WEBVTT - Bacterial Computers 0:00:00.160 --> 0:00:07.400 Brought to you by Toyota. Let's go places. Welcome to 0:00:07.560 --> 0:00:15.880 Forward Thinking eithan everyone, and welcome to Forward Thinking, the 0:00:15.960 --> 0:00:18.439 podcast that looks at the future and says there's a 0:00:18.440 --> 0:00:22.120 place for us somewhere, a place for us. I'm Jonathan 0:00:22.160 --> 0:00:25.640 Strickland and I'm Joe McCormick. And are our good friend 0:00:25.720 --> 0:00:32.240 Lauren is still battling bacteria. Uh, possibly with the sword. 0:00:32.520 --> 0:00:35.519 Strange coincidence. Yeah, it's almost as if we just continued 0:00:35.560 --> 0:00:39.280 recording on the same day as the other episode. There's 0:00:39.280 --> 0:00:42.360 a peak behind the curt most But anyway, we still 0:00:42.360 --> 0:00:44.879 want to talk a little more about bacteria and uh. 0:00:44.960 --> 0:00:48.080 And in the last podcast, we kind of talked about bacteria, 0:00:48.120 --> 0:00:50.960 about how they how we how we've used bacteria to 0:00:51.000 --> 0:00:55.400 create stuff, whether it's drugs or chemicals of some sort, 0:00:56.000 --> 0:01:01.120 or even possibly harnessing bacteria to form nano wires or 0:01:01.200 --> 0:01:04.960 even to do physical work on a very tiny scale. 0:01:05.360 --> 0:01:07.440 But we wanted to talk about a different application for 0:01:07.480 --> 0:01:11.600 bacteria in this podcast. Yeah, we wondered, have you ever 0:01:11.640 --> 0:01:15.600 considered the fact that the bacteria that gave you food 0:01:15.680 --> 0:01:19.680 poisoning when you were on vacation um and kept you 0:01:19.720 --> 0:01:22.319 inside for a week might be smarter than you are, 0:01:22.600 --> 0:01:25.040 or at least better at math. No, I have not. 0:01:25.280 --> 0:01:28.039 I thought that I was dumb forgetting it, but I 0:01:28.080 --> 0:01:30.840 didn't think that the bacteria itself was smarter. Well that's 0:01:30.840 --> 0:01:34.160 what you get when you eat the seafood special at 0:01:34.200 --> 0:01:37.679 a gas station. Yeah. Yeah, never again, well maybe one 0:01:37.680 --> 0:01:40.800 more time. But yeah, we wanted to talk about using 0:01:40.800 --> 0:01:44.520 bacteria to to do computations and the fact that a 0:01:44.560 --> 0:01:49.000 bacterial computer is in fact a possibility for very specific 0:01:49.000 --> 0:01:51.600 types of problems. People are probably going like, wait, wait, 0:01:51.600 --> 0:01:55.240 wait what Yeah, no, you heard us right, like, using 0:01:55.320 --> 0:02:00.240 bacteria to solve computational problems. It's real. We're not talking 0:02:00.280 --> 0:02:05.200 about you need to clean your keyboard, although that's also true. Gross. Yeah, 0:02:05.240 --> 0:02:07.960 this is also not just crazy future is speculation. We're 0:02:07.960 --> 0:02:10.720 talking about stuff that's already been done in the lab. 0:02:11.200 --> 0:02:14.120 So so, Jonathan, how what what are we talking about here? 0:02:14.160 --> 0:02:17.760 What's involved? We're mostly talking about NP class problems. So 0:02:17.800 --> 0:02:22.280 these are problems that are classically very difficult for computers 0:02:22.280 --> 0:02:26.519 to solve. NP problems tend to have lots of variables, 0:02:26.560 --> 0:02:29.079 and they tend to have a lot of potential uh 0:02:29.720 --> 0:02:32.480 pathways that you can take and Classically, the way a 0:02:32.520 --> 0:02:37.040 computer eliminates possibilities is it goes through every single permutation 0:02:37.520 --> 0:02:40.040 and checks to find out whether or not it's a 0:02:40.120 --> 0:02:43.240 valid response, which means that it has to go through 0:02:43.280 --> 0:02:46.680 them sequentially and one at a time, one at a time. So, 0:02:47.639 --> 0:02:49.720 for example, the one of the problems we can talk 0:02:49.760 --> 0:02:53.600 about is the Hamiltonian path problem. Uh, there's also the 0:02:53.639 --> 0:02:57.000 burnt pancake problem, which do you want to talk about 0:02:57.000 --> 0:02:59.240 that one? First, let's start with an example. What is 0:02:59.280 --> 0:03:02.080 the first explore and what the problems are? Okay, so 0:03:03.280 --> 0:03:06.880 the burnt pancake problem, Well, it starts with the pancake problem. 