1 00:00:03,840 --> 00:00:06,720 Speaker 1: Welcome to Stuff to Blow your Mind from how Stuff 2 00:00:06,720 --> 00:00:13,400 Speaker 1: Works dot com. Hey you welcome to Stuff to Blow 3 00:00:13,440 --> 00:00:15,400 Speaker 1: your Mind. My name is Robert Lamb and my name 4 00:00:15,440 --> 00:00:18,880 Speaker 1: is Julie Douglas, and we are rounding up the Trilogy 5 00:00:18,880 --> 00:00:21,560 Speaker 1: of Slime. Here we have. We started off with an 6 00:00:21,560 --> 00:00:23,680 Speaker 1: episode tital Trilogy of Slime, where we talking about the 7 00:00:23,760 --> 00:00:26,240 Speaker 1: natures of the nature of slime and organisms and all 8 00:00:26,280 --> 00:00:28,960 Speaker 1: the important roles that it serves. Then we did a 9 00:00:28,960 --> 00:00:31,880 Speaker 1: little Valentine special about the sex life of slugs, which 10 00:00:31,920 --> 00:00:35,760 Speaker 1: is also very slimy but also a little stabby. And 11 00:00:35,800 --> 00:00:39,960 Speaker 1: then finally we are discussing the slime mold, which is uh, 12 00:00:40,720 --> 00:00:43,080 Speaker 1: taking it in a in a different direction, but a 13 00:00:43,120 --> 00:00:47,120 Speaker 1: really really deceptively mind blowing direction, because when you just 14 00:00:47,200 --> 00:00:50,320 Speaker 1: talk about the word mold itself is kind of boring. 15 00:00:50,440 --> 00:00:53,760 Speaker 1: Mold is something that grows somewhere that you don't think about, 16 00:00:53,800 --> 00:00:55,440 Speaker 1: you know, It's like it's it's that's the stuff that 17 00:00:55,440 --> 00:00:57,520 Speaker 1: grows in the tub, it grows in the corner, grows 18 00:00:57,560 --> 00:01:00,520 Speaker 1: under the house maybe and unless you think about it 19 00:01:00,560 --> 00:01:05,279 Speaker 1: the better. Yeah. Um, but slime mold is actually something 20 00:01:05,319 --> 00:01:09,399 Speaker 1: that is helping is to redefine intelligence and we'll talk 21 00:01:09,440 --> 00:01:12,600 Speaker 1: a bit more about that in a moment. Um. But 22 00:01:12,760 --> 00:01:15,600 Speaker 1: when we talk about slime mold and we say mold, 23 00:01:15,760 --> 00:01:18,920 Speaker 1: we actually are not talking about any sort of fungus here, right, 24 00:01:19,760 --> 00:01:23,199 Speaker 1: We're talking about mainly when we talk about slime old 25 00:01:23,240 --> 00:01:27,360 Speaker 1: is something called phi serum polycephalum, and that that name 26 00:01:27,400 --> 00:01:31,360 Speaker 1: actually means many headed slime mold. Slime is not a 27 00:01:31,600 --> 00:01:33,800 Speaker 1: slime mold is not a plant or an animal. It's 28 00:01:33,840 --> 00:01:38,080 Speaker 1: not a fungus, though it sometimes resembles one structurally. Yeah, 29 00:01:38,080 --> 00:01:42,600 Speaker 1: it's a single, single celled creature, brainless, brainless, No, no 30 00:01:42,680 --> 00:01:45,520 Speaker 1: brain and that's important here, no nervous system to speak of. 31 00:01:46,200 --> 00:01:50,280 Speaker 1: And yet it's intelligence. It's what fascinates us. Yeah, I 32 00:01:50,280 --> 00:01:53,520 Speaker 1: mean it ultimately makes us really think hard and deep 33 00:01:53,560 --> 00:01:56,520 Speaker 1: about what intelligence is and what it can be, especially 34 00:01:56,560 --> 00:01:59,080 Speaker 1: when we're trying to think about what what life could 35 00:01:59,080 --> 00:02:02,400 Speaker 1: be like elsewhere in the in the universe. Um. And 36 00:02:02,440 --> 00:02:05,960 Speaker 1: when you say in the universe, you should consider that, Uh, 37 00:02:06,240 --> 00:02:09,800 Speaker 1: these guys go back in evolutionary history history about a 38 00:02:09,960 --> 00:02:12,840 Speaker 1: billion years. And according to Dr Baldolph, who is a 39 00:02:12,880 --> 00:02:16,280 Speaker 1: Swedish biologist studying the DNA of slime mold species, she 40 00:02:16,400 --> 00:02:18,840 Speaker 1: says that they might be tightly linked to the development 41 00:02:18,880 --> 00:02:21,760 Speaker 1: of soil on land, which is very cool to think 42 00:02:21,800 --> 00:02:24,040 Speaker 1: about when you think about slime mold. Yeah, it's kind 43 00:02:24,040 --> 00:02:26,360 Speaker 1: of triggy to to to really look at our history 44 00:02:26,400 --> 00:02:28,720 Speaker 1: of fly mold because it's not something that really lends 45 00:02:28,720 --> 00:02:31,800 Speaker 1: itself well to the fossil record. Yeah, exactly. We do 46 00:02:31,840 --> 00:02:34,400 Speaker 1: know that there are nine hundred known species of slime mold, 47 00:02:34,440 --> 00:02:37,560 Speaker 1: but they're really only about two that are studied in earnest. 