1 00:00:00,320 --> 00:00:02,880 Speaker 1: Brought to you by the reinvented two thousand twelve camera. 2 00:00:03,200 --> 00:00:08,920 Speaker 1: It's ready. Are you get in touch with technology with 3 00:00:09,039 --> 00:00:17,880 Speaker 1: tech Stuff from how stuff works dot com. Hello again, everyone, 4 00:00:17,920 --> 00:00:20,160 Speaker 1: welcome to tech Stuff. My name is Chris Poulette, and 5 00:00:20,200 --> 00:00:21,919 Speaker 1: I am the tech editor here at how stuff works 6 00:00:21,920 --> 00:00:24,840 Speaker 1: dot com. And sitting across from me, as he always does, 7 00:00:25,320 --> 00:00:28,159 Speaker 1: is senior writer Jonathan Strickland. And I would like to 8 00:00:28,280 --> 00:00:31,880 Speaker 1: rock and roll all night and party every day. Well, 9 00:00:31,920 --> 00:00:35,760 Speaker 1: and you can, thank you. Let's start off with a 10 00:00:35,760 --> 00:00:45,760 Speaker 1: little listener mail. This little listener mail comes from Charlie. Hey, Charlie, 11 00:00:46,159 --> 00:00:50,080 Speaker 1: sorry at a little unicorn moment there, says okay, you 12 00:00:50,080 --> 00:00:53,680 Speaker 1: haven't seen that video? All right, Charlie the unicorn. We're 13 00:00:53,680 --> 00:00:57,240 Speaker 1: watching it after this episode. Hi guys, I'm a big 14 00:00:57,280 --> 00:00:59,880 Speaker 1: fan and longtime listener. I've been noticing a lot of 15 00:01:00,000 --> 00:01:02,520 Speaker 1: positions have been using something known as auto tune more 16 00:01:02,560 --> 00:01:05,440 Speaker 1: prominently than ever lately. How does this work? Is this 17 00:01:05,480 --> 00:01:09,600 Speaker 1: a new technology? Keep up the great work, Charlie, so um. 18 00:01:09,959 --> 00:01:11,840 Speaker 1: Auto tune has been around for a while, as it 19 00:01:11,880 --> 00:01:16,119 Speaker 1: turns out, and another podcast covered this briefly, and it 20 00:01:16,160 --> 00:01:19,720 Speaker 1: wasn't high speed stuff. Although they do talk about autos 21 00:01:19,800 --> 00:01:21,880 Speaker 1: and tuning. It was stuff from the B Sides, which 22 00:01:21,920 --> 00:01:24,080 Speaker 1: had an episode about auto tuning, but we were going 23 00:01:24,160 --> 00:01:26,920 Speaker 1: to cover it as well. So auto tuning is also 24 00:01:26,959 --> 00:01:31,200 Speaker 1: known as pitch correction. Yes, it's when it's it's being 25 00:01:31,240 --> 00:01:34,759 Speaker 1: able to do digitally nudge a person's voice. So it's 26 00:01:34,760 --> 00:01:38,559 Speaker 1: closer to being on pitch um Now in the good 27 00:01:38,560 --> 00:01:40,440 Speaker 1: old days, and by the good old days, I mean 28 00:01:40,760 --> 00:01:45,800 Speaker 1: the old in the old days, what you would do 29 00:01:45,920 --> 00:01:48,840 Speaker 1: is you get a group of musicians in the studio 30 00:01:48,920 --> 00:01:52,320 Speaker 1: and you would start recording tracks, and whenever the lead 31 00:01:52,400 --> 00:01:55,600 Speaker 1: vocalist would uh would flub a note, you would just 32 00:01:55,680 --> 00:01:58,160 Speaker 1: make a mark of that and you would do another take, 33 00:01:58,720 --> 00:02:01,480 Speaker 1: and you do another take, and you do another take, 34 00:02:01,520 --> 00:02:03,400 Speaker 1: and even for the ones that sounded good all the 35 00:02:03,400 --> 00:02:07,280 Speaker 1: way through, you would do extra takes and then you 36 00:02:07,320 --> 00:02:11,040 Speaker 1: would cobble together the best sounding song from those multiple 37 00:02:11,120 --> 00:02:16,160 Speaker 1: takes using actual editing UH procedures. Yes um. Speaking as 38 00:02:16,160 --> 00:02:19,040 Speaker 1: someone who's gone through this process, I can tell you 39 00:02:19,080 --> 00:02:21,880 Speaker 1: it's not not nearly as much fun as it sounds, 40 00:02:21,880 --> 00:02:23,560 Speaker 1: and it doesn't really sound like all that much fun. 41 00:02:23,680 --> 00:02:27,320 Speaker 1: And before digital techniques, we're talking about things like splicing 42 00:02:27,400 --> 00:02:31,160 Speaker 1: sections of tape together with you know, a razor blade 43 00:02:31,200 --> 00:02:34,280 Speaker 1: and and you know, splicing material, trying to get it 44 00:02:34,400 --> 00:02:37,400 Speaker 1: so that you have one long, continuous take that is 45 00:02:37,440 --> 00:02:39,720 Speaker 1: in tune right, and you have to be very careful 46 00:02:39,720 --> 00:02:41,680 Speaker 1: to make sure it's all matched up just right so 47 00:02:41,800 --> 00:02:46,520 Speaker 1: that you can't detect the break beaus taking pains, taking work, 48 00:02:46,760 --> 00:02:49,400 Speaker 1: and before that, you're pretty much just stuck with whatever 49 00:02:49,440 --> 00:02:52,600 Speaker 1: you got ding. Like if if if you were recording, 50 00:02:52,680 --> 00:02:55,360 Speaker 1: especially on something like say, I don't know a wax cylinder, 51 00:02:56,200 --> 00:02:58,640 Speaker 1: it didn't matter if you flubbed it. That was how 52 00:02:58,680 --> 00:03:01,560 Speaker 1: that was gonna go out, warts and all all. But 53 00:03:01,560 --> 00:03:05,359 Speaker 1: But as as we began to get better at editing music, 54 00:03:05,600 --> 00:03:08,600 Speaker 1: are standards started to go up, and we began to 55 00:03:08,960 --> 00:03:12,120 Speaker 1: refuse to listen to music that seemed to have uh 56 00:03:12,320 --> 00:03:14,480 Speaker 1: some flaws, and that we the fewer the flaws, the 57 00:03:14,520 --> 00:03:18,080 Speaker 1: better in our opinion. Uh, in