0:03:06.919 --> 0:03:11.240 And this is a sorting problem in computation. Um. And 0:03:11.320 --> 0:03:13.840 so a lot of what computer programmers do is come 0:03:13.919 --> 0:03:16.799 up with ways of arranging data in a certain way, 0:03:16.880 --> 0:03:22.400 like from smallest to largest. Um. So the pancake problem 0:03:22.639 --> 0:03:25.080 tells you to imagine this. Okay, So you're you're like 0:03:25.120 --> 0:03:27.440 a waiter running around in a restaurant and you've got 0:03:27.440 --> 0:03:31.520 a stack of X number of pancakes in your hand. Um, 0:03:31.560 --> 0:03:34.680 that's not sanitary. It should be on a plate. Well, okay, 0:03:34.760 --> 0:03:37.760 imagine it's on a plate, but you're you're holding the 0:03:37.760 --> 0:03:41.080 bottom of the plate with one hand. Um, and while 0:03:41.120 --> 0:03:43.920 you're running around the restaurant. Um, you want to arrange 0:03:43.920 --> 0:03:46.680 the pancakes so that the largest pancake is on the 0:03:46.720 --> 0:03:49.080 bottom and the smallest pancake is on the top, thus 0:03:49.160 --> 0:03:53.000 ensuring pancakes stability. Right, very important. Right, you can't put 0:03:53.040 --> 0:03:55.480 the tallest pancake on the top it say it was 0:03:55.520 --> 0:03:59.840 just the topple over. It's madness. Uh so how do 0:03:59.880 --> 0:04:02.320 you arrange it? Well, you've only got one free hand, 0:04:02.640 --> 0:04:06.119 so you can't go sticking inserting all over. You can 0:04:06.200 --> 0:04:09.680 only flip stacks of pancakes. So imagine you've got a 0:04:09.680 --> 0:04:12.080 stack of pancakes and you can stick a spatula in 0:04:12.680 --> 0:04:16.599 anywhere along the stack and flip everything that's above the 0:04:16.640 --> 0:04:19.560 stat the spatula over. So yeah, so you would want 0:04:19.560 --> 0:04:22.359 to try and find the way of doing this with 0:04:22.440 --> 0:04:25.440 the fewest number of flaps. What's the fewest number of 0:04:25.440 --> 0:04:28.320 times you can stick the spatula in and turn over 0:04:28.400 --> 0:04:31.839 everything on top of it to get the stacks sorted 0:04:31.920 --> 0:04:34.560 from largest to smallest. See my solution to this problem 0:04:34.600 --> 0:04:38.080 is to order waffles. But you could have some waffles 0:04:38.080 --> 0:04:40.440 bigger than another. Oh well, probably not actually, because the 0:04:40.440 --> 0:04:43.760 waffle press has a standard size, whereas the pancakes that 0:04:43.880 --> 0:04:47.400 they spread out according to the poor exactly anyway. So 0:04:47.560 --> 0:04:51.840 that so that's smart. That's a more symmetrical order. Okay, well, um, 0:04:51.960 --> 0:04:54.279 so so you're sorting like that. So that's one type 0:04:54.279 --> 0:04:56.720 of hard problem. And what you want to do when 0:04:56.760 --> 0:04:59.960 you've got a pancake sorting algorithm is to figure out 0:05:00.120 --> 0:05:02.840 the least number of flips, like we said to get 0:05:02.920 --> 0:05:07.280 the stack in order. The burnt pancake problem adds another complication. 0:05:07.760 --> 0:05:10.799 It says that each pancake is burned on one side, 0:05:10.920 --> 0:05:13.479 got you, and so you want to get the stack 0:05:13.480 --> 0:05:16.359 in order, but you also want all of the burned 0:05:16.440 --> 0:05:20.000 sides facing down, got youa so you, So it may 0:05:20.120 --> 0:05:23.760 require extra flips because some of the when you when 0:05:23.760 --> 0:05:26.680 you arrange stuff, it may turn out that the one 0:05:26.720 --> 0:05:30.040 that would have been in the right position is it's 0:05:30.240 --> 0:05:33.640 from based on size, it's perfectly fine, but because the 0:05:33.640 --> 0:05:35.640 burnt side is up, you have to flip that. But 0:05:35.680 --> 0:05:38.000 that means that everything on top of it also gets flipped. 