48 00:02:38,080 --> 00:02:42,520 Speaker 1: Slime mold's live in moist terrestrial habitats like decaying wood 49 00:02:42,680 --> 00:02:47,200 Speaker 1: or fresh captung nice and once the mold has found food, 50 00:02:47,320 --> 00:02:50,800 Speaker 1: such as a piece of decaying vegetation or a micro organism, 51 00:02:50,960 --> 00:02:54,720 Speaker 1: it grows over it and it secretes digestive enzymes. So 52 00:02:54,880 --> 00:02:59,160 Speaker 1: something like polycephalum then construct an elaborate network of interconnections 53 00:02:59,200 --> 00:03:02,760 Speaker 1: between foods sources which allow it to shuttle nutrients around 54 00:03:03,360 --> 00:03:07,440 Speaker 1: and get the full form of the organism fully fed. Um. 55 00:03:07,600 --> 00:03:10,400 Speaker 1: Slime molds then devour many parts of bacteria, and then 56 00:03:10,440 --> 00:03:14,040 Speaker 1: this releases those nutrients for other organisms to grow on. 57 00:03:14,080 --> 00:03:16,280 Speaker 1: So it's a huge part of the ecosystem. So what 58 00:03:16,320 --> 00:03:19,160 Speaker 1: does it look like, Um, it does not really so 59 00:03:19,240 --> 00:03:22,440 Speaker 1: much look like slime per se like, it doesn't look 60 00:03:22,480 --> 00:03:25,440 Speaker 1: like Nickelodeon bucket of slime falling on someone's head. And 61 00:03:25,520 --> 00:03:28,360 Speaker 1: it has more of a yellowy consistency to it. It It 62 00:03:28,440 --> 00:03:33,000 Speaker 1: doesn't particularly look viscous. Yeah, a lot of people have 63 00:03:33,400 --> 00:03:37,600 Speaker 1: lined it to dog vomit. Um. That's a that's the 64 00:03:37,720 --> 00:03:40,640 Speaker 1: usual thing that people spot. UM. But it actually comes 65 00:03:40,640 --> 00:03:43,360 Speaker 1: in nearly every color of the rainbow except green because 66 00:03:43,400 --> 00:03:49,360 Speaker 1: it lacks chlorophyll um. Some resemble honeycomb lattice structures, others 67 00:03:49,560 --> 00:03:53,680 Speaker 1: kind of look like BlackBerry configurations. UM. And then of 68 00:03:53,720 --> 00:03:56,920 Speaker 1: course there's the dog vomit, which is the classic thing. UM. 69 00:03:56,960 --> 00:03:59,800 Speaker 1: Some remain microscopic to the eye, but others grow large, 70 00:03:59,800 --> 00:04:02,400 Speaker 1: and you can form boldest masses as long as ten 71 00:04:02,480 --> 00:04:05,640 Speaker 1: to thirteen feet long. So in the second we're gonna 72 00:04:05,920 --> 00:04:07,800 Speaker 1: we're gonna get into the idea of what happens when 73 00:04:07,840 --> 00:04:11,240 Speaker 1: you put slimold in a maze. But but imagine you 74 00:04:11,240 --> 00:04:14,560 Speaker 1: have a slime mold working its way down a corridor 75 00:04:14,920 --> 00:04:18,240 Speaker 1: and what happens when it encounters another slime mold coming 76 00:04:18,279 --> 00:04:21,800 Speaker 1: down the corridor from the opposite direction. You probably want 77 00:04:21,800 --> 00:04:23,720 Speaker 1: to do they do they fight each other? Do they 78 00:04:24,080 --> 00:04:27,280 Speaker 1: is there a war of slime mold that takes place here? Well, 79 00:04:27,360 --> 00:04:30,320 Speaker 1: if food is scarce is what's interesting is they do 80 00:04:30,440 --> 00:04:35,280 Speaker 1: essentially team up into it like a single communicating mass. Yeah, 81 00:04:35,360 --> 00:04:37,400 Speaker 1: it's really cool. Um. This is from a New York 82 00:04:37,400 --> 00:04:41,880 Speaker 1: Times article, Can answers to evolution be found in slime mold? Yeah? 83 00:04:41,880 --> 00:04:44,880 Speaker 1: The organisms do respond to starvation by rushing together by 84 00:04:44,920 --> 