speaker 1: thought was interesting about it is that this this guy Hendstrub, 322 00:18:13,640 --> 00:18:16,280 Speaker 1: he talks about the traditional jazz being structured more vertically, 323 00:18:16,280 --> 00:18:19,800 Speaker 1: which means in this context that traditional jazz impro improvisations 324 00:18:19,800 --> 00:18:23,480 Speaker 1: are based on chord progressions and modal jazz. On the 325 00:18:23,520 --> 00:18:28,120 Speaker 1: other hand, improvised improvisations typically go on for long periods 326 00:18:28,160 --> 00:18:30,520 Speaker 1: without any chord change. So that so I was talking 327 00:18:30,520 --> 00:18:33,480 Speaker 1: about earlier, and the interest is more turned towards the 328 00:18:33,480 --> 00:18:37,879 Speaker 1: melodic line. Uh So, it's it's a That's why I 329 00:18:37,880 --> 00:18:39,280 Speaker 1: thought it was sort of interesting to me because I 330 00:18:39,280 --> 00:18:41,280 Speaker 1: thought I can see that visually. I can see that 331 00:18:41,280 --> 00:18:44,560 Speaker 1: in Miles Davis's music. You can see this horizontal spreading. 332 00:18:44,560 --> 00:18:46,400 Speaker 1: You can see in Yo yo mom when he does 333 00:18:47,200 --> 00:18:50,720 Speaker 1: uh the box suitets um. You can see it maybe 334 00:18:50,720 --> 00:18:52,879 Speaker 1: even in like PJ. Harvey and like White Chalk, like 335 00:18:52,920 --> 00:18:55,119 Speaker 1: the Cults an album that has sort of like this 336 00:18:55,359 --> 00:18:58,800 Speaker 1: horizontal spreading, although you could say there are some there's 337 00:18:58,840 --> 00:19:02,280 Speaker 1: some vertical loops of coophany in that as well. But anyway, 338 00:19:02,359 --> 00:19:05,920 Speaker 1: let's let's just listen to a quick clip from kind 339 00:19:05,920 --> 00:19:21,680 Speaker 1: of Blue Miles Davis. Cool. Yeah, Now, did you say 340 00:19:21,760 --> 00:19:25,399 Speaker 1: this is actually your favorite track, your favorite song, favorite album? 341 00:19:25,440 --> 00:19:28,560 Speaker 1: I mean the entire album is my favorite. There's actually 342 00:19:28,600 --> 00:19:30,560 Speaker 1: not one song on there that I would say that 343 00:19:30,600 --> 00:19:32,760 Speaker 1: is my absolute favorite. I love it as a whole piece, 344 00:19:33,040 --> 00:19:35,680 Speaker 1: and um, you know we've talked about this before and 345 00:19:35,920 --> 00:19:38,159 Speaker 1: getting in the zone, and um, this is one of 346 00:19:38,160 --> 00:19:41,239 Speaker 1: those pieces of music that I can listen to and 347 00:19:41,320 --> 00:19:43,000 Speaker 1: it does sound it kind of put me into a 348 00:19:43,040 --> 00:19:46,359 Speaker 1: different state that allows me to think clearer, think at 349 00:19:46,440 --> 00:19:49,159 Speaker 1: higher levels. I think, is why I like it. And 350 00:19:49,200 --> 00:19:51,560 Speaker 1: also we've talked about this too, like lyrics sometimes bother 351 00:19:51,720 --> 00:19:56,640 Speaker 1: me when I'm trying to cogitate up in Monogaen. So 352 00:19:56,800 --> 00:19:59,520 Speaker 1: you know, that's that's that's some of the discovery here 353 00:19:59,600 --> 00:20:01,639 Speaker 1: where we're seeing that the music and the math, at 354 00:20:01,680 --> 00:20:04,000 Speaker 1: least again geometrically, I can see it. I don't know 355 00:20:04,040 --> 00:20:06,320 Speaker 1: if it's the same for other people. But there's a 356 00:20:06,320 --> 00:20:09,240 Speaker 1: guy named Dave Russ, and he's associate professor of mathematics 357 00:20:09,320 --> 00:20:12,879 Speaker 1: at Northern Illinois University, and he really does try to 358 00:20:12,960 --> 00:20:16,520 Speaker 1: make this correlation between music and math, and he thinks 359 00:20:16,520 --> 00:20:20,640 Speaker 1: it's important for for students to better understand math. In fact, well, 360 00:20:20,720 --> 00:20:24,439 Speaker 1: he says mathematics, like music, embodies certain patterns and ideas 361 00:20:24,480 --> 00:20:30,600 Speaker 1: which don't translate well into words, as we found out. Uh, 362 00:20:30,960 --> 00:20:33,440 Speaker 1: as you listener, hath end up. We can feel them, 363 00:20:33,480 --> 00:20:36,760 Speaker 1: see them, understand them, but only after we have really 364 00:20:36,840 --> 00:20:39,399 Speaker 1: worked to lift them off the paper and into our minds, 365 00:20:39,720 --> 00:20:41,960 Speaker 1: only after we've tried to see where they come from, 366 00:20:42,080 --> 00:20:47,480 Speaker 1: only after considerable practice with the minutia, gradually adding the trills. Uh, 367 00:20:47,520 --> 00:20:50,280 Speaker 1: do we have the full spirit of the idea? Mathematics 368 00:20:50,280 --> 00:20:53,359 Speaker 1: like music as a human adventure, people create and discover it, 369 00:20:53,680 --> 00:20:56,480 Speaker 1: they try to then share it and enjoy it. Yeah. 370 00:20:56,640 --> 00:20:58,320 Speaker 1: I mean I I definitely found that to be the 371 00:20:58,320 --> 00:21:01,320 Speaker 1: case with both music and mathematics, because on one hand, 372 00:21:01,400 --> 00:21:05,600 Speaker 1: I love um certain genres of music, and I'll you know, 373 00:21:05,640 --> 00:21:07,600 Speaker 1: I'll listen to it all the time, but I'm not 374 00:21:07,640 --> 00:21:10,280 Speaker 1: necessarily really good at describing what's great about it. Like 375 00:21:10,320 --> 00:21:11,920 Speaker 1: if if I'm like, you know, talking to a friend, 376 00:21:11,960 --> 00:21:13,600 Speaker 1: I'm like, oh, you gotta listen to this new mix 377 00:21:13,640 --> 00:21:14,920 Speaker 1: by so and so, and they might be like, well, 378 00:21:14,920 --> 00:21:17,080 Speaker 1: what's awesome about it? And I may be a little 379 00:21:17,080 --> 00:21:19,040 Speaker 1: stump for words, you know, unless I have some time 380 00:21:19,080 --> 00:21:23,400 Speaker 1: to prep. Likewise, with mathematics, I was the last week 381 00:21:23,400 --> 00:21:26,359 Speaker 1: I was working on an article about number theory and 382 00:21:26,400 --> 00:21:30,200 Speaker 1: like number theory. Especially when writing for a general audience 383 00:21:30,320 --> 00:21:34,719 Speaker 1: and a you know, non math audience, it's it quickly 384 00:21:34,800 --> 00:21:39,120 Speaker 1: becomes a conversation that cannot be really held in English 385 00:21:39,200 --> 00:21:41,320 Speaker 1: but needs to be held or any language, but needs 386 00:21:41,320 --> 00:21:43,840 Speaker 1: to be held in math. You know, it needs to 387 00:21:43,840 --> 00:21:47,240 Speaker 1: be held with numerals and and equations. So it becomes 388 00:21:47,240 --> 00:21:51,199 Speaker 1: increasingly difficult to to explain the topic without being the 389 00:21:51,240 --> 00:21:54,680 Speaker 1: topic right right. And that's why us wildly humans, I suppose, 390 00:21:54,840 --> 00:21:57,480 Speaker 1: turned to math and music to try to express ourselves 391 00:21:57,480 --> 00:22:00,240 Speaker 1: and our ideas and in a better way. Yeah, because 392 00:22:00,359 --> 00:22:02,320 Speaker 1: I think I saw it pointed out that both both 393 00:22:02,400 --> 00:22:05,359 Speaker 1: music and math are like they're self describing things. The 394 00:22:05,440 --> 00:22:10,200 Speaker 1: music describes itself, the math describes itself, and h and yeah, 395 00:22:10,240 --> 00:22:11,879 Speaker 1: at the at the end of the day, it kind 396 00:22:11,880 --> 00:22:14,159 Speaker 1: of sounds like, you know, defeatist, but they both kind 397 00:22:14,160 --> 00:22:18,119 Speaker 1: of described themselves the best. There we go looking in 398 00:22:18,160 --> 00:22:22,720 Speaker 1: the mirror. I'm trying to change the world. I don't 399 00:22:22,760 --> 00:22:25,919 Speaker 1: know I was trying to do, Michael Jackson, there apologize 400 00:22:26,760 --> 00:22:29,280 Speaker 1: you were trying to do like an impersonation. I was 401 00:22:29,320 --> 00:22:31,800 Speaker 1: thinking that math and music we're looking at each other 402 00:22:31,800 --> 00:22:33,760 Speaker 1: in the world. And then excuse me, looking at each 403 00:22:33,800 --> 00:22:35,240 Speaker 1: other in the mirror, and then I started thinking about 404 00:22:35,240 --> 00:22:38,000 Speaker 1: that song man in the mirror. Oh, it's just bad 405 00:22:38,040 --> 00:22:40,439 Speaker 1: all around. No, No, it