general, there's still people 58 00:03:18,080 --> 00:03:20,880 Speaker 1: out there who prefer the more genuine music, if you 59 00:03:20,880 --> 00:03:22,960 Speaker 1: want to call it that. I'm not going to get 60 00:03:23,000 --> 00:03:26,480 Speaker 1: into that argument, because, uh, there are those people who 61 00:03:26,560 --> 00:03:28,760 Speaker 1: love the super produced stuff, and they're the people who 62 00:03:28,760 --> 00:03:30,600 Speaker 1: love the strip down stuff. And I don't think anyone 63 00:03:30,720 --> 00:03:34,200 Speaker 1: is wrong. Um, and you know, it's all a matter 64 00:03:34,240 --> 00:03:37,480 Speaker 1: of personal opinion at any rate, So editing that was 65 00:03:37,520 --> 00:03:40,160 Speaker 1: the only way you could really get rid of a 66 00:03:40,200 --> 00:03:44,960 Speaker 1: flubbed note. But then a fellow by the name of 67 00:03:45,360 --> 00:03:49,920 Speaker 1: Harold Hildebrand, better known as Andy to his buddies, came 68 00:03:50,000 --> 00:03:54,760 Speaker 1: up with a special kind of software. It's this is 69 00:03:55,200 --> 00:03:58,760 Speaker 1: believe it or not, the oil industry's contribution to music. 70 00:03:59,000 --> 00:04:03,000 Speaker 1: That is not the joke. It really is. Mr Hildebrand, 71 00:04:03,000 --> 00:04:06,280 Speaker 1: as it turns out, before he got into the world 72 00:04:06,360 --> 00:04:09,800 Speaker 1: of making musicians sound better than they really do, was 73 00:04:09,920 --> 00:04:16,880 Speaker 1: a geophysicist. He created seismic data processing software, and this 74 00:04:16,960 --> 00:04:19,920 Speaker 1: was a software that would sort of measure the the 75 00:04:20,320 --> 00:04:23,840 Speaker 1: the seismic vibrations for oil companies to kind of get 76 00:04:23,839 --> 00:04:26,760 Speaker 1: an idea of where the best oil deposits were, whether 77 00:04:26,839 --> 00:04:28,800 Speaker 1: or not that were any oil deposits, that kind of thing, 78 00:04:29,120 --> 00:04:33,080 Speaker 1: because it's it's called auto correlation. Basically, once this sound 79 00:04:33,200 --> 00:04:36,320 Speaker 1: goes into the ground, the reflections based on the material 80 00:04:37,120 --> 00:04:39,480 Speaker 1: uh that is made up and you know, in the 81 00:04:39,480 --> 00:04:42,800 Speaker 1: area that they're using the the sound give them an 82 00:04:42,800 --> 00:04:45,640 Speaker 1: idea of what the composition of of the earth is 83 00:04:45,760 --> 00:04:49,960 Speaker 1: underneath their feet essentially and can tell them where pockets 84 00:04:49,960 --> 00:04:52,320 Speaker 1: of oil are stored, so it gives them a good 85 00:04:52,360 --> 00:04:55,360 Speaker 1: idea of where to to drill. And he uh Andy 86 00:04:55,440 --> 00:04:57,760 Speaker 1: Hildebrand made a lot of money, a whole lot of money, 87 00:04:57,880 --> 00:05:00,800 Speaker 1: retired at forty Yeah and clear. Really the next step 88 00:05:00,839 --> 00:05:03,320 Speaker 1: for anyone who creates that kind of software is finding 89 00:05:03,320 --> 00:05:05,719 Speaker 1: a way to get people to sing better. Well, the 90 00:05:05,720 --> 00:05:09,760 Speaker 1: way I heard it, a friend challenged him, said, okay, fine, 91 00:05:09,839 --> 00:05:12,960 Speaker 1: you're so smart, you're looking for something to do. Why 92 00:05:12,960 --> 00:05:15,840 Speaker 1: didn't you fix it so I can sing better? And 93 00:05:15,880 --> 00:05:19,680 Speaker 1: so he did. Yeah. So this is using a method 94 00:05:19,760 --> 00:05:24,839 Speaker 1: called digital signal processing. And the idea here is that 95 00:05:25,320 --> 00:05:29,320 Speaker 1: every sound that you hear is is really due to 96 00:05:29,560 --> 00:05:34,640 Speaker 1: vibrations everything. Yes, every sound is something vibrating against something else, 97 00:05:34,680 --> 00:05:38,000 Speaker 1: and then eventually it becomes air molecules vibrating against one another, 98 00:05:38,440 --> 00:05:41,279 Speaker 1: and then the vibrations hit your ear and uh, and 99 00:05:41,360 --> 00:05:45,200 Speaker 1: your brain manages to uh to translate this into sound 100 00:05:46,120 --> 00:05:51,320 Speaker 1: what we perceive as sound. So uh, the the notes 101 00:05:51,400 --> 00:05:57,040 Speaker 1: that we hear are vibrations at particular frequencies, and in general, 102 00:05:57,080 --> 00:05:59,280 Speaker 1: the higher the frequency, actually not in general, the higher 103 00:05:59,279 --> 00:06:01,680 Speaker 1: the frequency, the higher the sound, the pitch and the 104 00:06:01,720 --> 00:06:04,760 Speaker 1: sound right, so um, let's see if I can find 105 00:06:04,800 --> 00:06:08,680 Speaker 1: then the information I actually wrote down what the different 106 00:06:08,680 --> 00:06:11,760 Speaker 1: divisions were. I think four hundred and forty vibrations per 107 00:06:11,800 --> 00:06:14,159 Speaker 1: second is an A note. That is correct, So that's 108 00:06:14,160 --> 00:06:18,880 Speaker 1: your basic A. So you're basically is four vibrations per second. 