00:04:49,239 Speaker 1: the thousands into a single blob. And the blob stretches 85 00:04:49,279 --> 00:04:52,400 Speaker 1: out into a slug shaped mass about one millimeter long, 86 00:04:52,400 --> 00:04:55,560 Speaker 1: which is about one inch, and then it begins to 87 00:04:55,600 --> 00:04:59,039 Speaker 1: crawl along like a worm toward light. Wow, like like 88 00:04:59,080 --> 00:05:02,680 Speaker 1: a caravan of line. Really yep yep. And then once 89 00:05:02,720 --> 00:05:05,560 Speaker 1: it reaches the surface surface of the soil, the slug, 90 00:05:05,880 --> 00:05:09,240 Speaker 1: this the slug configuration undergoes another transformation. Some of the 91 00:05:09,279 --> 00:05:12,840 Speaker 1: cells turn into a stiff stock, while the others crawl 92 00:05:12,960 --> 00:05:16,039 Speaker 1: to the top inform a sticky ball of spores and 93 00:05:16,120 --> 00:05:18,160 Speaker 1: they stick to the foot of an animal and travel 94 00:05:18,200 --> 00:05:21,839 Speaker 1: to a hospitable place. So inside the slug. And this 95 00:05:21,960 --> 00:05:24,359 Speaker 1: again is according to the article, about one percent of 96 00:05:24,400 --> 00:05:28,080 Speaker 1: the miba's turn into police. This is really cool. They 97 00:05:28,120 --> 00:05:31,680 Speaker 1: crawl through the slug in search of infectious bacteria and 98 00:05:31,720 --> 00:05:35,720 Speaker 1: then they vanquish it. Really, they find this pathogen and 99 00:05:35,760 --> 00:05:39,040 Speaker 1: they devour it. And then these sentinels drop away from 100 00:05:39,080 --> 00:05:43,400 Speaker 1: this slug configuration of slime mold, taking the pathogen with it, 101 00:05:44,040 --> 00:05:46,239 Speaker 1: and then they die of the infection, while the slug 102 00:05:46,480 --> 00:05:51,200 Speaker 1: itself remains healthy, the colony of it remains healthy. So um, 103 00:05:51,240 --> 00:05:54,080 Speaker 1: this is so amazing to me. This is all going 104 00:05:54,120 --> 00:05:59,240 Speaker 1: on at this microscopic level. This these acts of altruism. Really. Yeah, 105 00:05:59,600 --> 00:06:01,200 Speaker 1: all right, we're gonna take a quick break and when 106 00:06:01,200 --> 00:06:03,160 Speaker 1: we come back, we will enter the maze with the 107 00:06:03,200 --> 00:06:06,719 Speaker 1: slime mold and discuss exactly how it finds its way out. 108 00:06:14,480 --> 00:06:17,960 Speaker 1: All right, we're back. So the maze. We we did 109 00:06:17,960 --> 00:06:20,560 Speaker 1: a whole episode on mazes, and we discussed what they 110 00:06:20,600 --> 00:06:23,480 Speaker 1: are and what they symbolize for us humans. Essentially, you're 111 00:06:23,520 --> 00:06:28,480 Speaker 1: talking about uh binding, confusing pathway corridors that end in 112 00:06:28,560 --> 00:06:33,480 Speaker 1: dead ends while other corridors take you ever closer to freedom. 113 00:06:33,480 --> 00:06:37,440 Speaker 1: So we often use these in science experiments. Put a 114 00:06:37,440 --> 00:06:39,520 Speaker 1: mouse inside of a maze. See what happens when it 115 00:06:39,560 --> 00:06:41,560 Speaker 1: gets stressed out? See if it can find its way out? 116 00:06:42,839 --> 00:06:45,400 Speaker 1: What happens when you put a slime mold into a 117 00:06:45,400 --> 00:06:48,359 Speaker 1: maze is really fascinating because now, for one thing, you 118 00:06:48,400 --> 00:06:50,920 Speaker 1: do have to sort of um. You have to create 119 00:06:50,920 --> 00:06:53,760 Speaker 1: a situation where the slime old quote unquote wants out, 120 00:06:53,920 --> 00:06:55,679 Speaker 1: the slime mold wants to find its way to food. 121 00:06:55,760 --> 00:06:59,120 Speaker 1: So that becomes the the idea here um for a 122 00:06:59,200 --> 00:07:00,840 Speaker 1: dead end. To be a true dead end, it needs 123 00:07:00,839 --> 00:07:03,279 Speaker 1: to not have something that the slime old can eat 124 00:07:03,279 --> 00:07:05,159 Speaker 1: at the end of it, whereas they dad end with 125 00:07:05,240 --> 00:07:06,919 Speaker 1: food at the end of it is essentially kind of 126 00:07:06,920 --> 00:07:09,680 Speaker 1: an exit. So they found that if you