0:05:38.000 --> 0:05:39.360 So then you have to figure out how many more 0:05:39.360 --> 0:05:43.279 flips do you do to get all ordered largest on 0:05:43.320 --> 0:05:46.000 the bottom and burnt sides down. If you just stop 0:05:46.040 --> 0:05:47.919 and think about this for a second, this is a 0:05:48.040 --> 0:05:51.000 really hard problem to solve. Yeah, it's not something that 0:05:51.160 --> 0:05:53.760 is you know, you just look at Especially it gets 0:05:53.760 --> 0:05:56.640 harder the more pancakes you add, right, And that's that's 0:05:56.640 --> 0:05:58.760 another thing that we can talk about that a lot 0:05:58.800 --> 0:06:02.240 of these NP problems fall into this category where they 0:06:02.240 --> 0:06:05.760 get uh much more complex when you start to add 0:06:06.120 --> 0:06:09.520 extra variables in they get what would is it exponentially 0:06:09.600 --> 0:06:12.039 more complex? I would need to look into it to 0:06:12.080 --> 0:06:15.960 make absolutely sure that exponentially is in fact the correct term. 0:06:16.040 --> 0:06:20.279 I would say at least geometrically more complex. In other words, 0:06:20.320 --> 0:06:24.920 that it's it's increasing at a very um predictable rate, 0:06:24.920 --> 0:06:28.640 because exponentially would mean that it's increasing ten times over 0:06:29.240 --> 0:06:35.279 each time or what. Okay, yeah, we'll settle that later. Yes, 0:06:35.680 --> 0:06:39.120 but anyway, it does get far more complex. And once 0:06:39.160 --> 0:06:41.120 you get to a certain level of complexity and you're 0:06:41.160 --> 0:06:43.520 using a classic computer to try and solve this, remember 0:06:43.600 --> 0:06:47.280 that classic computer is going through every single variation of 0:06:47.320 --> 0:06:49.840 the solution of that problem, so it has to wait 0:06:49.880 --> 0:06:51.719 until it's finished with one before it can begin the 0:06:51.760 --> 0:06:54.480 next one. If you have a multi core processor, then 0:06:54.480 --> 0:06:57.200 it can divide that up among the various cores and 0:06:57.279 --> 0:06:59.720 try and solve the problem more quickly by each core 0:06:59.800 --> 0:07:02.719 we're working on a different variation of that, but even 0:07:02.760 --> 0:07:06.280 then you're still only reducing the overall time by a 0:07:06.400 --> 0:07:09.000 tiny amount compared to how you know, this could take 0:07:09.640 --> 0:07:12.800 decades or centuries to solve, depending on how complex the 0:07:12.800 --> 0:07:16.600 problem is. If you're using a classical computer UM and 0:07:16.640 --> 0:07:18.360 the other NP problem, we're going to talk about the 0:07:18.360 --> 0:07:21.440 Hamiltonian path problem. This is one you guys may have 0:07:21.480 --> 0:07:24.720 heard about. The idea is that you've got these different 0:07:24.760 --> 0:07:27.880 nodes within a system, or you can give it as 0:07:27.920 --> 0:07:32.160 cities UM. Sometimes this is a variation of this is 0:07:32.200 --> 0:07:35.320 called the traveling salesman problem. The traveling salesman problem is 0:07:35.360 --> 0:07:38.960 a little bit harder because it involves calculating a minimum distance. Right. 0:07:39.160 --> 0:07:41.640 This is a little different in that the ideas that 0:07:41.680 --> 0:07:44.640 you've got Let's let's say you've got five cities and 0:07:44.920 --> 0:07:47.800 you want to visit all five cities, and the cities 0:07:47.840 --> 0:07:51.680 have roadways, but not every city is connected to every 0:07:51.760 --> 0:07:55.000 other city, right, So some cities are connected to maybe 0:07:55.000 --> 0:07:57.400 just one other city. Other cities are connected to two 0:07:57.520 --> 0:08:00.400 or three, and you have to figure out which way 0:08:00.440 --> 0:08:02.760 you can take where you visit each city once and 0:08:02.920 --> 0:08:06.920 only once, but you do visit all the cities. So again, 0:08:07.120 --> 0:08:09.000 a classic computer would have to sit there and go 0:08:09.080 --> 0:08:13.360 through each variation and validate or throw out the results 0:08:13.360 --> 0:08:17.960 based upon what happened. So depending on how how many 0:08:18.040 --> 0:08:21.120 cities are there, that can take a really long time 0:08:21.160 --> 0:08:25.840 because there's so many different options. So instead of trying 0:08:26.200 --> 0:08:30.200 each thing, instead of having one smart computer try each 0:08:30.520 --> 0:08:34.640 option one at a time. Is there something? Is there 0:08:34.679 --> 0:08:38.000 something that can do lots of different variations all at 0:08:38.000 --> 0:08:40.199 the same time. There are a couple of things, and 0:08:40.240 --> 0:08:43.480 one of them, of course, is what we're talking about. Bacteria. Uh. 0:08:43.800 --> 0:08:46.880 It turns out that if you are using bacteria and 0:08:47.040 --> 0:08:50.400 you encode d n A so that it essentially simulates 0:08:50.400 --> 0:08:55.160 whatever the problem is. Uh, And then you kind of 0:08:55.160 --> 0:08:57.760 sounds crazy, but you're kind of shaking the bacteria altogether. 