1 00:00:04,160 --> 00:00:06,200 Speaker 1: Hey, and welcome to the short stuff. I'm Josh, and 2 00:00:06,280 --> 00:00:08,639 Speaker 1: there's Chuck, and Jerry's here too, and so's Dave and 3 00:00:08,720 --> 00:00:12,360 Speaker 1: Spirit and we're coming at you from the future of 4 00:00:12,520 --> 00:00:13,000 Speaker 1: right now. 5 00:00:14,120 --> 00:00:18,480 Speaker 2: This is one of those where it's so interesting, so cool, 6 00:00:18,920 --> 00:00:21,920 Speaker 2: so mind blowing and so promising, and then you get 7 00:00:21,920 --> 00:00:27,400 Speaker 2: to the very end and then you're like, oh. 8 00:00:25,960 --> 00:00:27,720 Speaker 1: To me, that just meant just give it a little 9 00:00:27,760 --> 00:00:28,280 Speaker 1: more time. 10 00:00:28,480 --> 00:00:30,080 Speaker 2: No, And in a lot of times that is the case, 11 00:00:30,080 --> 00:00:31,880 Speaker 2: and probably will be in this case. But it was 12 00:00:31,920 --> 00:00:35,000 Speaker 2: such a oh. And you'll see what in about you know, 13 00:00:35,080 --> 00:00:36,520 Speaker 2: twelish minutes what we're talking about. 14 00:00:36,840 --> 00:00:39,720 Speaker 1: So essentially, what we're talking about first is data. We've 15 00:00:39,720 --> 00:00:42,479 Speaker 1: got a lot of data. Like anytime somebody says something, 16 00:00:42,720 --> 00:00:45,360 Speaker 1: thinks something writes something down, somebody comes up with a 17 00:00:45,360 --> 00:00:48,760 Speaker 1: new recipe or a new patent or whatever, that gets encoded. 18 00:00:48,800 --> 00:00:51,520 Speaker 1: It's data that gets saved. We don't really throw stuff 19 00:00:51,560 --> 00:00:55,520 Speaker 1: away anymore. And so we're kind of a wash in data. 20 00:00:56,080 --> 00:00:57,720 Speaker 1: And if you want to take that data, you want 21 00:00:57,720 --> 00:00:59,480 Speaker 1: to save it, you want to preserve it. Let's say, 22 00:00:59,480 --> 00:01:04,080 Speaker 1: it's really like you're the Library of Congress. Sure get this, man, 23 00:01:04,120 --> 00:01:06,240 Speaker 1: I did not realize this what you do is you 24 00:01:06,280 --> 00:01:09,160 Speaker 1: take that data and you transfer onto the same kind 25 00:01:09,160 --> 00:01:14,240 Speaker 1: of magnetic reels that those old room sized computer mainframes 26 00:01:14,360 --> 00:01:17,720 Speaker 1: used to read and write data. Yeah, you put it 27 00:01:17,760 --> 00:01:21,319 Speaker 1: on tape, Yeah exactly. Well I didn't realize that, but 28 00:01:21,880 --> 00:01:27,080 Speaker 1: it's just the proven go to means of long term 29 00:01:27,120 --> 00:01:30,240 Speaker 1: it's called archival storage of the kind of data that 30 00:01:30,319 --> 00:01:33,960 Speaker 1: you don't really need to access anytime soon. It's called 31 00:01:34,000 --> 00:01:38,080 Speaker 1: low touch data. You're just putting it literally in cold storage. 32 00:01:38,720 --> 00:01:40,959 Speaker 2: Yeah, I mean, it's been around for a long time, 33 00:01:41,600 --> 00:01:46,679 Speaker 2: very dependable, very durable, very reliable. It doesn't cost a 34 00:01:46,680 --> 00:01:48,960 Speaker 2: lot of money. It can hold a ton of data. 35 00:01:49,680 --> 00:01:53,480 Speaker 2: One tape can hold between one million and fifteen million 36 00:01:53,520 --> 00:01:58,400 Speaker 2: gigabytes or one to fifteen petabytes. That's a lot of stuff. 