put a 127 00:07:09,760 --> 00:07:11,360 Speaker 1: Researchers have found it that if you put a slime 128 00:07:11,400 --> 00:07:16,400 Speaker 1: mold inside of this maze, it will start off by 129 00:07:16,520 --> 00:07:19,200 Speaker 1: mapping its environment out. It will send out these uh, 130 00:07:19,280 --> 00:07:22,680 Speaker 1: these tendrils, and they will follow every course in the 131 00:07:22,720 --> 00:07:25,200 Speaker 1: maze to its end. And if they find a true 132 00:07:25,240 --> 00:07:28,520 Speaker 1: dead end where everything just ends and there's no food there, 133 00:07:28,840 --> 00:07:31,440 Speaker 1: then it will retract, but it will leave a trail 134 00:07:31,760 --> 00:07:34,840 Speaker 1: of slime that kind of works as an external memory 135 00:07:34,960 --> 00:07:37,920 Speaker 1: of where it has been, and that is a that 136 00:07:38,040 --> 00:07:40,120 Speaker 1: is a hallway that it need not go down again 137 00:07:40,160 --> 00:07:42,800 Speaker 1: because there's no food down there, and then it will 138 00:07:42,840 --> 00:07:48,760 Speaker 1: concentrate its efforts on the pathways that do lead to food. Yeah, 139 00:07:48,760 --> 00:07:50,920 Speaker 1: it's really cool. As you say, it's like this externalized 140 00:07:50,960 --> 00:07:55,400 Speaker 1: spatial memory and um. And again no brain. Creature does 141 00:07:55,400 --> 00:07:57,480 Speaker 1: not have a brain, and it is not intelligent in 142 00:07:58,000 --> 00:08:00,120 Speaker 1: the larger sense of the word. But it is is 143 00:08:00,240 --> 00:08:03,320 Speaker 1: using a certain amount of matt making intelligence. It's using 144 00:08:03,360 --> 00:08:06,480 Speaker 1: that chemical scent to figure out where it's been and 145 00:08:06,480 --> 00:08:09,960 Speaker 1: then not expend the effort on searches that won't pay off. Right, 146 00:08:10,040 --> 00:08:11,920 Speaker 1: So it's saying, I've been down that hallway, there's no 147 00:08:12,120 --> 00:08:14,680 Speaker 1: no reason I need to redouble my efforts on this. 148 00:08:15,280 --> 00:08:20,080 Speaker 1: Another cool thing is that the five serum slime mold 149 00:08:20,600 --> 00:08:24,600 Speaker 1: sends these tendrils of protoplasum out search for food. And 150 00:08:24,640 --> 00:08:28,280 Speaker 1: it's but but it's not just hey, wholesale everybody find food. 151 00:08:29,280 --> 00:08:31,680 Speaker 1: What they do is they say, okay, this one over 152 00:08:31,720 --> 00:08:34,200 Speaker 1: here to the left has found some food. These guys 153 00:08:34,240 --> 00:08:36,880 Speaker 1: over here on the right have not. All right, everybody 154 00:08:36,960 --> 00:08:40,280 Speaker 1: reconfigure and now let's bolsh for our efforts to that 155 00:08:40,360 --> 00:08:43,440 Speaker 1: food to the left. So they reorganize themselves to then 156 00:08:43,559 --> 00:08:47,200 Speaker 1: sort of go in and effectively cover that food spectrum 157 00:08:47,240 --> 00:08:49,760 Speaker 1: that they did find, which is amazing. So not only 158 00:08:50,160 --> 00:08:52,320 Speaker 1: are they making sure that they're not going into areas 159 00:08:52,320 --> 00:08:55,280 Speaker 1: they've already been, but when they do find food, they're 160 00:08:55,320 --> 00:08:58,520 Speaker 1: able to to sort of say, all right, troops, here 161 00:08:58,559 --> 00:09:00,800 Speaker 1: we go, We're now going to some trade on this. 162 00:09:01,200 --> 00:09:04,360 Speaker 1: All right. All of this is really amazing when you 163 00:09:04,440 --> 00:09:08,640 Speaker 1: look at it in the context of engineering problems that 164 00:09:08,679 --> 00:09:13,000 Speaker 1: we humans try to solve every single day. Yeah, particularly 165 00:09:13,160 --> 00:09:16,120 Speaker 1: um it's it's interesting when you take the slime mold 166 00:09:16,160 --> 00:09:18,480 Speaker 1: and you put it over a major city, and then 167 00:09:18,520 --> 00:09:21,400 Speaker 1: you distribute the food in a way that resembles uh, 168 00:09:21,600 --> 00:09:24,640 Speaker 1: major population points, major points of interest, places that you 169 00:09:24,880 --> 00:09:28,520 Speaker 1: need to say, a public transportation system to reach. So 170 00:09:28,640 --> 00:09:31,040 Speaker 1: if it were a map of Atlanta, for instance, you 171 00:09:31,080 --> 00:09:34,320 Speaker 1: would have like central Atlanta, Midtown, you'd have the Bucket 172 00:09:34,360 --> 00:09:37,800 Speaker 1: area where we are, and and various other important places. 