109 00:06:18,880 --> 00:06:21,800 Speaker 1: And I'm I'm sitting here with a musician, so I 110 00:06:21,839 --> 00:06:24,760 Speaker 1: expect you to correct me whenever and I get things wrong. Well, 111 00:06:24,760 --> 00:06:26,560 Speaker 1: I had a tuning fork, but I had forgotten we 112 00:06:26,560 --> 00:06:28,080 Speaker 1: were doing this today, so I left her to have them. 113 00:06:28,080 --> 00:06:31,359 Speaker 1: Oh that's a shame that would have been coming. Alright, 114 00:06:31,400 --> 00:06:33,680 Speaker 1: So four and forty isn't a and then you can 115 00:06:34,000 --> 00:06:37,159 Speaker 1: if you increase that the vibrations per second, you then 116 00:06:37,720 --> 00:06:43,000 Speaker 1: the notes go up. And uh so I actually, let's 117 00:06:43,000 --> 00:06:46,159 Speaker 1: say four vibrations per second would be a B note. 118 00:06:47,560 --> 00:06:50,680 Speaker 1: Five and eighty seven vibrations per second or thereabouts would 119 00:06:50,720 --> 00:06:57,320 Speaker 1: be a C note, which is not Shaving and haircut, 120 00:06:57,440 --> 00:07:03,200 Speaker 1: all right, So that's about these days. Never mind, I 121 00:07:03,240 --> 00:07:04,839 Speaker 1: can't tell I was about to out one of our 122 00:07:04,960 --> 00:07:07,240 Speaker 1: one of our coworkers who did recently spend more than 123 00:07:07,279 --> 00:07:10,000 Speaker 1: a hundred dollars on a haircut. But I will not 124 00:07:10,080 --> 00:07:15,360 Speaker 1: do that because this person will kill me anyway at 125 00:07:15,360 --> 00:07:19,200 Speaker 1: any rate. So, yes, the vibrations determine what the note is. 126 00:07:19,440 --> 00:07:22,200 Speaker 1: And so let's say that you're trying to sing an 127 00:07:22,240 --> 00:07:24,160 Speaker 1: a note. Now, if you're trying to sing an a note, 128 00:07:24,160 --> 00:07:27,760 Speaker 1: what's happening is your vocal cords are vibrating to generate 129 00:07:27,840 --> 00:07:32,280 Speaker 1: this and that's what's generating the sound. Right. So uh, 130 00:07:32,400 --> 00:07:35,440 Speaker 1: most of us are not capable of holding an a 131 00:07:35,560 --> 00:07:39,800 Speaker 1: note perfectly, um, for any extended time. I mean we're 132 00:07:39,840 --> 00:07:43,520 Speaker 1: gonna are are It's going to wander a little bit. Yes, 133 00:07:43,600 --> 00:07:45,480 Speaker 1: I I tend to Uh, I tend to sing a 134 00:07:45,480 --> 00:07:48,080 Speaker 1: little sharp, to be honest, Yeah, I tend. I tend 135 00:07:48,120 --> 00:07:50,760 Speaker 1: to sing in a different key, but at any rate, 136 00:07:50,840 --> 00:07:54,760 Speaker 1: so uh, or sometimes my wife prefers it if I 137 00:07:54,800 --> 00:07:59,120 Speaker 1: sing in a different state. Um. But the so if 138 00:07:59,160 --> 00:08:01,320 Speaker 1: you if you visual is each note with a line 139 00:08:01,400 --> 00:08:03,640 Speaker 1: going to the right. So let's say you know you 140 00:08:03,720 --> 00:08:07,040 Speaker 1: have a B C yeah, and you have the lines 141 00:08:07,320 --> 00:08:11,320 Speaker 1: to the right, uh, and you think of the person singing, 142 00:08:11,680 --> 00:08:13,560 Speaker 1: it tends to look kind of like a sign wave. 143 00:08:13,640 --> 00:08:16,040 Speaker 1: I mean, it usually tends to hover around the note, 144 00:08:16,120 --> 00:08:18,000 Speaker 1: unless the person is a terrible singer, in which case 145 00:08:18,000 --> 00:08:19,800 Speaker 1: it may not be anywhere close to the note they're 146 00:08:19,840 --> 00:08:23,160 Speaker 1: supposed to be singing generally, if you can never mind. Yeah, 147 00:08:23,360 --> 00:08:24,960 Speaker 1: I see, I see what you're see what I'm saying. 148 00:08:24,960 --> 00:08:26,960 Speaker 1: So let's say let's say I'm trying to sing an A, 149 00:08:27,200 --> 00:08:30,000 Speaker 1: but I have terrible pitch and I'm tone deaf, and 150 00:08:30,040 --> 00:08:33,720 Speaker 1: I'm actually singing what is closer to a B. Well, 151 00:08:33,960 --> 00:08:36,840 Speaker 1: I would say, I would argue even that someone who 152 00:08:36,960 --> 00:08:39,480 Speaker 1: is a really good singer is going to waiver in 153 00:08:39,559 --> 00:08:44,000 Speaker 1: pitch somewhat because the vibration of your vocal chords depends 154 00:08:44,040 --> 00:08:47,079 Speaker 1: a lot on how much air uh you're putting in, 155 00:08:47,160 --> 00:08:50,200 Speaker 1: and if you are running out of breath, yeah, it 156 00:08:50,200 --> 00:08:53,320 Speaker 1: tends to peter l your your attending. Yeah, the pitch 157 00:08:53,360 --> 00:08:56,360 Speaker 1: of your voice is going to change. So so, I mean, 158 00:08:56,400 --> 00:08:58,360 Speaker 1: even even the best singers are going to have this problem. 159 00:08:58,400 --> 00:09:00,760 Speaker 1: So what Hildebrand did was he decided to create some 160 00:09:00,840 --> 00:09:05,520 Speaker 1: software that could nudge this these these variations around a 161 00:09:05,559 --> 00:09:08,080 Speaker 1: note or sometimes you know, hitting the wrong note entirely 162 00:09:08,640 --> 00:09:11,680 Speaker 1: and put them where they're supposed to be, so kind 163 00:09:11,720 --> 00:09:15,360 Speaker 1: of smoothing out the peaks and valleys across the line 164 00:09:15,400 --> 00:09:19,120 Speaker 1: so to to make it a more a more consistent note, 165 00:09:19,320 --> 00:09:21,800 Speaker 1: or to even shift it up or down the scale 166 00:09:22,280 --> 00:09:25,680 Speaker 1: so that it hits the note it's supposed to be on. Now, 167 00:09:25,960 --> 00:09:29,000 Speaker 1: you can only do this a little bit within within 168 00:09:29,080 --> 00:09:31,400 Speaker 1: a couple of notes of where you're supposed to be 169 00:09:32,160 --> 00:09:35,920 Speaker 1: without its sounding artificial, right, And there's there's a lot 170 00:09:35,920 --> 00:09:38,720 Speaker 1: of other little factors in there, because the the auto 171 00:09:38,760 --> 00:09:42,400 Speaker 1: tune software gives