0:08:58.280 --> 0:09:02.000 What what results is the answer to the problem. So 0:09:02.520 --> 0:09:05.880 both of the problems we've just described, the burnt pancake 0:09:05.960 --> 0:09:08.960 problem and the Hamiltonian path problem, believe it or not, 0:09:09.160 --> 0:09:14.000 have been solved by bacteria. Shut your mouth, yes, okay, 0:09:14.200 --> 0:09:19.640 bacterial computers what some people call uh back toputing. I 0:09:21.000 --> 0:09:24.000 wish I had not heard that, But alright, we're bacterial puting, 0:09:24.320 --> 0:09:31.480 or you're not making it any better pupingpingputing, coputing, okay, 0:09:31.679 --> 0:09:37.400 okay um. Bacterial computers, literally colonies of bacteria have been 0:09:37.400 --> 0:09:40.360 made to solve these problems. Well, how on earth could 0:09:40.360 --> 0:09:42.679 they do that? They're they're able to do this in 0:09:42.960 --> 0:09:47.040 parallel as opposed to sequentially. So the classical computer is 0:09:47.040 --> 0:09:49.240 trying to solve the problem sequentially, like we said, it's 0:09:49.240 --> 0:09:53.840 going through all but bacteria can actually examine all of 0:09:53.880 --> 0:09:57.720 these kind of at once. And it's interesting. They researchers 0:09:57.720 --> 0:10:00.560 had for the Hamiltonian problem. What they did was they 0:10:00.559 --> 0:10:04.719 only used three cities, which dramatically reduces the complexity. But 0:10:05.160 --> 0:10:08.120 it's a proof of concept and it's and they showed 0:10:08.120 --> 0:10:10.720 that it's a sound proof of concept. What they did 0:10:10.880 --> 0:10:14.760 was they modified the DNA of E. Coli. Bacteria are 0:10:15.000 --> 0:10:18.000 good old buddies who make you feel not so good 0:10:18.040 --> 0:10:22.840 after you've had that lukewarm hot dog. Uh. But they 0:10:22.920 --> 0:10:27.680 modified the DNA and they ended up shuffling this DNA 0:10:27.760 --> 0:10:31.319 together and the bacteria ended up producing the correct answer. 0:10:31.440 --> 0:10:34.720 The back to the DNA was to give the bacteria 0:10:34.800 --> 0:10:40.240 command to either glow red or green. And then uh, 0:10:40.360 --> 0:10:44.040 they put the bacteria in different combinations that represented the 0:10:44.160 --> 0:10:49.200 various um options for traveling through this this these nodes, 0:10:50.280 --> 0:10:53.760 and the one that was the actual answer ended up 0:10:53.800 --> 0:10:58.880 turning yellow. The bacteria turned yellow. And so in a 0:10:58.920 --> 0:11:02.960 way you're thinking, all right, well, you're just throwing all 0:11:03.000 --> 0:11:05.560 the options into variations and then you shake it up 0:11:05.559 --> 0:11:07.760 and see what comes out. And that's actually true. You know, 0:11:07.800 --> 0:11:10.760 you're using all these but it is processing in parallel. 0:11:10.800 --> 0:11:13.440 But but it's useful. I mean, it can solve the problem. 0:11:13.480 --> 0:11:16.640 It's like even if the bacteria don't know what they're doing. 0:11:17.000 --> 0:11:19.760 Of course, one might point out that the silicon and 0:11:19.800 --> 0:11:22.320 your computer chip doesn't know what it's doing. Yeah, and 0:11:22.360 --> 0:11:24.120 often I don't know what I'm doing, so I don't 0:11:24.160 --> 0:11:27.120 see where the But so the bacteria don't know what 0:11:27.200 --> 0:11:29.559 they're doing, they don't understand that they're solving the problem. 