173 00:09:38,320 --> 00:09:40,920 Speaker 1: Um well, several of those in both places are probably 174 00:09:40,920 --> 00:09:44,240 Speaker 1: not gonna reach by public transportation down here as far 175 00:09:44,320 --> 00:09:45,880 Speaker 1: as the train goes. But that's a whole another story. 176 00:09:46,760 --> 00:09:48,880 Speaker 1: But you put the slime mold in there and you 177 00:09:48,960 --> 00:09:50,960 Speaker 1: let it figure out the best ways to get to 178 00:09:51,040 --> 00:09:54,800 Speaker 1: its food sources, and researchers have found that the paths 179 00:09:54,800 --> 00:09:58,720 Speaker 1: that the slime mold creates are comparable to the major 180 00:09:58,760 --> 00:10:01,959 Speaker 1: public transportation system in those cities. You know, we've seen 181 00:10:02,000 --> 00:10:04,040 Speaker 1: this again and again. It's not just Okay, there's just 182 00:10:04,120 --> 00:10:06,240 Speaker 1: one set of researchers doing this. But I think the 183 00:10:06,400 --> 00:10:10,760 Speaker 1: standout in this is the Tokyo railway system. Um, it's 184 00:10:10,840 --> 00:10:14,319 Speaker 1: a two excuse me. In two thousand and ten, mathematical 185 00:10:14,440 --> 00:10:19,559 Speaker 1: biologists toshi Yuki naga Aki and his colleagues observed how 186 00:10:19,720 --> 00:10:23,160 Speaker 1: this networking behavior could translate into efficient city planning. So 187 00:10:23,200 --> 00:10:25,480 Speaker 1: they drew a map of Japan. They put oat flakes 188 00:10:25,480 --> 00:10:28,720 Speaker 1: on the map to represent cities, and then they let 189 00:10:28,760 --> 00:10:32,000 Speaker 1: the five serum loose on the area that represented Tokyo, Okay. 190 00:10:32,080 --> 00:10:34,720 Speaker 1: So key to this is that they're obviously going to 191 00:10:34,760 --> 00:10:37,880 Speaker 1: be obstacles in city planning, like waterways that you can't 192 00:10:37,880 --> 00:10:39,480 Speaker 1: you have to make sure that you didn't try to 193 00:10:39,520 --> 00:10:42,640 Speaker 1: transverse long standing buildings and areas that you're just not 194 00:10:42,679 --> 00:10:46,160 Speaker 1: going to bulldoze to build your right. So what they 195 00:10:46,240 --> 00:10:49,080 Speaker 1: did is they took bright lights in these areas and 196 00:10:49,679 --> 00:10:52,280 Speaker 1: which slim olds will avoid they do not like, and 197 00:10:52,320 --> 00:10:55,000 Speaker 1: so those represented those areas that they knew that you 198 00:10:55,000 --> 00:10:57,920 Speaker 1: couldn't do any sort of public transportation around. And then 199 00:10:57,960 --> 00:11:00,360 Speaker 1: what bloomed in front of the researcher with the FI 200 00:11:00,440 --> 00:11:04,920 Speaker 1: serum network that produced interconnections just that were strikingly similar 201 00:11:04,960 --> 00:11:08,599 Speaker 1: to the layout of the Tokyo railway system and um 202 00:11:08,640 --> 00:11:12,679 Speaker 1: in the ways that they differed from the actual Tokyo 203 00:11:12,760 --> 00:11:17,160 Speaker 1: railway system. It turns out that their methods of reaching 204 00:11:17,840 --> 00:11:22,280 Speaker 1: uh net networked UM places was much more effective that 205 00:11:23,160 --> 00:11:28,080 Speaker 1: than what was already in place. So what we're saying 206 00:11:28,120 --> 00:11:32,320 Speaker 1: here is that slime molds are solving engineering problems. I mean, 207 00:11:32,360 --> 00:11:34,160 Speaker 1: this is amazing. This is stuff that we spend a 208 00:11:34,200 --> 00:11:36,520 Speaker 1: lot of time on. This is these are computer programs, 209 00:11:36,520 --> 00:11:39,360 Speaker 1: are modeling that's going on, and you just let a 210 00:11:39,400 --> 00:11:42,240 Speaker 1: sly old loose and they can help. It'll