you some control over how quickly the 172 00:09:42,520 --> 00:09:46,120 Speaker 1: pitch shifts up. But you can you can actually set 173 00:09:46,160 --> 00:09:48,760 Speaker 1: the range, uh the key that you're supposed to be 174 00:09:48,800 --> 00:09:52,680 Speaker 1: singing in, so it can it can. It has some 175 00:09:52,800 --> 00:09:56,120 Speaker 1: idea of what you're trying to do, so you can. 176 00:09:56,200 --> 00:09:58,920 Speaker 1: You can have an auto detect, like if if you 177 00:09:58,920 --> 00:10:01,240 Speaker 1: put on auto detect. Essentially, what the software does is 178 00:10:01,280 --> 00:10:04,720 Speaker 1: it assumes whatever note you're singing closest to is the 179 00:10:04,760 --> 00:10:07,679 Speaker 1: note you wanted to sing. Yes, So if you are 180 00:10:07,800 --> 00:10:11,880 Speaker 1: at least a decent singer, the auto function of auto 181 00:10:11,920 --> 00:10:14,680 Speaker 1: tune should get you pretty much where you wanted to 182 00:10:14,720 --> 00:10:16,480 Speaker 1: be in the first place, even if you were, you know, 183 00:10:16,520 --> 00:10:19,800 Speaker 1: a little off. You can also do it manually, however, 184 00:10:19,880 --> 00:10:22,480 Speaker 1: so let's say that that someone has hit just you know, 185 00:10:22,600 --> 00:10:26,680 Speaker 1: just really misjudged it. They're singing the national anthem and 186 00:10:26,720 --> 00:10:29,400 Speaker 1: when they get to uh uh the Land, you know, 187 00:10:29,720 --> 00:10:32,400 Speaker 1: the Land of the Free, and they hit that high note, 188 00:10:32,480 --> 00:10:35,200 Speaker 1: it's just way off. Well, then you might need to 189 00:10:35,320 --> 00:10:38,280 Speaker 1: manually put it closer to the note it's supposed to 190 00:10:38,320 --> 00:10:41,280 Speaker 1: be on. So it doesn't sound terrible, right, it doesn't 191 00:10:41,280 --> 00:10:45,880 Speaker 1: work so well live, well it can not the manual. No, no, live, 192 00:10:45,920 --> 00:10:48,480 Speaker 1: it's auto. But now that that isn't that. One of 193 00:10:48,480 --> 00:10:50,600 Speaker 1: the things that impressed me about the auto tune software 194 00:10:50,640 --> 00:10:52,439 Speaker 1: is that it can be used live. It could be 195 00:10:52,559 --> 00:10:54,679 Speaker 1: used in real time. Now granted that's when it's using 196 00:10:54,679 --> 00:10:57,200 Speaker 1: the automatic feature, not the manual functure. As you were 197 00:10:57,200 --> 00:11:01,840 Speaker 1: pointing out, you are correct. Otherwise you would have like 198 00:11:01,880 --> 00:11:05,480 Speaker 1: the highest paid sound engineer on the planet, like rapidly 199 00:11:05,520 --> 00:11:11,040 Speaker 1: switching the the pitch. So yeah, the software has this 200 00:11:11,160 --> 00:11:14,240 Speaker 1: very complex algorithm and it can it can. The cool 201 00:11:14,240 --> 00:11:17,880 Speaker 1: thing is it can it can adjust the pitch without 202 00:11:18,000 --> 00:11:21,880 Speaker 1: really affecting the tone of the voice. Now, this is 203 00:11:21,880 --> 00:11:25,000 Speaker 1: a lot different from the old way of changing the pitch, 204 00:11:25,040 --> 00:11:28,600 Speaker 1: which was just essentially playing it faster than you had before. 205 00:11:29,000 --> 00:11:33,320 Speaker 1: Are you're thinking like those three rodents of recent movie fame, 206 00:11:33,440 --> 00:11:36,600 Speaker 1: the Chipmunks. Yeah, alright, so we're going to give Liz 207 00:11:36,640 --> 00:11:39,600 Speaker 1: a little challenge here. We're going to we're going to 208 00:11:39,600 --> 00:11:42,079 Speaker 1: speak in our normal tone of voice, but we're going 209 00:11:42,120 --> 00:11:49,640 Speaker 1: to do so slowly so that Liz can speed it 210 00:11:49,960 --> 00:12:03,400 Speaker 1: up later from or of voluble statter speaking there anyway, 211 00:12:03,480 --> 00:12:07,440 Speaker 1: So by by speaking that up, Liz could could adjust 212 00:12:07,559 --> 00:12:10,120 Speaker 1: the pitch of our voices. But of course that means that, 213 00:12:10,320 --> 00:12:13,120 Speaker 1: you know, the whole tone sounds different and it's going 214 00:12:13,240 --> 00:12:16,280 Speaker 1: much faster than before. The neat thing about auto tune 215 00:12:16,320 --> 00:12:19,719 Speaker 1: is it doesn't adjust the speed of the voice. It 216 00:12:19,800 --> 00:12:23,160 Speaker 1: doesn't really affect the tone that much, unless again, you're 217 00:12:23,160 --> 00:12:25,400 Speaker 1: trying to push it much further up or down the 218 00:12:25,440 --> 00:12:29,120 Speaker 1: scale than where it originally started. Um, so it makes 219 00:12:29,120 --> 00:12:32,760 Speaker 1: it sound more natural. Now, this method has been in 220 00:12:32,920 --> 00:12:36,400 Speaker 1: use for years to just kind of tweak notes here 221 00:12:36,440 --> 00:12:38,160 Speaker 1: and there. It wasn't really used as kind of an 222 00:12:38,240 --> 00:12:43,000 Speaker 1: artistic thing until more recently. Yes, Actually, I I'll never 223 00:12:43,120 --> 00:12:47,280 Speaker 1: forget the first time I heard Shares Believe and I thought, 224 00:12:48,320 --> 00:12:51,480 Speaker 1: could anyone make a more annoying song than that? It 225 00:12:51,559 --> 00:12:54,480 Speaker 1: turns out yes, because I had not heard peanut butter 226 00:12:54,640 --> 00:13:00,280 Speaker 1: jelly time at that point. Peanut butter, yes. But uh, 227 00:13:00,800 --> 00:13:04,480 Speaker 1: but but in in the case with Share, she actually 228 