37 00:01:58,840 --> 00:01:59,120 Speaker 1: Really. 38 00:02:00,000 --> 00:02:03,280 Speaker 2: The problem is, and you know it's all relative, but 39 00:02:04,760 --> 00:02:08,040 Speaker 2: they're kind of big, but not big big. They're three 40 00:02:08,040 --> 00:02:10,160 Speaker 2: inches by three inches and you're like, Chuck, that's not 41 00:02:10,240 --> 00:02:12,640 Speaker 2: very big at all, But that is big when you 42 00:02:12,720 --> 00:02:16,440 Speaker 2: talk about you know, potentially billions of these things and 43 00:02:16,480 --> 00:02:19,680 Speaker 2: having to store them in a place that is, like 44 00:02:19,720 --> 00:02:23,040 Speaker 2: you said, cold storage. So it's the cost of building 45 00:02:23,080 --> 00:02:27,040 Speaker 2: these cold storage buildings that is the issue. When it 46 00:02:27,040 --> 00:02:28,840 Speaker 2: comes to this three by three inch thing. 47 00:02:29,200 --> 00:02:31,520 Speaker 1: That and then also you know they've been around for 48 00:02:31,600 --> 00:02:34,200 Speaker 1: three quarters of a century, so we know they last 49 00:02:34,240 --> 00:02:35,960 Speaker 1: that long if you keep them in cold storage, but 50 00:02:36,000 --> 00:02:38,880 Speaker 1: we don't know exactly how long they will last, so 51 00:02:39,200 --> 00:02:43,560 Speaker 1: there's also a question of that. So that combined with 52 00:02:43,680 --> 00:02:47,800 Speaker 1: so cost questions about how long it will last, and 53 00:02:47,840 --> 00:02:52,280 Speaker 1: then also just the enormous amounts of information we're adding 54 00:02:52,520 --> 00:02:56,239 Speaker 1: every year are making people look for other ways to 55 00:02:56,720 --> 00:03:00,600 Speaker 1: encapsulate data, to encode data in ways that are cheaper, 56 00:03:00,639 --> 00:03:03,959 Speaker 1: that are smaller, that are require less money to keep cold. 57 00:03:04,520 --> 00:03:07,399 Speaker 1: And what they've come up with, chuck. For anybody who 58 00:03:07,480 --> 00:03:10,080 Speaker 1: has looked at the title of this episode, they won't 59 00:03:10,080 --> 00:03:13,160 Speaker 1: be very surprised. But DNA, that's right. 60 00:03:13,639 --> 00:03:15,080 Speaker 2: I know it's early, but we got to take a 61 00:03:15,080 --> 00:03:15,600 Speaker 2: break right. 62 00:03:15,520 --> 00:03:17,799 Speaker 1: There, right agreed, all right, we'll be right back. 63 00:03:38,800 --> 00:03:41,280 Speaker 2: All right. So you dropped a pretty big truth bomb 64 00:03:41,360 --> 00:03:45,280 Speaker 2: on everyone. I'm sure there are people that for sixty seconds, 65 00:03:45,320 --> 00:03:50,280 Speaker 2: where like, what storing data on DNA? Dude, that's in 66 00:03:50,360 --> 00:03:53,480 Speaker 2: my body? Like, what are you talking about putting data 67 00:03:53,480 --> 00:03:54,120 Speaker 2: in my body? 68 00:03:54,360 --> 00:03:55,240 Speaker 1: You got that straight? 69 00:03:56,120 --> 00:03:58,920 Speaker 2: You don't have that straight. But here's here's a pretty 70 00:03:58,920 --> 00:04:01,160 Speaker 2: good as far as how much this stuff can hold. 71 00:04:01,640 --> 00:04:05,280 Speaker 2: This is pretty staggering stuff. And this is from a 72 00:04:05,320 --> 00:04:08,720 Speaker 2: couple of dudes from the Los Alamos National Lab, and 73 00:04:09,040 --> 00:04:12,720 Speaker 2: I think you got it from Scientific American. Here's how 74 00:04:12,800 --> 00:04:18,280 Speaker 2: much DNA can hold. Seventy four million million bytes of information, 75 00:04:18,320 --> 00:04:20,280 Speaker 2: which is basically the Library of Congress. 