equal or 211 00:11:42,280 --> 00:11:46,800 Speaker 1: exceed human production on those of those same trade routes 212 00:11:47,360 --> 00:11:50,040 Speaker 1: are same public transportation routes. Because another one that I 213 00:11:50,120 --> 00:11:52,240 Speaker 1: ran across what was they were actually able to get 214 00:11:52,320 --> 00:11:57,079 Speaker 1: up of the serum to um to reproduce the silk 215 00:11:57,160 --> 00:12:00,520 Speaker 1: road in various other global trading routes. Put it on 216 00:12:00,559 --> 00:12:02,840 Speaker 1: a map of the Earth and you'll see, oh, it's well, 217 00:12:02,880 --> 00:12:04,760 Speaker 1: there's a silk road right there. It's thinking along the 218 00:12:04,800 --> 00:12:08,080 Speaker 1: same lines as uh as as as humans did when 219 00:12:08,120 --> 00:12:09,400 Speaker 1: they were trying figure out how to get from a 220 00:12:09,440 --> 00:12:12,320 Speaker 1: point A to point B in the most effective manner possible, right, 221 00:12:12,320 --> 00:12:14,800 Speaker 1: And when they took that globe to they configured it 222 00:12:14,880 --> 00:12:17,280 Speaker 1: so that again there were certain places that that mold 223 00:12:17,320 --> 00:12:21,719 Speaker 1: couldn't try to transfer because of the configuration of the 224 00:12:21,880 --> 00:12:24,839 Speaker 1: continents and the continents of that time. And so they 225 00:12:24,840 --> 00:12:27,880 Speaker 1: tried to reproduce that and that is amazing that the 226 00:12:27,920 --> 00:12:31,400 Speaker 1: silk road came up. That popped up. Another example I 227 00:12:31,400 --> 00:12:34,760 Speaker 1: think it's really cool is this is by Andrew Adamatzki, 228 00:12:34,920 --> 00:12:37,320 Speaker 1: and he's a researcher at the University of West England. 229 00:12:37,880 --> 00:12:40,040 Speaker 1: He wanted to figure out what would happen in the 230 00:12:40,120 --> 00:12:43,560 Speaker 1: nuclear disaster. In other words, if a reactor melted down, 231 00:12:43,800 --> 00:12:46,079 Speaker 1: what would be the best course of action for citizens 232 00:12:46,080 --> 00:12:50,680 Speaker 1: to flee from it. So he took those ice eilier 233 00:12:50,960 --> 00:12:54,320 Speaker 1: modes that um that are used for highway like patterns, 234 00:12:55,120 --> 00:12:58,840 Speaker 1: and they grew a slime mold network of highways for Canada. 235 00:12:59,280 --> 00:13:02,520 Speaker 1: And then they placed a crystal of salt which repels 236 00:13:02,679 --> 00:13:05,840 Speaker 1: slime molds on the map where the Bruce nuclear power 237 00:13:05,880 --> 00:13:08,920 Speaker 1: plants located in Canada. And then what they found is 238 00:13:08,960 --> 00:13:11,160 Speaker 1: that the slime mold abandoned its tendrils near the salt 239 00:13:11,200 --> 00:13:13,959 Speaker 1: and then grew a new highway pattern that efficiently re 240 00:13:14,200 --> 00:13:18,679 Speaker 1: routed food across Canada and also showed different paths that 241 00:13:18,720 --> 00:13:22,280 Speaker 1: you could leave obviously this area. So it sheds some 242 00:13:22,360 --> 00:13:26,040 Speaker 1: sort of light on what can happen in disaster situations. Yeah, 243 00:13:26,080 --> 00:13:29,599 Speaker 1: that's it's just amazing to think about slime mold is 244 00:13:29,960 --> 00:13:33,520 Speaker 1: that is, being capable of doing this um and again 245 00:13:33,559 --> 00:13:37,200 Speaker 1: it ultimately makes us rethink what intelligence is, um is 246 00:13:37,200 --> 00:13:42,800 Speaker 1: as we we look at possible models for extraterrestrial life. Yeah. 247 00:13:42,840 --> 00:13:45,959 Speaker 1: Adam Rogers, he's a senior editor at Wired. He has 248 00:13:46,000 --> 00:13:48,199 Speaker 1: a really interesting riff on this, so if you want 249 00:13:48,240 --> 00:13:50,680 Speaker 1: to see his video, check that out on Wired dot com. 250 00:13:51,360 --> 00:13:55,920 Speaker 1: I believe the column is observation Deck Intelligent slime Molds 251 00:13:56,000 --> 00:13:58,960 Speaker 1: and the applications here with slime molds, I mean, aside 252 00:13:58,960 --> 00:14:03,240 Speaker 1: from possible