00:13:04,559 --> 00:13:08,480 Speaker 1: took a feature of the auto tune software that was 229 00:13:08,960 --> 00:13:11,920 Speaker 1: never really intended to be used as as a performance 230 00:13:12,000 --> 00:13:15,040 Speaker 1: thing and turned it into a performance And you remember 231 00:13:15,080 --> 00:13:17,320 Speaker 1: when you were talking about how you adjust the speed 232 00:13:17,440 --> 00:13:21,959 Speaker 1: when the pitch changes, she essentially switched that to zero. Yes, 233 00:13:22,040 --> 00:13:24,160 Speaker 1: there's a there's a range that the software has between 234 00:13:24,280 --> 00:13:27,240 Speaker 1: zero and four hundred milliseconds, which is four tenths of 235 00:13:27,320 --> 00:13:30,760 Speaker 1: a second. Especially and uh, you have the option that 236 00:13:30,920 --> 00:13:33,960 Speaker 1: that's how long it takes for the pitch to shift 237 00:13:34,080 --> 00:13:36,439 Speaker 1: to what it thinks it's supposed to be right, And 238 00:13:36,840 --> 00:13:38,520 Speaker 1: and you may think, well, why would you want to 239 00:13:38,600 --> 00:13:41,520 Speaker 1: set that at four hundred? It makes it create a 240 00:13:41,559 --> 00:13:45,120 Speaker 1: more natural sound, because we you know, we don't tend 241 00:13:45,200 --> 00:13:48,800 Speaker 1: to sing notes perfect notes one right after the other, 242 00:13:49,360 --> 00:13:51,719 Speaker 1: especially jumping around a lot, unless you're talking about like 243 00:13:51,920 --> 00:13:55,440 Speaker 1: uh an Aria by Mozart and which case, I mean, 244 00:13:55,520 --> 00:13:58,120 Speaker 1: those are amazing, but most of us can't sing those. 245 00:13:58,960 --> 00:14:01,440 Speaker 1: Most of us, when we sing, we tend to slide 246 00:14:01,880 --> 00:14:03,760 Speaker 1: a little bit from one note to the next. And 247 00:14:03,840 --> 00:14:07,800 Speaker 1: if you take that that sliding out, it suddenly sounds 248 00:14:08,000 --> 00:14:11,960 Speaker 1: robotic and unnatural. But if your share and you're creating 249 00:14:12,000 --> 00:14:14,880 Speaker 1: this song. Believe that turns out to be the effect 250 00:14:14,960 --> 00:14:16,400 Speaker 1: you wanted to go for in the first place. So 251 00:14:16,480 --> 00:14:19,080 Speaker 1: you turned this thing that would normally be considered a 252 00:14:19,160 --> 00:14:22,560 Speaker 1: total a total mistake. You wouldn't want it to be 253 00:14:22,560 --> 00:14:24,760 Speaker 1: in there because you wouldn't want people to detect that 254 00:14:24,880 --> 00:14:28,760 Speaker 1: you had electronically altered your voice and turn it into 255 00:14:28,800 --> 00:14:31,880 Speaker 1: a performance. And it ended up working out very well 256 00:14:31,920 --> 00:14:33,640 Speaker 1: for her and got a lot of radio play and 257 00:14:34,320 --> 00:14:38,640 Speaker 1: slowly made me go crazy. Yeah, and of course then 258 00:14:38,680 --> 00:14:41,520 Speaker 1: you had I wondered what did that now? Yeah, that 259 00:14:41,640 --> 00:14:44,760 Speaker 1: was definitely a contributing factor. I can't lay all the 260 00:14:44,840 --> 00:14:48,040 Speaker 1: blame and shares feet. No, but it's uh, but that 261 00:14:48,160 --> 00:14:51,240 Speaker 1: explains why her voice sounds like it is snapping from 262 00:14:51,280 --> 00:14:55,160 Speaker 1: pitch to pitch without any kind of any kind of 263 00:14:55,200 --> 00:14:59,480 Speaker 1: glas Sando without any kind of you know, break glas 264 00:14:59,560 --> 00:15:05,320 Speaker 1: Sando music theory coming in here, so you know. On 265 00:15:05,480 --> 00:15:09,040 Speaker 1: on the other hand, there are artists who have essentially 266 00:15:09,080 --> 00:15:11,200 Speaker 1: made their living off of this. That would be you 267 00:15:11,280 --> 00:15:15,760 Speaker 1: know Pain Yes, who not only made several songs featuring 268 00:15:15,800 --> 00:15:19,880 Speaker 1: auto tune, but also the was the name behind the 269 00:15:20,000 --> 00:15:23,720 Speaker 1: iPhone feature that allows people to download the the app 270 00:15:24,840 --> 00:15:29,480 Speaker 1: The t paining app and and do live auto tuning 271 00:15:29,520 --> 00:15:33,400 Speaker 1: of their own voices, and he's unapologetic about about using 272 00:15:33,960 --> 00:15:37,720 Speaker 1: the software. Um, it's a performance, it's it's like any 273 00:15:37,800 --> 00:15:41,400 Speaker 1: other tool. Now. Now, some people even argue that anyone 274 00:15:41,600 --> 00:15:44,520 Speaker 1: using auto tune is cheating. Yeah, and that's that's what 275 00:15:44,640 --> 00:15:47,040 Speaker 1: some of the detractors say. But what he's doing with 276 00:15:47,160 --> 00:15:51,840 Speaker 1: it is on purpose, So it's you know, he's like, no, no, 277 00:15:52,000 --> 00:15:54,280 Speaker 1: this is my Yeah, I intended to do that. That 278 00:15:54,440 --> 00:15:56,360 Speaker 1: was the whole purpose of it, which I think that's 279 00:15:56,520 --> 00:15:59,000 Speaker 1: totally legitimate. I mean, it's just like taking a musical 280 00:15:59,040 --> 00:16:01,760 Speaker 1: instrument and playing in a way different than than the 281 00:16:01,800 --> 00:16:05,400 Speaker 1: way it was originally intended. That doesn't make it invalid. 282 00:16:05,960 --> 00:16:08,880 Speaker 1: It just means that you're innovative. Right, So the same 283 00:16:08,920 --> 00:16:11,359 Speaker 1: thing I just like share, I think was truly innovative 284 00:16:11,440 --> 00:16:14,640 Speaker 1: with that the way she she used auto tune. I may, 285 00:16:14,760 --> 00:16:16,640 Speaker 1: I may hate the song, but I can't argue with 286 00:16:16,680 --> 00:16:19,080 Speaker 1: the fact that it was innovative. I could have done without. 