76 00:04:20,400 --> 00:04:20,960 Speaker 1: That's a lot. 77 00:04:21,200 --> 00:04:24,040 Speaker 2: That's a lot. You can put that, if you were 78 00:04:24,040 --> 00:04:28,160 Speaker 2: putting it on DNA, into the size of something as 79 00:04:28,160 --> 00:04:31,800 Speaker 2: big as a poppy seed, six thousand times over. Right. 80 00:04:33,120 --> 00:04:35,360 Speaker 2: Said another way, if you split that seed in half, 81 00:04:35,920 --> 00:04:39,200 Speaker 2: you could store all of the data on Facebook. 82 00:04:39,920 --> 00:04:44,680 Speaker 1: Yeah, and then by twenty twenty five, the size of 83 00:04:44,760 --> 00:04:49,160 Speaker 1: the data that humanity's generated, it will reach an estimated 84 00:04:49,200 --> 00:04:52,760 Speaker 1: thirty three zeta bytes, so three point three followed by 85 00:04:52,800 --> 00:04:56,960 Speaker 1: twenty two zeros of bytes of information, a lot of bytes. 86 00:04:57,760 --> 00:05:01,400 Speaker 1: If you can transcribe that all to DNA, you could 87 00:05:01,440 --> 00:05:04,400 Speaker 1: fit the whole thing into a ping pong ball. Yeah, 88 00:05:04,560 --> 00:05:09,839 Speaker 1: not a three by three plastic cartridge, multiple times over. 89 00:05:10,160 --> 00:05:12,720 Speaker 1: A single ping pong ball could hold all of the 90 00:05:12,760 --> 00:05:15,880 Speaker 1: world's data. And you can make multiple ping pong balls 91 00:05:15,880 --> 00:05:16,880 Speaker 1: as backups too. 92 00:05:17,160 --> 00:05:19,359 Speaker 2: Yeah, and you don't need to. And it's pretty easy 93 00:05:19,360 --> 00:05:22,480 Speaker 2: to duplicate them, apparently, and you don't need to keep 94 00:05:22,520 --> 00:05:24,600 Speaker 2: them in the fridge, even though you could put it 95 00:05:24,640 --> 00:05:28,400 Speaker 2: in an egg carton sure and be set. You don't 96 00:05:28,440 --> 00:05:30,520 Speaker 2: even have to. It's going to last a long time 97 00:05:31,600 --> 00:05:33,919 Speaker 2: not being in cold storage, and probably even longer in 98 00:05:33,960 --> 00:05:34,680 Speaker 2: cold storage. 99 00:05:34,760 --> 00:05:37,039 Speaker 1: You could give a ping pong ball to every living 100 00:05:37,080 --> 00:05:40,520 Speaker 1: human to keep in their fridge and like it would 101 00:05:40,600 --> 00:05:43,159 Speaker 1: have no problem whatsoever. Be like here, you keep this 102 00:05:43,240 --> 00:05:46,040 Speaker 1: cold for one hundred and fifty years, and only. 103 00:05:45,839 --> 00:05:48,640 Speaker 2: Half of them would eat that ping pong ball thinking 104 00:05:48,680 --> 00:05:49,279 Speaker 2: it was an egg. 105 00:05:49,640 --> 00:05:52,080 Speaker 1: Yeah. Yeah, so you'd still be left with all of 106 00:05:52,120 --> 00:05:53,240 Speaker 1: those backups. 