wasn't that bad. It was good. 406 00:22:40,960 --> 00:22:44,920 Speaker 1: You did fun um. If we have the speaking of math, 407 00:22:45,160 --> 00:22:47,520 Speaker 1: we have a listener mail here, a listener by the 408 00:22:47,560 --> 00:22:49,679 Speaker 1: name of Timothy. He says, hello, stuff to all your 409 00:22:49,720 --> 00:22:51,639 Speaker 1: mind crew. I just wanted to say thank you for 410 00:22:51,760 --> 00:22:54,800 Speaker 1: the unusually deep mathematics podcast. I am a science and 411 00:22:54,840 --> 00:22:57,320 Speaker 1: philosophy enthusiast, and I just happened to be in the 412 00:22:57,320 --> 00:22:59,440 Speaker 1: middle of a book called A World Without Time, the 413 00:22:59,520 --> 00:23:02,879 Speaker 1: Forgotten Legacy of Godal and Einstein when you aired your podcast. 414 00:23:03,320 --> 00:23:06,879 Speaker 1: I personally believe that Godal's incompleteness, theorems, the existence of 415 00:23:06,960 --> 00:23:12,320 Speaker 1: non eucludean geometries, the necessity of imaginary numbers, and such 416 00:23:12,400 --> 00:23:15,520 Speaker 1: all point to math is a formal system invented by humans. 417 00:23:15,760 --> 00:23:18,359 Speaker 1: It strikes me as something similar to a game like chess, 418 00:23:18,640 --> 00:23:23,040 Speaker 1: where simple rules give rise to an incredibly complex overall system. 419 00:23:23,119 --> 00:23:26,040 Speaker 1: I could imagine a chess like game being created to 420 00:23:26,119 --> 00:23:29,080 Speaker 1: model physics. What is interesting to me is that Godal, 421 00:23:29,200 --> 00:23:32,719 Speaker 1: like many mathematicians, was of the opposite persuasion. He believed 422 00:23:32,720 --> 00:23:36,840 Speaker 1: that math exists independent of the human mind. By the way, 423 00:23:36,880 --> 00:23:39,600 Speaker 1: one of my favorite books is also godal escher Bach 424 00:23:39,720 --> 00:23:46,720 Speaker 1: by Douglas hofstadtur Hofstadter Yeah, can we as ye, which 425 00:23:46,760 --> 00:23:49,399 Speaker 1: I highly recommend it to any listeners who also enjoyed 426 00:23:49,440 --> 00:23:51,640 Speaker 1: the Math podcast. Thank you for all the hard work 427 00:23:51,720 --> 00:23:55,879 Speaker 1: you to do, Tim. Thanks Tim. Yeah, so, yeah, the 428 00:23:56,240 --> 00:23:59,120 Speaker 1: we have the podcast that we've in referenced earlier. Um 429 00:23:59,359 --> 00:24:02,880 Speaker 1: is math a human invention or a human discovery? And uh, yeah, 430 00:24:02,920 --> 00:24:05,080 Speaker 1: that was a lot of fun to do. Yeah it was. 431 00:24:05,200 --> 00:24:08,159 Speaker 1: And and uh again, we were both a little bit 432 00:24:08,160 --> 00:24:11,040 Speaker 1: trepidacious about, you know, entering into the realm of math, 433 00:24:11,160 --> 00:24:14,520 Speaker 1: but it turns out it was not painful at all. Yeah, 434 00:24:14,840 --> 00:24:16,719 Speaker 1: And if you want to enter into our realm, then 435 00:24:16,760 --> 00:24:18,720 Speaker 1: all you have to do is check out Facebook and Twitter. 436 00:24:19,040 --> 00:24:21,600 Speaker 1: It is not painful either, not painful at all. I 437 00:24:21,600 --> 00:24:23,600 Speaker 1: mean unless like twitters down or something, and it can 438 00:24:23,640 --> 00:24:25,920 Speaker 1: be a little frustrating. But now we'll blow the mind 439 00:24:25,960 --> 00:24:27,560 Speaker 1: on both of those and we update that with all 440 00:24:27,600 --> 00:24:30,000 Speaker 1: sorts of links to cool stuff. We're reading cool stuff, 441 00:24:30,000 --> 00:24:33,480 Speaker 1: we're writing cool stuff that we just podcasts about, and 442 00:24:33,560 --> 00:24:35,240 Speaker 1: we would love to hear from you. So Please feel 443 00:24:35,280 --> 00:24:37,240 Speaker 1: free to drop us a line at blow the Mind 444 00:24:37,280 --> 00:24:44,560 Speaker 1: at how stuff works dot com. Be sure to check 445 00:24:44,600 --> 00:24:47,760 Speaker 1: out our new video podcast, Stuff from the Future. Join 446 00:24:47,800 --> 00:24:50,320 Speaker 1: how Stuff Work staff as we explore the most promising 447 00:24:50,400 --> 00:24:52,720 Speaker 1: and perplexing possibilities of tomorrow.