0:11:29.600 --> 0:11:31.680 But it just happens to be that we can set 0:11:31.720 --> 0:11:34.720 it so that the ones that do solve the problem 0:11:34.760 --> 0:11:37.640 make it clear. Yeah, exactly. So what we can do 0:11:37.800 --> 0:11:40.319 is you create the bacteria with all the different variations 0:11:40.360 --> 0:11:43.920 that you need to address whatever the problem is. You 0:11:44.000 --> 0:11:47.120 do all the different combinations that those bacteria can be in, 0:11:47.120 --> 0:11:51.480 in other words, like the variations, and then you you 0:11:51.679 --> 0:11:54.880 take a look and see the results and whatever. Whatever 0:11:54.920 --> 0:11:56.880 the right answer is is going to be evident based 0:11:56.960 --> 0:11:59.160 upon whatever you've told the bacteria to do. When it 0:11:59.320 --> 0:12:03.520 when it's the result you need. So the what I 0:12:03.559 --> 0:12:07.480 was reading, if I understand correctly, the way they ascertained 0:12:07.559 --> 0:12:11.280 the success of computing the burnt pancake problem in bacteria 0:12:11.400 --> 0:12:16.360 was they I think they introduced an antibiotic into the 0:12:16.400 --> 0:12:20.400 bacterial colonies and basically they had worked it so that 0:12:20.520 --> 0:12:24.960 bacteria that solved the problem correctly would end up with 0:12:25.000 --> 0:12:28.520 a resistance to the antibiotics, so those bacteria would survive 0:12:28.720 --> 0:12:31.120 in all the rest. Ye off, Yeah, yeah, that's and 0:12:31.160 --> 0:12:34.000 that that's a very quick way of taking a look 0:12:34.000 --> 0:12:36.160 and saying, all right, here's your answer, because it has 0:12:36.200 --> 0:12:39.400 to be. Uh, that's it's kind of an interesting approach. 0:12:39.440 --> 0:12:42.560 The other the other big method I've heard of for 0:12:42.720 --> 0:12:45.120 tackling these sort of problems, besides using something like a 0:12:45.120 --> 0:12:48.240 graphics processing unit which has lots and lots of different 0:12:48.400 --> 0:12:52.360 parallel processors in it. Uh, they that would still take 0:12:52.440 --> 0:12:54.400 a long time to solve. A lot of these NP 0:12:54.600 --> 0:12:59.880 problems um depending upon how complex they were. But quantum 0:13:00.000 --> 0:13:03.760 computers are very take a very similar approach. But that's 0:13:03.800 --> 0:13:05.960 a whole other episode. It's a different episode. But just 0:13:06.280 --> 0:13:08.840 really quickly, a quantum computer, you know, a classic computer 0:13:08.960 --> 0:13:12.160 uses bits which are either a zero or a one, 0:13:12.320 --> 0:13:16.559 so that that binary digit um, that's what bit stands for. Well, 0:13:16.760 --> 0:13:21.560 quantum computers use cubits qu b I t s, and 0:13:21.640 --> 0:13:25.559 these are bits that exist in superposition, meaning that they 0:13:26.800 --> 0:13:28.920 not just a zero or one, they are both a 0:13:29.000 --> 0:13:33.520 zero and the one and technically everything in between. And theoretically, 0:13:33.760 --> 0:13:38.320 if you had enough cubits together, you could process these 0:13:38.360 --> 0:13:42.839 problems in parallel, where each cubit is either a zero 0:13:43.040 --> 0:13:46.320 or a one or both or whatever, and you process 0:13:46.440 --> 0:13:49.800 all the all the possibilities all at once, assuming that 0:13:49.840 --> 0:13:52.640 you have enough cubits to tackle whatever the big problem is. 0:13:53.080 --> 0:13:55.600 So you would have to first create enough cubits to 0:13:55.600 --> 0:13:58.360 be able to do this. If you did, then you 0:13:58.400 --> 0:14:01.040 could solve the problem in parallel. We're really good at 0:14:01.080 --> 0:14:04.839 manipulating cubits, aren't we not. Unfortunately, no, no, because if 0:14:04.840 --> 0:14:09.920 you it's very it's a very um delicate system. Anything 0:14:09.960 --> 0:14:13.920 time you're you're talking about quantum effects. You are talking 0:14:13.960 --> 0:14:17.960 about a very delicate system that can very simply break down. 0:14:18.120 --> 0:14:21.880 And if it broke down, your quantum computer would essentially 0:14:21.880 --> 0:14:24.640 become a classical computer. Do we do we interfere with 0:14:24.680 --> 0:14:26.840 the state of the cubit whenever we look at the cubit? 