107 00:05:53,800 --> 00:05:57,359 Speaker 2: Here's where it gets super interesting though, because you know, 108 00:05:57,400 --> 00:05:59,560 Speaker 2: as most people listening probably are, Like I said, as 109 00:05:59,600 --> 00:06:01,680 Speaker 2: I was read this, I was like, Okay, that's a 110 00:06:01,720 --> 00:06:04,559 Speaker 2: cool idea, but like, how in the world does this work? 111 00:06:05,120 --> 00:06:09,080 Speaker 2: And it turns out that it's not that mind blowing 112 00:06:09,080 --> 00:06:11,000 Speaker 2: your difficult I'm not saying I could go out and 113 00:06:11,040 --> 00:06:13,359 Speaker 2: do it, but it makes a lot of sense to 114 00:06:13,360 --> 00:06:17,359 Speaker 2: wrap your head around. Because DNA, as we all know, 115 00:06:18,040 --> 00:06:26,280 Speaker 2: is composed of four nucleotides, or at least combinations of guanine, thymine, addenine, 116 00:06:26,320 --> 00:06:34,599 Speaker 2: and cytosine. Just remember GTAC and attica. Yeah, ooh, ironically, 117 00:06:35,480 --> 00:06:39,000 Speaker 2: all this digital data though is included. That's out there 118 00:06:39,040 --> 00:06:41,680 Speaker 2: in the world and as everyone knows, and ones and zeros. 119 00:06:42,360 --> 00:06:44,880 Speaker 2: So it's it's you know, it sounds like you know, 120 00:06:44,920 --> 00:06:47,000 Speaker 2: and it can be any combination of ways. But when 121 00:06:47,000 --> 00:06:48,719 Speaker 2: you really break it down, it's really you can either 122 00:06:48,760 --> 00:06:51,560 Speaker 2: just have zero zero, zero, one, one zero or one 123 00:06:51,640 --> 00:06:55,360 Speaker 2: one as far as those combinations go. And that's four things. 124 00:06:55,640 --> 00:06:58,640 Speaker 2: And there are those four nucleotides. So if you just 125 00:06:58,760 --> 00:07:02,240 Speaker 2: like say, hey, each one of these nucleotides is going 126 00:07:02,279 --> 00:07:05,080 Speaker 2: to be assigned to different number, then that's all you need. 127 00:07:05,320 --> 00:07:06,400 Speaker 2: There's the key to your map. 128 00:07:06,800 --> 00:07:12,000 Speaker 1: Yeah, so say adenocene stands for zero zero, and guanine 129 00:07:12,000 --> 00:07:15,200 Speaker 1: stands for one to one, and so forth, each one 130 00:07:15,240 --> 00:07:18,160 Speaker 1: stands for one of those pairs of possible combinations. Then 131 00:07:18,200 --> 00:07:21,800 Speaker 1: you can take any string of binary data zeros and 132 00:07:21,840 --> 00:07:26,520 Speaker 1: ones and turn it into genetic code based on those nucleotides. 133 00:07:26,560 --> 00:07:29,360 Speaker 1: So like you would just have you go from a 134 00:07:29,360 --> 00:07:31,920 Speaker 1: string of ones and zeros to a string of ATG's 135 00:07:32,000 --> 00:07:35,360 Speaker 1: and c's. That's it. The thing is is you're you're 136 00:07:35,360 --> 00:07:40,480 Speaker 1: not turning ones and zeros into letters. You're actually transcribing 137 00:07:41,000 --> 00:07:45,520 Speaker 1: the ones and zeros from binary code into physical genetic material. 138 00:07:45,720 --> 00:07:49,840 Speaker 1: You're actually putting a base of at Adenocene right there. 