WEBVTT 00:00:00.340 --> 00:00:02.381 So, I have a strange career. 00:00:02.405 --> 00:00:05.521 I know it because people come up to me, like colleagues, and say, 00:00:05.545 --> 00:00:07.411 "Chris, you have a strange career." NOTE Paragraph 00:00:07.435 --> 00:00:09.078 (Laughter) NOTE Paragraph 00:00:09.102 --> 00:00:10.421 And I can see their point, 00:00:10.445 --> 00:00:14.976 because I started my career as a theoretical nuclear physicist. 00:00:15.000 --> 00:00:19.164 And I was thinking about quarks and gluons and heavy ion collisions, 00:00:19.188 --> 00:00:20.976 and I was only 14 years old -- 00:00:21.593 --> 00:00:24.280 No, no, I wasn't 14 years old. 00:00:25.237 --> 00:00:26.976 But after that, 00:00:27.796 --> 00:00:29.737 I actually had my own lab 00:00:29.761 --> 00:00:31.876 in the Computational Neuroscience department, 00:00:31.900 --> 00:00:33.628 and I wasn't doing any neuroscience. 00:00:33.652 --> 00:00:36.584 Later, I would work on evolutionary genetics, 00:00:36.608 --> 00:00:38.558 and I would work on systems biology. NOTE Paragraph 00:00:38.582 --> 00:00:41.247 But I'm going to tell you about something else today. 00:00:41.271 --> 00:00:45.533 I'm going to tell you about how I learned something about life. 00:00:45.557 --> 00:00:49.038 And I was actually a rocket scientist. 00:00:49.062 --> 00:00:51.365 I wasn't really a rocket scientist, 00:00:51.389 --> 00:00:55.745 but I was working at the Jet Propulsion Laboratory 00:00:55.769 --> 00:00:58.404 in sunny California, where it's warm; 00:00:58.428 --> 00:01:02.276 whereas now I am in the mid-West, and it's cold. 00:01:02.300 --> 00:01:04.976 But it was an exciting experience. 00:01:05.000 --> 00:01:08.443 One day, a NASA manager comes into my office, 00:01:08.467 --> 00:01:10.976 sits down and says, 00:01:11.602 --> 00:01:15.403 "Can you please tell us, how do we look for life outside Earth?" 00:01:16.361 --> 00:01:18.039 And that came as a surprise to me, 00:01:18.063 --> 00:01:21.697 because I was actually hired to work on quantum computation. 00:01:22.213 --> 00:01:23.714 Yet, I had a very good answer. 00:01:23.738 --> 00:01:25.164 I said, "I have no idea." NOTE Paragraph 00:01:25.539 --> 00:01:26.689 (Laughter) NOTE Paragraph 00:01:26.713 --> 00:01:32.055 And he told me, "Biosignatures, we need to look for a biosignature." 00:01:32.079 --> 00:01:33.443 And I said, "What is that?" 00:01:33.467 --> 00:01:36.064 And he said, "It's any measurable phenomenon 00:01:36.088 --> 00:01:38.933 that allows us to indicate the presence of life." 00:01:39.528 --> 00:01:40.678 And I said, "Really? 00:01:41.173 --> 00:01:43.120 Because isn't that easy? 00:01:43.144 --> 00:01:44.975 I mean, we have life. 00:01:44.999 --> 00:01:46.971 Can't you apply a definition, 00:01:46.995 --> 00:01:51.169 for example, a Supreme Court-like definition of life?" NOTE Paragraph 00:01:51.931 --> 00:01:54.473 And then I thought about it a little bit, and I said, 00:01:54.497 --> 00:01:55.972 "Well, is it really that easy? 00:01:55.996 --> 00:01:58.189 Because, yes, if you see something like this, 00:01:58.213 --> 00:02:00.557 then all right, fine, I'm going to call it life -- 00:02:00.581 --> 00:02:01.731 no doubt about it. 00:02:02.257 --> 00:02:03.897 But here's something." 00:02:03.921 --> 00:02:06.976 And he goes, "Right, that's life too. I know that." 00:02:07.000 --> 00:02:11.592 Except, if you think that life is also defined by things that die, 00:02:11.616 --> 00:02:13.369 you're not in luck with this thing, 00:02:13.393 --> 00:02:15.655 because that's actually a very strange organism. 