0:14:26.880 --> 0:14:29.560 I mean, that's the problem, right. And then also I 0:14:29.600 --> 0:14:32.760 should point out that the answers you get from a 0:14:32.800 --> 0:14:37.920 quantum computer are probabilistic. They are not definitive. So you 0:14:37.920 --> 0:14:43.000 would get essentially a level of like a percentage of 0:14:43.080 --> 0:14:47.760 how accurate is this answer? Like is it it's there's 0:14:47.760 --> 0:14:50.120 an eight percent chance this is the answer kind of 0:14:50.160 --> 0:14:53.800 thing like you're never gonna get response where you're going 0:14:53.840 --> 0:14:56.120 to know for sure that you've got the right answer. 0:14:56.880 --> 0:15:01.960 That's again grossly under stating what a quantum computer does. 0:15:02.040 --> 0:15:03.920 But you know, for the purposes of this discussion, I 0:15:03.920 --> 0:15:05.960 thought it was interesting just because again it was one 0:15:06.000 --> 0:15:08.080 of those things where as I was reading about these 0:15:08.120 --> 0:15:10.400 bacterial computers, I thought, well, that's kind of similar to 0:15:10.400 --> 0:15:12.880 what a quantum computer does. It's just doing it with 0:15:12.960 --> 0:15:15.200 d n A and doing it in a you know, 0:15:15.320 --> 0:15:19.400 not in a quantum like a weird quantum effect kind 0:15:19.400 --> 0:15:21.960 of way. Ps right to us and tell us to 0:15:22.040 --> 0:15:24.840 do an episode on quantum computers and we can convince 0:15:24.840 --> 0:15:26.680 our bosses to do it. Yeah, we need enough of 0:15:26.720 --> 0:15:28.400 you guys to say I really want to know about 0:15:28.400 --> 0:15:30.880 this quantum computer. Also we can talk about quantum encryption, 0:15:30.920 --> 0:15:34.320 which is wicked awesome. But yeah, you need to write 0:15:34.360 --> 0:15:41.360 inn until So Yeah, so we have solved problems with bacteria. Yes, 0:15:41.600 --> 0:15:44.200 what what else do we need to do to make 0:15:44.280 --> 0:15:48.480 a bacterial computer. Well, you've got to be able to 0:15:48.520 --> 0:15:52.120 go beyond just the prototype stage and make sure you have. 0:15:52.200 --> 0:15:54.600 You have to. It's all a question of scale, right, 0:15:55.040 --> 0:15:57.080 So the scale is an issue. And also you know 0:15:57.080 --> 0:15:59.640 you got to feed your computer as it turns out. Well, 0:15:59.680 --> 0:16:02.320 maybe here's how I should rephrase it. Are the ways 0:16:02.360 --> 0:16:06.000 that we know we can use bacteria in uh, or 0:16:06.080 --> 0:16:07.920 at least we think we will be able to use 0:16:07.960 --> 0:16:11.360 bacteria in in computing in the nearer future. In a 0:16:11.440 --> 0:16:15.760 in an indirect way, there are bacteria that can produce 0:16:16.760 --> 0:16:22.520 essentially magnetic material magnetite, right, magnetite, it's the most magnetic 0:16:22.600 --> 0:16:27.440 natural mineral in them yep. And there are there's bacteria 0:16:27.560 --> 0:16:34.760 that that consumes iron and creates magnetite, and so you know, 0:16:34.800 --> 0:16:38.480 if you've ever wondered about how how a hard drive works, 0:16:38.480 --> 0:16:42.000 a classic hard drive, those are magnetic drives. They are 0:16:42.240 --> 0:16:46.680 storing information magnetically. That's also why if you've ever worked 0:16:46.720 --> 0:16:50.280 with any kind of computer or magnetic storage, you know 0:16:50.560 --> 0:16:53.840 you're not supposed to bring powerful magnets anywhere close to 0:16:53.880 --> 0:16:56.880 that because you could accidentally wipe whatever it is you're 0:16:56.920 --> 0:17:02.200 working with. Um. Well, there there are bacteria that produce magnetite, 0:17:02.240 --> 0:17:05.119 and there's a possibility that we could use these to 0:17:05.240 --> 0:17:07.840 create new types of hard drives. Because one of the 0:17:07.920 --> 0:17:13.520 challenges we're encountering is designing uh computer components that are 0:17:13.920 --> 0:17:18.080 on an increasingly smaller scale. It's hard to get to 0:17:18.119 --> 0:17:20.479 a level of precision once we get down below a 0:17:20.520 --> 0:17:23.480 certain level, and this might give us a chance to 0:17:23.520 --> 0:17:30.080 create even more precise means of constructing something like hard drives. 