139 00:07:49,960 --> 00:07:53,520 Speaker 1: You're putting a base of thiamine next to it, like, 140 00:07:53,960 --> 00:07:56,720 Speaker 1: depending on how the code reads with the ones and 141 00:07:56,720 --> 00:07:59,880 Speaker 1: the zeros and what order they're in. You're actually physically 142 00:08:00,120 --> 00:08:04,760 Speaker 1: creating genetic material DNA. But rather than encoding the information 143 00:08:05,000 --> 00:08:09,440 Speaker 1: to building a living thing, you're encoding the information to 144 00:08:10,680 --> 00:08:13,880 Speaker 1: the entire catalog of stuff you should know. And honestly, 145 00:08:14,240 --> 00:08:18,800 Speaker 1: isn't that the first thing we should preserve in DNA? Sure? Good? 146 00:08:19,160 --> 00:08:21,520 Speaker 2: After the movies of Gene Wilder. 147 00:08:22,800 --> 00:08:24,920 Speaker 1: How about at the same time as the movies of 148 00:08:24,960 --> 00:08:26,920 Speaker 1: Gene Wilder, can we just agree to that? 149 00:08:26,960 --> 00:08:27,680 Speaker 2: How dare you? 150 00:08:28,400 --> 00:08:33,200 Speaker 1: Hey? I think highly of us and Gene Wilder. Uh. 151 00:08:33,320 --> 00:08:35,120 Speaker 2: I don't know why he's been on my mind lately, 152 00:08:35,160 --> 00:08:35,760 Speaker 2: but he has been. 153 00:08:36,160 --> 00:08:38,240 Speaker 1: He's been shaking it for you in your head. 154 00:08:38,679 --> 00:08:41,160 Speaker 2: He's been shaking it for me. So this all sounds great. 155 00:08:41,240 --> 00:08:43,880 Speaker 2: And like I mentioned at the very beginning, this is 156 00:08:43,920 --> 00:08:45,920 Speaker 2: one of those things where like, holy cow, this is 157 00:08:45,960 --> 00:08:48,959 Speaker 2: the future, this is it, and then the L at 158 00:08:48,960 --> 00:08:52,680 Speaker 2: the end, and the L is that it's really expensive 159 00:08:53,640 --> 00:08:56,080 Speaker 2: to do this. Like, we can do this, we figured 160 00:08:56,080 --> 00:08:58,360 Speaker 2: out how to do this, it's possible, we have the 161 00:08:58,400 --> 00:09:02,440 Speaker 2: tech to do this, but that here's a tape name 162 00:09:02,679 --> 00:09:06,040 Speaker 2: lto DASH nine. It's a magnetic storage tape. You can 163 00:09:06,040 --> 00:09:07,640 Speaker 2: get it for eight bucks and you can get one 164 00:09:07,679 --> 00:09:11,240 Speaker 2: petabyte of storage. That would cost you about a trillion 165 00:09:11,320 --> 00:09:14,040 Speaker 2: dollars to do for DNA. 166 00:09:14,440 --> 00:09:16,400 Speaker 1: Yeah, there was a guy who was interviewed in Ours 167 00:09:16,440 --> 00:09:19,360 Speaker 1: Technica named Hugh and June Park. He's the CEO of 168 00:09:19,400 --> 00:09:22,640 Speaker 1: a data storage company called Catalog, and he even estimated said, 169 00:09:22,679 --> 00:09:24,680 Speaker 1: let's say it cost you three cents to print a 170 00:09:24,720 --> 00:09:28,959 Speaker 1: single nucleotide. Yes, that's cheap, but for each base pairrot 171 00:09:29,000 --> 00:09:30,760 Speaker 1: now you're up to six cents. And then now you're 172 00:09:30,800 --> 00:09:34,880 Speaker 1: translating gigabytes, you're entering millions of dollars. So if it 173 00:09:34,920 --> 00:09:39,440 Speaker 1: cost millions of dollars to translate a gigabyte, it cost 174 00:09:39,559 --> 00:09:42,720 Speaker 1: trillions of dollars to do a petabyte. And the other 175 00:09:42,760 --> 00:09:45,959 Speaker 1: problem of it, too, Chuck, is that it's really really slow, right. 