00:02:15.679 --> 00:02:17.726 It grows up into the adult stage like that 00:02:17.750 --> 00:02:19.976 and then goes through a Benjamin Button phase, 00:02:20.000 --> 00:02:24.935 and actually goes backwards and backwards until it's like a little embryo again, 00:02:24.959 --> 00:02:27.873 and then actually grows back up, and back down and back up -- 00:02:27.897 --> 00:02:29.676 sort of yo-yo -- and it never dies. 00:02:29.700 --> 00:02:31.926 So it's actually life, 00:02:31.950 --> 00:02:35.975 but it's actually not as we thought life would be. 00:02:36.491 --> 00:02:38.402 And then you see something like that. 00:02:38.426 --> 00:02:41.299 And he was like, "My God, what kind of a life form is that?" 00:02:41.323 --> 00:02:42.742 Anyone know? 00:02:42.766 --> 00:02:45.768 It's actually not life, it's a crystal. NOTE Paragraph 00:02:46.282 --> 00:02:49.583 So once you start looking and looking at smaller and smaller things -- 00:02:49.607 --> 00:02:52.769 so this particular person wrote a whole article and said, 00:02:52.793 --> 00:02:54.274 "Hey, these are bacteria." 00:02:54.298 --> 00:02:56.269 Except, if you look a little bit closer, 00:02:56.293 --> 00:02:59.929 you see, in fact, that this thing is way too small to be anything like that. 00:02:59.953 --> 00:03:03.111 So he was convinced, but, in fact, most people aren't. 00:03:03.792 --> 00:03:06.976 And then, of course, NASA also had a big announcement, 00:03:07.000 --> 00:03:09.865 and President Clinton gave a press conference, 00:03:09.889 --> 00:03:14.750 about this amazing discovery of life in a Martian meteorite. 00:03:15.400 --> 00:03:18.361 Except that nowadays, it's heavily disputed. 00:03:18.806 --> 00:03:21.241 If you take the lesson of all these pictures, 00:03:21.265 --> 00:03:24.159 then you realize, well, actually, maybe it's not that easy. 00:03:24.183 --> 00:03:27.582 Maybe I do need a definition of life 00:03:27.606 --> 00:03:29.884 in order to make that kind of distinction. NOTE Paragraph 00:03:29.908 --> 00:03:32.439 So can life be defined? 00:03:32.463 --> 00:03:33.970 Well how would you go about it? 00:03:33.994 --> 00:03:38.001 Well of course, you'd go to Encyclopedia Britannica and open at L. 00:03:38.025 --> 00:03:41.037 No, of course you don't do that; you put it somewhere in Google. 00:03:41.061 --> 00:03:42.652 And then you might get something. NOTE Paragraph 00:03:42.676 --> 00:03:43.700 (Laughter) NOTE Paragraph 00:03:43.724 --> 00:03:44.942 And what you might get -- 00:03:44.966 --> 00:03:48.745 and anything that actually refers to things that we are used to, 00:03:48.769 --> 00:03:49.991 you throw away. 00:03:50.015 --> 00:03:52.513 And then you might come up with something like this. 00:03:52.537 --> 00:03:55.794 And it says something complicated with lots and lots of concepts. 00:03:55.818 --> 00:04:01.178 Who on Earth would write something as convoluted and complex and inane? 00:04:02.952 --> 00:04:06.853 Oh, it's actually a really, really, important set of concepts. 00:04:06.877 --> 00:04:08.976 So I'm highlighting just a few words 00:04:09.000 --> 00:04:12.924 and saying definitions like that rely on things 00:04:12.948 --> 00:04:19.097 that are not based on amino acids or leaves or anything that we are used to, 00:04:19.121 --> 00:04:20.872 but in fact on processes only. 00:04:20.896 --> 00:04:22.767 And if you take a look at that, 00:04:22.791 --> 00:04:26.248 this was actually in a book that I wrote that deals with artificial life. 00:04:26.272 --> 00:04:30.499 And that explains why that NASA manager was actually in my office to begin with. 00:04:30.523 --> 00:04:33.610 Because the idea was that, with concepts like that, 00:04:33.634 --> 00:04:37.654 maybe we can actually manufacture a form of life. NOTE Paragraph 00:04:37.678 --> 00:04:42.475 And so if you go and ask yourself, "What on Earth is artificial life?", 00:04:42.499 --> 00:04:46.168 let me give you a whirlwind tour of how all this stuff came about. 