0:17:30.160 --> 0:17:31.879 So it wouldn't be a full computer, it would be 0:17:31.960 --> 0:17:36.199 a computer component. But that's an actual possibility that we 0:17:36.240 --> 0:17:39.480 may see within the next few years. That's pretty cool, now, 0:17:39.520 --> 0:17:43.119 that's pretty awesome. The idea of harnessing bacteria to create 0:17:44.000 --> 0:17:48.639 things that that will increase our own ability to to 0:17:48.800 --> 0:17:52.800 store information and access information. That's interesting if you've listened 0:17:52.800 --> 0:17:55.080 to our last episode that that isn't the only thing, 0:17:55.640 --> 0:17:59.879 uh that bacteria can manufacture. Now we can create the 0:18:00.200 --> 0:18:03.080 like wires I mean, and the wires thing. To me, 0:18:03.160 --> 0:18:05.399 the wires thing is really interesting because the idea of 0:18:05.760 --> 0:18:08.040 being able to create wires that can exist within an 0:18:08.119 --> 0:18:12.160 organism means that you have a lot of options when 0:18:12.200 --> 0:18:15.000 it comes to cyborg implants. And as we've already covered 0:18:15.040 --> 0:18:18.680 in a previous episode of Forward Thinking, I'm an aspiring cyborg. 0:18:18.920 --> 0:18:24.400 So that'll just pave my pathway to robotic uh superiority 0:18:24.440 --> 0:18:29.240 that much more quickly. So you know, stay on. That 0:18:29.280 --> 0:18:32.400 gets a crazy look in your eye. I pretty much 0:18:32.400 --> 0:18:34.000 always have a crazy look at my eye, but I 0:18:34.000 --> 0:18:37.040 have a have a specifically crazy look at my eye here. 0:18:37.080 --> 0:18:41.119 I'm I'm mostly imagining that scene in Terminator where you 0:18:41.160 --> 0:18:45.280 see the robot on the mound of human skulls. That's 0:18:45.359 --> 0:18:49.639 you know, that's my happy They end up there. They 0:18:49.680 --> 0:18:52.239 don't necessarily start there, but I find a way to 0:18:52.280 --> 0:18:56.399 find a way. Yeah, how does the the naked in 0:18:56.480 --> 0:18:59.920 high school dream turned to well, standing on the skulls? 0:19:00.080 --> 0:19:03.399 Clothes don't don't transfer over when you go through the 0:19:03.440 --> 0:19:10.960 time point. That's correct. So okay, speaking of robots, let's 0:19:10.960 --> 0:19:13.960 do that. I had a kind of crazy idea. Um 0:19:14.040 --> 0:19:18.159 and and here we're going to utter speculation. But in 0:19:18.200 --> 0:19:21.800 the last podcast, we talked about how bacteria can be 0:19:21.880 --> 0:19:25.760 used to generate mechanical motion. Right, so you can, um, 0:19:25.800 --> 0:19:29.760 you can regulate the amount of oxygen and fluid um 0:19:29.800 --> 0:19:32.520 with bacteria suspended in it to get the bacteria to 0:19:32.560 --> 0:19:35.640 push micro gears. They're actually they're turning gears. They can 0:19:35.680 --> 0:19:40.040 operate tiny machinery. Okay, so you've got mechanical motion. We 0:19:40.119 --> 0:19:45.760 just talked about computing. Those two things put together are 0:19:45.760 --> 0:19:50.320 the building blocks of something we would call a robot. Yeah. Now, 0:19:50.359 --> 0:19:53.760 if you're talking about a bacterial robot, uh, this is 0:19:53.760 --> 0:19:57.160 not a nanobot. It's going to be larger than the nanoscale, 0:19:57.560 --> 0:20:01.360 but it would still would be made of bacteria. Yeah, 0:20:01.400 --> 0:20:04.240 you can have a in theory if we were able 0:20:04.280 --> 0:20:09.160 to harness this sort of power, then yeah, I guess 0:20:09.320 --> 0:20:12.520 I imagine. So, I mean you would still need uh, 0:20:12.800 --> 0:20:16.240 some means of processing that information because right now, what 0:20:16.280 --> 0:20:19.639 we're talking about with the computers is mostly you know, 0:20:20.160 --> 0:20:21.960 put all the dice in a in a in a 0:20:22.000 --> 0:20:24.320 bucket and shake um. And when you remove the bucket 0:20:24.359 --> 0:20:27.080 and you reveal what the dice have rolled. Because of 0:20:27.119 --> 0:20:30.080 the way that this system works, only the dice that 0:20:30.119 --> 0:20:32.639 are necessary to answer the question show up and you 0:20:32.680 --> 