287 00:16:19,200 --> 00:16:22,640 Speaker 1: The seven fifty or so songs that I've heard since 288 00:16:22,720 --> 00:16:25,080 Speaker 1: then that are all using auto tune in that way 289 00:16:25,280 --> 00:16:28,080 Speaker 1: is no longer innovative. It's just a different way of 290 00:16:28,200 --> 00:16:30,800 Speaker 1: performing and they think of it as cheating. Now, granted, 291 00:16:30,840 --> 00:16:32,160 Speaker 1: lots of artists have been using this, a lot of 292 00:16:32,200 --> 00:16:34,720 Speaker 1: producers have been using as It's very possible that some 293 00:16:34,920 --> 00:16:36,880 Speaker 1: artists don't even know it was used on their their 294 00:16:36,920 --> 00:16:41,400 Speaker 1: particular records. Um, they probably do, because suddenly they aren't 295 00:16:41,520 --> 00:16:44,920 Speaker 1: having to do a lot of uh retakes and overdubs. 296 00:16:44,960 --> 00:16:48,120 Speaker 1: They're doing, you know, one or two takes per song 297 00:16:48,320 --> 00:16:51,440 Speaker 1: and heading for home. And that's down on the amount 298 00:16:51,440 --> 00:16:53,800 Speaker 1: of studio time that you need to spend, and you 299 00:16:53,840 --> 00:16:58,000 Speaker 1: know that's expensive. And hilder Brand points out that auto 300 00:16:58,080 --> 00:17:01,840 Speaker 1: tune does not make you a singer. Um. Auto tune 301 00:17:01,880 --> 00:17:04,520 Speaker 1: can help correct pitch, it can help you be you 302 00:17:04,560 --> 00:17:06,919 Speaker 1: can help you sing on pitch, and it will help 303 00:17:07,000 --> 00:17:09,600 Speaker 1: help you sing the right notes. But if your vocal 304 00:17:09,720 --> 00:17:14,240 Speaker 1: tone is not a good pleasing vocal tone, such as mine, 305 00:17:14,520 --> 00:17:17,640 Speaker 1: what my my singing tone is pretty terrible. Um, even 306 00:17:17,720 --> 00:17:20,359 Speaker 1: with auto tune, my singing is not gonna be great. 307 00:17:20,840 --> 00:17:24,960 Speaker 1: It's just gonna be the right notes, which granted, is 308 00:17:25,080 --> 00:17:28,160 Speaker 1: an improvement, but it's not gonna be something you're gonna think, Hey, 309 00:17:28,840 --> 00:17:30,359 Speaker 1: this is who I want to be listening to on 310 00:17:30,480 --> 00:17:33,359 Speaker 1: that five hour flight that I got coming up. Can 311 00:17:33,400 --> 00:17:36,840 Speaker 1: you can you auto tune karaoke? You could, you could 312 00:17:36,840 --> 00:17:39,520 Speaker 1: do and yeah, why not? You could have a microphone 313 00:17:39,560 --> 00:17:41,920 Speaker 1: built in with the auto tune and you could you 314 00:17:42,000 --> 00:17:46,280 Speaker 1: could have it automatically auto tune your your your vocals. 315 00:17:46,359 --> 00:17:50,280 Speaker 1: That's got cheating, I mean considered cheating. Yeah, well I 316 00:17:50,320 --> 00:17:52,840 Speaker 1: don't considering some of the people I've heard sing karaoke, 317 00:17:53,080 --> 00:17:57,080 Speaker 1: I be willing to entertain some cheating. And I know 318 00:17:57,200 --> 00:17:59,680 Speaker 1: the people who have heard me sing karaoke would entertain 319 00:17:59,760 --> 00:18:03,119 Speaker 1: some eating. Um. And we were actually thinking at one 320 00:18:03,160 --> 00:18:06,159 Speaker 1: point of having Liz auto tune some of some of 321 00:18:06,320 --> 00:18:09,639 Speaker 1: us bits of bits of what we were doing here. Oh, 322 00:18:10,400 --> 00:18:12,639 Speaker 1: you know, it's funny. We I'm surprised we haven't mentioned 323 00:18:13,680 --> 00:18:16,720 Speaker 1: other phenomena that have used auto tune, not just in 324 00:18:16,800 --> 00:18:20,040 Speaker 1: the music industry, you mean, like auto tune the news. Yeah, 325 00:18:20,160 --> 00:18:23,080 Speaker 1: there's this great YouTube series where these guys have taken 326 00:18:23,400 --> 00:18:26,680 Speaker 1: news clips from you know, any like Usually it's about 327 00:18:26,680 --> 00:18:29,480 Speaker 1: a week long period, but they take they take big 328 00:18:29,560 --> 00:18:32,080 Speaker 1: news clips and then they put it through auto tune 329 00:18:32,119 --> 00:18:35,399 Speaker 1: and turned them into songs and they cut the news 330 00:18:35,960 --> 00:18:39,200 Speaker 1: clips up so that it makes it more Yeah, yeah, 331 00:18:39,240 --> 00:18:41,880 Speaker 1: so that you get phrases and things, and sometimes they'll 332 00:18:41,920 --> 00:18:44,840 Speaker 1: have someone repeat something five or six times to make 333 00:18:44,880 --> 00:18:48,359 Speaker 1: it more like a song. They are absolutely hysterical videos. 334 00:18:48,440 --> 00:18:51,240 Speaker 1: There's also I've seen the auto tuning of the baby crying. 