00:04:46.192 --> 00:04:49.327 And it started out quite a while ago, 00:04:49.351 --> 00:04:53.676 when someone wrote one of the first successful computer viruses. 00:04:53.985 --> 00:04:56.158 And for those of you who aren't old enough, 00:04:56.182 --> 00:04:58.765 you have no idea how this infection was working -- 00:04:58.789 --> 00:05:01.049 namely, through these floppy disks. 00:05:01.073 --> 00:05:04.960 But the interesting thing about these computer virus infections 00:05:04.984 --> 00:05:08.436 was that, if you look at the rate at which the infection worked, 00:05:08.460 --> 00:05:12.610 they show this spiky behavior that you're used to from a flu virus. 00:05:12.634 --> 00:05:14.976 And it is in fact due to this arms race 00:05:15.000 --> 00:05:18.456 between hackers and operating system designers 00:05:18.480 --> 00:05:20.080 that things go back and forth. 00:05:20.104 --> 00:05:24.615 And the result is kind of a tree of life of these viruses, 00:05:24.639 --> 00:05:28.244 a phylogeny that looks very much like the type of life 00:05:28.268 --> 00:05:30.697 that we're used to, at least on the viral level. NOTE Paragraph 00:05:30.721 --> 00:05:32.051 So is that life? 00:05:32.266 --> 00:05:33.882 Not as far as I'm concerned. 00:05:33.906 --> 00:05:36.748 Why? Because these things don't evolve by themselves. 00:05:36.772 --> 00:05:38.725 In fact, they have hackers writing them. 00:05:38.749 --> 00:05:42.079 But the idea was taken very quickly a little bit further, 00:05:42.103 --> 00:05:45.414 when a scientist working at the Santa Fe Institute decided, 00:05:45.438 --> 00:05:48.571 "Why don't we try to package these little viruses 00:05:48.595 --> 00:05:50.810 in artificial worlds inside of the computer 00:05:50.834 --> 00:05:52.105 and let them evolve?" 00:05:52.129 --> 00:05:53.723 And this was Steen Rasmussen. 00:05:53.747 --> 00:05:56.439 And he designed this system, but it really didn't work, 00:05:56.463 --> 00:05:59.347 because his viruses were constantly destroying each other. 00:05:59.371 --> 00:06:02.888 But there was another scientist who had been watching this, an ecologist. 00:06:02.912 --> 00:06:05.404 And he went home and says, "I know how to fix this." 00:06:05.428 --> 00:06:07.072 And he wrote the Tierra system, 00:06:07.096 --> 00:06:08.301 and, in my book, 00:06:08.325 --> 00:06:12.149 is in fact one of the first truly artificial living systems -- 00:06:12.173 --> 00:06:15.635 except for the fact that these programs didn't really grow in complexity. NOTE Paragraph 00:06:15.659 --> 00:06:18.523 So having seen this work, worked a little bit on this, 00:06:18.547 --> 00:06:20.205 this is where I came in. 00:06:20.229 --> 00:06:23.872 And I decided to create a system that has all the properties 00:06:23.896 --> 00:06:27.742 that are necessary to see, in fact, the evolution of complexity, 00:06:27.766 --> 00:06:31.068 more and more complex problems constantly evolving. 00:06:31.092 --> 00:06:34.876 And of course, since I really don't know how to write code, I had help in this. 00:06:34.900 --> 00:06:36.448 I had two undergraduate students 00:06:36.472 --> 00:06:39.201 at California Institute of Technology that worked with me. 00:06:39.225 --> 00:06:42.077 That's Charles Ofria on the left, Titus Brown on the right. 00:06:42.101 --> 00:06:44.436 They are now, actually, respectable professors 00:06:44.460 --> 00:06:46.202 at Michigan State University, 00:06:46.226 --> 00:06:50.727 but I can assure you, back in the day, we were not a respectable team. 00:06:50.751 --> 00:06:52.800 And I'm really happy that no photo survives 00:06:52.824 --> 00:06:55.347 of the three of us anywhere close together. NOTE Paragraph 00:06:56.092 --> 00:06:57.967 But what is this system like? 00:06:57.991 --> 00:07:00.180 Well I can't really go into the details, 00:07:00.204 --> 00:07:02.857 but what you see here is some of the entrails. 