shooting scenarios that were in addition to UH 253 00:14:03,240 --> 00:14:06,600 Speaker 1: their biophysicist in Germany and Singapore who think that the 254 00:14:06,679 --> 00:14:10,200 Speaker 1: mathematical models that they were agam based on sly mold 255 00:14:10,559 --> 00:14:14,520 Speaker 1: behavior might lead to new ways to starve tumors of 256 00:14:14,559 --> 00:14:18,280 Speaker 1: blood and essentially to a fight cancer, Yeah, which is 257 00:14:18,320 --> 00:14:21,000 Speaker 1: because what they found is that again there's this mathematical 258 00:14:21,120 --> 00:14:25,040 Speaker 1: similarity in the ways that a tumor tries to gain 259 00:14:25,120 --> 00:14:28,360 Speaker 1: nutrients from the body and the way that slim mold grows. 260 00:14:29,040 --> 00:14:34,280 Speaker 1: So taking those those two um examples, they can actually 261 00:14:34,360 --> 00:14:36,200 Speaker 1: try to figure out ways that they could try to 262 00:14:36,200 --> 00:14:38,280 Speaker 1: starve that tumor. As you say, yeah, I mean it 263 00:14:38,320 --> 00:14:41,520 Speaker 1: all comes down I think to the idea you think about, Okay, 264 00:14:41,560 --> 00:14:43,800 Speaker 1: what is what is mathematics? What is our what is 265 00:14:43,800 --> 00:14:46,920 Speaker 1: our spatial understanding? What is what is the the ability 266 00:14:46,960 --> 00:14:49,120 Speaker 1: to create a map on a piece of paper as 267 00:14:49,160 --> 00:14:51,560 Speaker 1: a as an intelligent human like, it all comes down 268 00:14:51,600 --> 00:14:55,480 Speaker 1: to our ability to navigate the physical world. Um, it's 269 00:14:55,520 --> 00:14:59,520 Speaker 1: just kind of a an ability that has grown, uh 270 00:15:00,040 --> 00:15:03,000 Speaker 1: for more robust with the passage of time, with our 271 00:15:03,000 --> 00:15:05,680 Speaker 1: evolution and then with our the building of our culture. 272 00:15:06,080 --> 00:15:09,680 Speaker 1: But at it's at the very like base level, something 273 00:15:09,720 --> 00:15:12,560 Speaker 1: even without a brain, has to be able to do 274 00:15:12,640 --> 00:15:14,760 Speaker 1: this to some level. And the and the slime mold 275 00:15:15,240 --> 00:15:18,240 Speaker 1: does a fantastic job. So if you ever find yourself 276 00:15:18,400 --> 00:15:23,040 Speaker 1: lost wandering about, think about, yeah, I think about the 277 00:15:23,080 --> 00:15:28,320 Speaker 1: serum polysphal um, and take take heart in saying that 278 00:15:28,360 --> 00:15:32,800 Speaker 1: this uh, this organism that goes back a billion years 279 00:15:33,360 --> 00:15:36,920 Speaker 1: can find a way and so too can you. All Right, well, 280 00:15:36,920 --> 00:15:38,880 Speaker 1: there's slime Mold for you, and that finishes out our 281 00:15:38,880 --> 00:15:40,840 Speaker 1: three episodes on slime. If you missed it any of 282 00:15:40,840 --> 00:15:43,000 Speaker 1: the other two, do check them out. There's a lot 283 00:15:43,040 --> 00:15:45,840 Speaker 1: of cool data in there, and it really really made 284 00:15:45,840 --> 00:15:49,280 Speaker 1: me rethink what slime is. And really, as I mentioned before, 285 00:15:49,320 --> 00:15:53,480 Speaker 1: a long time fan of slime loved slimy monsters, slimy 286 00:15:53,520 --> 00:15:56,920 Speaker 1: things even as I hated slugs, and uh, and there's 287 00:15:56,960 --> 00:16:00,160 Speaker 1: just so much more there, uh, not only understanding how 288 00:16:00,240 --> 00:16:02,720 Speaker 1: slime works, but but slugs as well. I mean, they're 289 00:16:02,920 --> 00:16:06,280 Speaker 1: I think, to slug like monsters that have appeared in 290 00:16:06,400 --> 00:16:10,680 Speaker 1: various uh forms of fiction and even once where they 291 00:16:10,720 --> 00:16:13,600 Speaker 1: do a pretty good job of making the creature monstrous, like, 292 00:16:13,640 --> 00:16:16,400 Speaker 1: they really don't dive into all of the just weird 293 00:16:16,440 --> 00:16:20,880 Speaker 1: and fascinating biology of a slug. So just putting that 294 00:16:20,880 --> 00:16:23,480 Speaker 1: out there, are there any potential filmmakers and fiction weavers 