335 00:18:52,280 --> 00:18:54,000 Speaker 1: The baby's crying, but they put it through auto tune. 336 00:18:54,040 --> 00:18:56,080 Speaker 1: And here's the thing is that auto tune it is 337 00:18:56,119 --> 00:18:58,680 Speaker 1: a software suite that you can purchase. But um but 338 00:18:58,840 --> 00:19:02,760 Speaker 1: you can download a demo version and try it out 339 00:19:02,920 --> 00:19:05,320 Speaker 1: for a while on your computer. It's only gonna last 340 00:19:05,400 --> 00:19:07,840 Speaker 1: for a trial period, and then you are going to 341 00:19:07,920 --> 00:19:10,320 Speaker 1: be prompted to purchase it. And then of course there's 342 00:19:10,359 --> 00:19:12,479 Speaker 1: the app on the iPhone that you can get. Um, 343 00:19:12,640 --> 00:19:16,560 Speaker 1: so you can. That's that's considerably cheaper at yeah, yeah, 344 00:19:16,840 --> 00:19:18,960 Speaker 1: so but you can. You can play around with this 345 00:19:19,040 --> 00:19:22,960 Speaker 1: stuff and uh and and kind of see, you know, 346 00:19:23,160 --> 00:19:25,880 Speaker 1: how how it is that the big names are able 347 00:19:25,960 --> 00:19:30,159 Speaker 1: to get that really great produced sound on their tracks. 348 00:19:30,720 --> 00:19:33,720 Speaker 1: I would never have expected this to come from a 349 00:19:33,800 --> 00:19:38,359 Speaker 1: geologic technology. No. I I had real money on astrophysics, 350 00:19:39,080 --> 00:19:45,760 Speaker 1: but not geophysics. Maybe quantum physics. Maybe you know that's 351 00:19:45,840 --> 00:19:50,600 Speaker 1: that's funny because technically it's called pitch quantization. Yeah, I 352 00:19:50,800 --> 00:19:53,639 Speaker 1: I read through kind of now now, when when asked 353 00:19:53,760 --> 00:19:57,640 Speaker 1: exactly what sort of things go into his uh calculations, 354 00:19:57,720 --> 00:20:02,240 Speaker 1: Hildebrand said, and this is a direct quote out multiplications, additions, 355 00:20:02,280 --> 00:20:05,119 Speaker 1: and a few divisions, but designed by an extensive theoretical 356 00:20:05,200 --> 00:20:08,520 Speaker 1: foundation and digital signal processing, encompassing the physical principles of 357 00:20:08,560 --> 00:20:11,679 Speaker 1: sound production, physics of hearing, disciplines of modeling, filtering, linear 358 00:20:11,720 --> 00:20:15,200 Speaker 1: systems theory, estimation theory, numerical analysis, calculus, music theory, and 359 00:20:15,240 --> 00:20:20,400 Speaker 1: other disciplines pretty much including the pretty much, yeah, pretty much, 360 00:20:20,600 --> 00:20:23,119 Speaker 1: it's right there, it's right there. Yeah. No, that was 361 00:20:23,160 --> 00:20:25,679 Speaker 1: a direct quote that wasn't a frequently asked questions section. 362 00:20:26,119 --> 00:20:28,119 Speaker 1: He he actually seems to be a sort of a 363 00:20:28,200 --> 00:20:31,399 Speaker 1: humorous kind of guy. He did, well, I mean you 364 00:20:31,520 --> 00:20:35,680 Speaker 1: have to after after and he specifically stated that he 365 00:20:35,840 --> 00:20:38,400 Speaker 1: had never intended anyone to use it in the way 366 00:20:38,480 --> 00:20:41,199 Speaker 1: that t Pain and Share have used it and numerous 367 00:20:41,240 --> 00:20:43,680 Speaker 1: other people at this point, however, it was always meant 368 00:20:43,720 --> 00:20:46,159 Speaker 1: to be kind of a behind the scenes, you no 369 00:20:46,640 --> 00:20:52,199 Speaker 1: way of just just tweaking a track, rather than an outright, uh, 370 00:20:52,480 --> 00:20:54,000 Speaker 1: you know, the cat is out of the bag kind 371 00:20:54,000 --> 00:20:57,600 Speaker 1: of thing. I do think. Uh. This this has led 372 00:20:57,680 --> 00:21:00,040 Speaker 1: to the rise of music that is maybe just a 373 00:21:00,080 --> 00:21:03,480 Speaker 1: little bit too perfect for some people. So speaking of 374 00:21:03,760 --> 00:21:06,960 Speaker 1: the people who are remember how we were saying some 375 00:21:07,080 --> 00:21:10,040 Speaker 1: people really like low fi, some people really like hi fi. Right, 376 00:21:10,840 --> 00:21:14,040 Speaker 1: I've had people say that song is just too perfect 377 00:21:14,080 --> 00:21:16,240 Speaker 1: for me. Well, they could always listen to me sing 378 00:21:16,320 --> 00:21:22,480 Speaker 1: and they'll be cured of that right away. Amen. Um, so, 379 00:21:22,720 --> 00:21:26,800 Speaker 1: do you have anything else to add for our discussion 380 00:21:26,840 --> 00:21:30,399 Speaker 1: on auto tuning? And not really? Um, it's just kind 381 00:21:30,440 --> 00:21:32,600 Speaker 1: of uh, it's kind of funny. It's pretty much baked 382 00:21:32,640 --> 00:21:35,359 Speaker 1: into most studios at this point that that they have 383 00:21:35,480 --> 00:21:39,680 Speaker 1: it there, but um, you know, it's it's pretty ubiquitous 384 00:21:39,720 --> 00:21:43,880 Speaker 1: at this point, right. So, Um, here's where I'm gonna 385 00:21:44,280 --> 00:21:47,359 Speaker 1: throw it out there, and Liz, I'm gonna apologize to 386 00:21:47,359 --> 00:21:50,240 Speaker 1: you because you're gonna have to hear this unfiltered. In fact, 387 00:21:50,280 --> 00:21:52,520 Speaker 1: if you want to play it unfiltered once and auto 388 00:21:52,600 --> 00:21:55,840 Speaker 1: tuned once just to let people know how horribly I sing, 389 00:21:56,680 --> 00:21:59,120 Speaker 1: go for it, all right, guys. This song, by the way, 390 00:21:59,200 --> 00:22:01,640 Speaker 1: has been in the public domain for about five years, 391 00:22:01,680 --> 00:22:03,359 Speaker 1: so I don't want to hear anything from you. Guys. 392 00:22:03,880 --> 00:22:07,560 Speaker 1: You know you should have warned me. I would you 393 00:22:07,640 --> 00:22:12,560 Speaker 1: like to step out of the room. Um, alas, my love, 394 00:22:12,920 --> 00:22:19,439 Speaker 1: you do me wrong to cast me off discourteously. Alas, 395 00:22:19,880 --> 00:22:25,840 Speaker 1: my love, you do me wrong to cast me off discourteously. 