00:07:02.881 --> 00:07:06.966 But what I wanted to focus on is this type of population structure. 00:07:06.990 --> 00:07:09.462 There's about 10,000 programs sitting here. 00:07:09.486 --> 00:07:12.405 And all different strains are colored in different colors. 00:07:12.429 --> 00:07:16.033 And as you see here, there are groups that are growing on top of each other, 00:07:16.057 --> 00:07:17.398 because they are spreading. 00:07:17.422 --> 00:07:21.526 Any time there is a program that's better at surviving in this world, 00:07:21.550 --> 00:07:23.518 due to whatever mutation it has acquired, 00:07:23.542 --> 00:07:27.012 it is going to spread over the others and drive the others to extinction. NOTE Paragraph 00:07:27.036 --> 00:07:28.591 So I'm going to show you a movie 00:07:28.615 --> 00:07:30.842 where you're going to see that kind of dynamic. 00:07:30.866 --> 00:07:35.142 And these kinds of experiments are started with programs that we wrote ourselves. 00:07:35.166 --> 00:07:38.503 We write our own stuff, replicate it, and are very proud of ourselves. 00:07:38.527 --> 00:07:41.303 And we put them in, and what you see immediately 00:07:41.327 --> 00:07:44.393 is that there are waves and waves of innovation. 00:07:44.417 --> 00:07:46.311 By the way, this is highly accelerated, 00:07:46.335 --> 00:07:48.532 so it's like a 1000 generations a second. 00:07:48.556 --> 00:07:52.523 But immediately, the system goes like, "What kind of dumb piece of code was this? 00:07:52.547 --> 00:07:56.268 This can be improved upon in so many ways, so quickly." 00:07:56.292 --> 00:08:00.040 So you see waves of new types taking over the other types. 00:08:00.064 --> 00:08:02.626 And this type of activity goes on for quite a while, 00:08:02.650 --> 00:08:07.471 until the main easy things have been acquired by these programs. 00:08:07.495 --> 00:08:10.976 And then, you see sort of like a stasis coming on 00:08:11.000 --> 00:08:12.976 where the system essentially waits 00:08:13.000 --> 00:08:16.183 for a new type of innovation, like this one, 00:08:16.207 --> 00:08:20.489 which is going to spread over all the other innovations that were before 00:08:20.513 --> 00:08:22.976 and is erasing the genes that it had before, 00:08:23.000 --> 00:08:26.976 until a new type of higher level of complexity has been achieved. 00:08:27.000 --> 00:08:29.976 And this process goes on and on and on. NOTE Paragraph 00:08:30.467 --> 00:08:31.782 So what we see here 00:08:31.806 --> 00:08:35.969 is a system that lives in very much the way we're used to how life goes. 00:08:36.688 --> 00:08:40.808 But what the NASA people had asked me really was, 00:08:41.213 --> 00:08:43.975 "Do these guys have a biosignature? 00:08:44.580 --> 00:08:46.393 Can we measure this type of life? 00:08:46.417 --> 00:08:47.609 Because if we can, 00:08:47.633 --> 00:08:51.482 maybe we have a chance of actually discovering life somewhere else 00:08:51.506 --> 00:08:54.660 without being biased by things like amino acids." 00:08:55.221 --> 00:08:59.754 So I said, "Well, perhaps we should construct a biosignature 00:08:59.778 --> 00:09:02.976 based on life as a universal process. 00:09:03.000 --> 00:09:07.864 In fact, it should perhaps make use of the concepts that I developed 00:09:07.888 --> 00:09:11.975 just in order to sort of capture what a simple living system might be." NOTE Paragraph 00:09:11.999 --> 00:09:13.518 And the thing I came up with -- 00:09:13.542 --> 00:09:17.524 I have to first give you an introduction about the idea, 00:09:17.548 --> 00:09:21.087 and maybe that would be a meaning detector, 00:09:21.111 --> 00:09:22.658 rather than a life detector. 