295 00:16:23,800 --> 00:16:26,080 Speaker 1: in the audience, Well, let's call the robot over and 296 00:16:26,080 --> 00:16:29,680 Speaker 1: do one quick listener mail this when it comes to 297 00:16:29,720 --> 00:16:32,440 Speaker 1: us from Catherine and she has a book recommendation for us, 298 00:16:32,480 --> 00:16:34,720 Speaker 1: She says, Robert and Julie, your most recent podcast made 299 00:16:34,720 --> 00:16:36,280 Speaker 1: me think of one of my favorite books by my 300 00:16:36,320 --> 00:16:39,120 Speaker 1: favorite author. For a great book about pretending to be 301 00:16:39,200 --> 00:16:42,480 Speaker 1: someone you're not, I recommend Mother Night by Kurt Vonnegut. 302 00:16:42,520 --> 00:16:44,640 Speaker 1: The main character is an American playwright who has spent 303 00:16:44,720 --> 00:16:46,960 Speaker 1: most of his life in Germany. As an adult, during 304 00:16:47,000 --> 00:16:49,120 Speaker 1: World War Two, he was recruited by the US government 305 00:16:49,120 --> 00:16:51,800 Speaker 1: to help transmit messages to the Allies. He does this 306 00:16:51,920 --> 00:16:55,600 Speaker 1: via code inserted into his Nazi propaganda radio show. He 307 00:16:55,680 --> 00:16:57,400 Speaker 1: is so good at pretending to be a Nazi that 308 00:16:57,440 --> 00:16:59,720 Speaker 1: he has respected as a leader within the Nazi Party. 309 00:17:00,040 --> 00:17:01,800 Speaker 1: He also managed to get on the list of wanted 310 00:17:01,800 --> 00:17:04,800 Speaker 1: war criminals. The problem is that he entered this knowing 311 00:17:04,840 --> 00:17:07,240 Speaker 1: that the U s would never recognize his work, nor 312 00:17:07,320 --> 00:17:09,760 Speaker 1: would they come to his defense. So really, the only 313 00:17:09,760 --> 00:17:12,480 Speaker 1: people invested in keeping him alive or the nazis a 314 00:17:12,520 --> 00:17:14,840 Speaker 1: group he does not truly want to be a part of. 315 00:17:15,160 --> 00:17:18,400 Speaker 1: There's a movie made of the book starring Nicknolty. Read 316 00:17:18,440 --> 00:17:21,280 Speaker 1: the book. Thanks as always for the entertainment and education. 317 00:17:21,520 --> 00:17:24,000 Speaker 1: I hate the term entertainment. Yeah, I don't think we 318 00:17:24,080 --> 00:17:27,520 Speaker 1: really use entertainment either. But let's got a bit of 319 00:17:27,520 --> 00:17:30,200 Speaker 1: a musty ring to it. Yeah, but we hit the idea. 320 00:17:30,280 --> 00:17:33,760 Speaker 1: But we're we're glad that we're providing some interesting tidbits 321 00:17:33,800 --> 00:17:36,600 Speaker 1: for you guys. That's an awesome book recommendation, something I 322 00:17:36,640 --> 00:17:39,000 Speaker 1: definitely want to follow up on. Yeah, I've I've only 323 00:17:39,000 --> 00:17:41,520 Speaker 1: read a couple of Vonnegut stories of read Slaughterhouse Five 324 00:17:41,680 --> 00:17:46,400 Speaker 1: and The Sirens of Titan. Good stuff, especially Slaughterhouse Five, 325 00:17:46,480 --> 00:17:49,159 Speaker 1: one of my all time favorites. So hey, if you 326 00:17:49,160 --> 00:17:50,600 Speaker 1: want to reach out to us, you want to share 327 00:17:50,640 --> 00:17:52,360 Speaker 1: some stuff with us, you want to see what we're 328 00:17:52,440 --> 00:17:55,040 Speaker 1: up to, what we're blogging about, what links we're looking at, 329 00:17:55,080 --> 00:17:58,520 Speaker 1: maybe get an idea of what future episodes will consist of. 330 00:17:59,000 --> 00:18:01,560 Speaker 1: Then you can find us on Facebook, you can find 331 00:18:01,600 --> 00:18:03,480 Speaker 1: us on tumbler. We are stuff to blow your mind 332 00:18:03,480 --> 00:18:05,240 Speaker 1: on both of those, and you can also find us 333 00:18:05,280 --> 00:18:07,879 Speaker 1: on Twitter, where our handle is blow the Mind. And 334 00:18:08,080 --> 00:18:10,520 Speaker 1: you can also drop us a line at blow the 335 00:18:10,560 --> 00:18:19,159 Speaker 1: Mind at Discovery dot com for more on this and 336 00:18:19,240 --> 00:18:21,800 Speaker 1: thousands of other topics. Is it how Stuff Works dot 337 00:18:21,800 --> 00:18:27,040 Speaker 1: com