396 00:22:26,560 --> 00:22:29,400 Speaker 1: There we go. That's all I'm gonna do. I don't 397 00:22:29,440 --> 00:22:31,960 Speaker 1: want to hit you too hard. That's bad enough right there. 398 00:22:32,520 --> 00:22:37,840 Speaker 1: I could have done no never mind best copyright. So yeah, 399 00:22:38,160 --> 00:22:40,359 Speaker 1: that was written, by the way, by Henry the Eighth, 400 00:22:40,520 --> 00:22:43,200 Speaker 1: by the grace of God, King of England and France, 401 00:22:43,400 --> 00:22:48,960 Speaker 1: Lord defender of the Faith and Lord of all Ireland. Um. Deceased, 402 00:22:49,359 --> 00:22:54,800 Speaker 1: Yes for quite some time. So anyway, hopefully it's better 403 00:22:54,880 --> 00:22:57,159 Speaker 1: than singing I'm Henry the Eighth. I am right. Hopefully 404 00:22:57,240 --> 00:22:59,440 Speaker 1: Liz will be able to uh to auto tune that, 405 00:22:59,520 --> 00:23:02,639 Speaker 1: and if not, hopefully she'll be able to cut that out. Alright, 406 00:23:02,720 --> 00:23:04,880 Speaker 1: So that wraps this up on auto tune. I hope 407 00:23:04,920 --> 00:23:09,680 Speaker 1: that answers your question, Jane. Uh. And now that leads 408 00:23:09,720 --> 00:23:16,640 Speaker 1: us to our second round of listener mail. Let's listen 409 00:23:16,800 --> 00:23:19,480 Speaker 1: mail comes from Nathan, and Nathan says, Hi, guys, I 410 00:23:19,640 --> 00:23:22,399 Speaker 1: was just wondering if you or anyone at your organization 411 00:23:22,560 --> 00:23:25,160 Speaker 1: listens back to your podcast and can hear what sounds 412 00:23:25,200 --> 00:23:27,240 Speaker 1: to me like an air conditioning hum in the background. 413 00:23:27,520 --> 00:23:29,720 Speaker 1: Would it be possible to edit that out? Look forward 414 00:23:29,760 --> 00:23:33,160 Speaker 1: to hearing back from you. Cheers Nathan, Nathan, that could 415 00:23:33,280 --> 00:23:35,480 Speaker 1: be one of many things that could be a fan. 416 00:23:36,160 --> 00:23:37,920 Speaker 1: It might be the fan, and might it might even 417 00:23:37,960 --> 00:23:40,800 Speaker 1: be the fan of my laptop, because you know, you know, 418 00:23:40,960 --> 00:23:43,240 Speaker 1: I need that so that my computer does not overheat 419 00:23:43,320 --> 00:23:45,560 Speaker 1: and shut down. And there's a refrigerator in the hallway. 420 00:23:45,720 --> 00:23:49,280 Speaker 1: There's yeah, there is an air conditioning system. And here's 421 00:23:49,320 --> 00:23:52,800 Speaker 1: the thing. We're dying in here. It is so hot 422 00:23:52,880 --> 00:23:55,760 Speaker 1: in here. Please don't take our air conditioning away. And 423 00:23:55,920 --> 00:23:57,840 Speaker 1: if I asked Liz to try and edit that out, 424 00:23:58,000 --> 00:24:01,440 Speaker 1: I think that would drive her crazy. So unfortunately, I 425 00:24:01,520 --> 00:24:03,800 Speaker 1: think we're kind of stuck with what we have until 426 00:24:03,880 --> 00:24:06,560 Speaker 1: but you know, we're we're renovating our our studio space. 427 00:24:06,680 --> 00:24:09,280 Speaker 1: Who knows what's gonna sound like when we're done. You know, 428 00:24:09,320 --> 00:24:12,520 Speaker 1: it only homes because it doesn't know the words. Very good, Chris, 429 00:24:12,800 --> 00:24:15,640 Speaker 1: That is exactly right. So if you have any other questions, 430 00:24:15,720 --> 00:24:18,720 Speaker 1: comments you'd like to criticize Chris for his joke, you 431 00:24:18,800 --> 00:24:21,760 Speaker 1: can write us tech stuff at how stuff works dot com. 432 00:24:22,720 --> 00:24:25,080 Speaker 1: Check out our blogs blogs dot how Stuff works dot com. 433 00:24:25,200 --> 00:24:27,520 Speaker 1: Check out the website itself, how stuff works dot com, 434 00:24:27,600 --> 00:24:30,119 Speaker 1: because it's awesome. It is, it's so yeah, it's a 435 00:24:30,160 --> 00:24:33,200 Speaker 1: great website, it's great resource. Um. Remember, we are no 436 00:24:33,359 --> 00:24:36,480 Speaker 1: longer doing tech stuff live while we are renovating our 437 00:24:36,560 --> 00:24:39,879 Speaker 1: studio space. So that's gonna last for probably about six weeks, 438 00:24:40,000 --> 00:24:42,359 Speaker 1: and then we're gonna think about what we can do 439 00:24:42,560 --> 00:24:45,239 Speaker 1: with that video series when we get back, because we're 440 00:24:45,240 --> 00:24:48,680 Speaker 1: gonna have a little bit more flexibility than we did before. 441 00:24:48,760 --> 00:24:50,560 Speaker 1: So I feeling of you have any cool ideas of 442 00:24:50,600 --> 00:24:52,280 Speaker 1: what you would like to see in a video series 443 00:24:52,320 --> 00:24:55,040 Speaker 1: from tech stuff. Um, Like, for instance, you would say, 444 00:24:55,359 --> 00:24:57,399 Speaker 1: I would love for the video series of tech stuff 445 00:24:57,520 --> 00:24:59,200 Speaker 1: to have the stuff you should know guys in it. 446 00:24:59,680 --> 00:25:02,040 Speaker 1: Right a tech stuff at how stuff works dot com 447 00:25:02,240 --> 00:25:04,480 Speaker 1: and Chris and I will talk to you again really soon. 448 00:25:07,240 --> 00:25:09,919 Speaker 1: For moral thiss and thousands of other topics, visit how 449 00:25:09,960 --> 00:25:12,359 Speaker 1: stuff works dot com and be sure to check out 450 00:25:12,400 --> 00:25:14,560 Speaker 1: the new tech stuff blog now on the how Stuff 451 00:25:14,560 --> 00:25:22,040 Speaker 1: Works homepage, brought to you by the reinvented two thousand 452 00:25:22,119 --> 00:25:24,119 Speaker 1: twelve camera. It's ready, are you