0:20:35.679 get the answer. Going from that to some sort of 0:20:35.720 --> 0:20:38.800 computer that can actually process information in a meaningful way 0:20:38.840 --> 0:20:41.440 and give commands, that's a big jump. It's not to 0:20:41.480 --> 0:20:44.560 say that we won't make it so. And also, like 0:20:44.600 --> 0:20:47.680 we've said before, if we're if we're talking about building 0:20:47.760 --> 0:20:50.879 something at a very tiny scale, it it behooves us 0:20:50.920 --> 0:20:54.560 to look at nature because they're already these natural organisms 0:20:54.600 --> 0:20:57.200 that are on this tiny, tiny scale that do very well. 0:20:57.720 --> 0:21:01.320 So if we can emulate that or manipulate them in 0:21:01.359 --> 0:21:05.439 some way, then we can create things on that scale 0:21:05.520 --> 0:21:07.639 much more quickly than we would if we just build 0:21:07.680 --> 0:21:12.480 from the ground up, so to speak. So could we 0:21:12.640 --> 0:21:16.480 have a bacterial robot? I don't see why not. If 0:21:16.520 --> 0:21:19.560 we did, what would it be good for an autonomous 0:21:19.600 --> 0:21:23.800 bacterial machine? I would imagine that that would have medical uses. 0:21:24.040 --> 0:21:27.560 I mean something that could especially if you had any 0:21:27.600 --> 0:21:31.560 way of guiding it in within a larger organism than 0:21:31.640 --> 0:21:35.280 you could end up using that to either administer medicine 0:21:35.400 --> 0:21:39.200 or do even you know, think about cellular level surgery, 0:21:40.080 --> 0:21:42.639 you know, I mean talking about surgery on the cellular 0:21:42.720 --> 0:21:47.520 level where you're actually repairing injured or damaged or or 0:21:47.640 --> 0:21:53.040 diseased tissue with something that has a level of precision 0:21:53.160 --> 0:21:56.840 far greater than even the sharpest scalpel. So that's a 0:21:56.920 --> 0:22:00.320 potential use for it. Whether we actually ever see at 0:22:00.680 --> 0:22:03.159 I don't know. I'm a I'm a little skeptical. It 0:22:03.200 --> 0:22:05.919 sounds like it's a little science fiction e to me. 0:22:06.040 --> 0:22:09.720 But then I'm sure if we had talked to people, 0:22:10.280 --> 0:22:12.600 you know, fifty years ago, they would say that the 0:22:12.600 --> 0:22:15.720 stuff that we take for granted now is the stuff 0:22:15.760 --> 0:22:18.240 of science fiction. It would never come to pass the Internet, 0:22:18.440 --> 0:22:20.480 the Internet, having the Internet in your in your hand, 0:22:20.880 --> 0:22:23.320 having things like tell Us surgery. I mean, we already 0:22:23.359 --> 0:22:26.960 have tell usurgery where people can can perform surgeries from 0:22:27.000 --> 0:22:30.680 across the world. Well, it seems clear that if there 0:22:30.720 --> 0:22:34.240 ever will be a bacterial robot, it's a long way off. 0:22:34.720 --> 0:22:37.960 But another thing that seemed possible to me is a 0:22:38.080 --> 0:22:41.399 use for a bacterial robot is um So how do 0:22:41.480 --> 0:22:45.320 you get your other bacterial machines to do their job. 0:22:45.600 --> 0:22:48.240 I mean, if we have like microfluidic machines that are 0:22:48.240 --> 0:22:52.720 controlled by bacteria, it could be useful to have autonomous 0:22:52.760 --> 0:22:57.160 bacterial machines that know what they're doing via the computing power. Yeah. 0:22:57.680 --> 0:22:59.520 I would imagine you would mostly have to have some 0:22:59.560 --> 0:23:03.200 bacteria owen sentives in there, like some bacterial coffee, uh, 0:23:03.320 --> 0:23:07.159 like a good bacterial life work balance, you know, some 0:23:07.320 --> 0:23:10.640 maybe you could work from outside the organism three days 0:23:10.680 --> 0:23:14.160 all the week, a bacterial vacation plan. Yeah, yeah, every 0:23:14.160 --> 0:23:18.640 now and then your holidays in Jonathan Strickland's lower intestine. Yeah, well, 0:23:18.760 --> 0:23:22.600 boy do they But to seriously answer your question, that's 0:23:22.640 --> 0:23:25.280 that's a good that's an excellent question. And honestly, it's 0:23:25.280 --> 0:23:28.480 one of those things where again, like I can kind 0:23:28.520 --> 0:23:30.880