176 00:09:46,600 --> 00:09:49,560 Speaker 2: It's super slow. So this is a clear case of 177 00:09:49,600 --> 00:09:51,200 Speaker 2: one of those things like you mentioned, which is like 178 00:09:51,320 --> 00:09:54,480 Speaker 2: just wait, because like with any technology, it's going to 179 00:09:54,520 --> 00:09:57,439 Speaker 2: get quicker, it's going to get cheaper. I don't know 180 00:09:57,480 --> 00:09:59,320 Speaker 2: if this is like one hundred years into the future, 181 00:09:59,360 --> 00:10:01,480 Speaker 2: but I don't think at this point the cost is 182 00:10:01,880 --> 00:10:05,480 Speaker 2: just so outrageous that there's no government is going to 183 00:10:05,559 --> 00:10:06,280 Speaker 2: fund something like this. 184 00:10:06,360 --> 00:10:09,600 Speaker 1: I mean, a trillion dollars for one petabyte of information 185 00:10:10,360 --> 00:10:13,480 Speaker 1: is not You're not going to sell that very very easily. 186 00:10:13,600 --> 00:10:16,319 Speaker 1: And then yeah, like I was saying, the speed, if 187 00:10:16,320 --> 00:10:21,360 Speaker 1: you're transferring information from one of those magnetic storage tapes, 188 00:10:21,679 --> 00:10:25,679 Speaker 1: you're transferring it about a gigabyte per second typically if 189 00:10:25,720 --> 00:10:29,120 Speaker 1: it takes even like a second to print a single nucleotide, 190 00:10:29,160 --> 00:10:32,120 Speaker 1: which is still very fast, but you're we're thinking on 191 00:10:32,240 --> 00:10:35,200 Speaker 1: human level fast. We need to think on like how 192 00:10:35,240 --> 00:10:39,680 Speaker 1: many ones and zeros are in the average gigabyte of code. 193 00:10:40,480 --> 00:10:44,439 Speaker 1: Now you're talking about decades to transfer a petabyte discs 194 00:10:44,520 --> 00:10:50,160 Speaker 1: worth of information using DNA technology. Yeah, so, yes, it's 195 00:10:50,400 --> 00:10:54,040 Speaker 1: very slow right now, it's very expensive right now, But 196 00:10:54,240 --> 00:10:56,400 Speaker 1: I don't think we're one hundred years off, Chuck, because 197 00:10:56,480 --> 00:10:59,719 Speaker 1: we're able to do this now relatively cheaply because the 198 00:11:00,280 --> 00:11:03,040 Speaker 1: Human Genome Project came along that was twenty years ago. 199 00:11:03,480 --> 00:11:05,600 Speaker 1: Think about how much, how long, how far we've come, 200 00:11:05,760 --> 00:11:08,280 Speaker 1: And this is like the hardest chunk the first twenty years. 201 00:11:08,640 --> 00:11:10,640 Speaker 1: I think it's just going to get faster and easier. 202 00:11:10,920 --> 00:11:12,480 Speaker 1: I don't think we're going to be waiting one hundred 203 00:11:12,520 --> 00:11:14,160 Speaker 1: years to see DNA data storage. 204 00:11:14,640 --> 00:11:16,280 Speaker 2: Does that mean that stuff you should Know is in 205 00:11:16,320 --> 00:11:19,760 Speaker 2: the hardest chunk when you're fifteen? 206 00:11:19,920 --> 00:11:25,040 Speaker 1: I think so. Yeah, it feels like it. Okay, I'm kidding. Well, 207 00:11:25,080 --> 00:11:29,760 Speaker 1: I'm teasing Chuck, right, Yeah, just teasing, which means, of course, 208 00:11:30,160 --> 00:11:33,840 Speaker 1: short stuff is out. 209 00:11:34,440 --> 00:11:37,320 Speaker 2: Stuff you Should Know is a production of iHeartRadio. For 210 00:11:37,400 --> 00:11:41,560 Speaker 2: more podcasts my Heart Radio, visit the iHeartRadio app, Apple Podcasts, 211 00:11:41,679 --> 00:11:41,719 Speaker 2: or 212 00:11:41,760 --> 00:11:49,040 Speaker 1: Wherever you listen to your favorite shows.