00:09:23.226 --> 00:09:24.976 And the way we would do that -- 00:09:25.000 --> 00:09:27.636 I would like to find out how I can distinguish text 00:09:27.660 --> 00:09:32.307 that was written by a million monkeys, as opposed to text that is in our books. 00:09:32.645 --> 00:09:34.522 And I would like to do it in such a way 00:09:34.546 --> 00:09:37.424 that I don't actually have to be able to read the language, 00:09:37.448 --> 00:09:39.218 because I'm sure I won't be able to. 00:09:39.242 --> 00:09:41.742 As long as I know that there's some sort of alphabet. 00:09:41.766 --> 00:09:44.096 So here would be a frequency plot 00:09:44.120 --> 00:09:47.502 of how often you find each of the 26 letters of the alphabet 00:09:47.526 --> 00:09:49.745 in a text written by random monkeys. 00:09:50.195 --> 00:09:54.749 And obviously, each of these letters comes off about roughly equally frequent. NOTE Paragraph 00:09:54.773 --> 00:09:58.365 But if you now look at the same distribution in English texts, 00:09:58.389 --> 00:09:59.637 it looks like that. 00:10:00.202 --> 00:10:03.750 And I'm telling you, this is very robust across English texts. 00:10:03.774 --> 00:10:06.758 And if I look at French texts, it looks a little bit different, 00:10:06.782 --> 00:10:07.960 or Italian or German. 00:10:07.984 --> 00:10:11.400 They all have their own type of frequency distribution, 00:10:11.424 --> 00:10:12.857 but it's robust. 00:10:12.881 --> 00:10:16.088 It doesn't matter whether it writes about politics or about science. 00:10:16.112 --> 00:10:21.892 It doesn't matter whether it's a poem or whether it's a mathematical text. 00:10:21.916 --> 00:10:23.753 It's a robust signature, 00:10:23.777 --> 00:10:25.597 and it's very stable. 00:10:25.621 --> 00:10:27.778 As long as our books are written in English -- 00:10:27.802 --> 00:10:30.593 because people are rewriting them and recopying them -- 00:10:30.617 --> 00:10:31.976 it's going to be there. NOTE Paragraph 00:10:32.000 --> 00:10:37.761 So that inspired me to think about, well, what if I try to use this idea 00:10:37.785 --> 00:10:41.540 in order, not to detect random texts from texts with meaning, 00:10:41.564 --> 00:10:45.293 but rather detect the fact that there is meaning 00:10:45.317 --> 00:10:47.844 in the biomolecules that make up life. 00:10:47.868 --> 00:10:49.036 But first I have to ask: 00:10:49.060 --> 00:10:50.548 what are these building blocks, 00:10:50.572 --> 00:10:52.868 like the alphabet, elements that I showed you? 00:10:52.892 --> 00:10:55.765 Well it turns out, we have many different alternatives 00:10:55.789 --> 00:10:58.103 for such a set of building blocks. 00:10:58.127 --> 00:10:59.375 We could use amino acids, 00:10:59.399 --> 00:11:02.601 we could use nucleic acids, carboxylic acids, fatty acids. 00:11:02.625 --> 00:11:06.063 In fact, chemistry's extremely rich, and our body uses a lot of them. NOTE Paragraph 00:11:06.087 --> 00:11:08.393 So that we actually, to test this idea, 00:11:08.417 --> 00:11:11.964 first took a look at amino acids and some other carboxylic acids. 00:11:11.988 --> 00:11:13.459 And here's the result. 00:11:13.483 --> 00:11:16.649 Here is, in fact, what you get 00:11:16.673 --> 00:11:19.696 if you, for example, look at the distribution of amino acids 00:11:19.720 --> 00:11:24.455 on a comet or in interstellar space or, in fact, in a laboratory, 00:11:24.479 --> 00:11:27.138 where you made very sure that in your primordial soup, 00:11:27.162 --> 00:11:29.080 there is no living stuff in there. 00:11:29.104 --> 00:11:31.983 What you find is mostly glycine and then alanine 00:11:32.007 --> 00:11:34.366 and there's some trace elements of the other ones. 00:11:34.390 --> 00:11:36.819 That is also very robust -- 00:11:36.843 --> 00:11:40.675 what you find in systems like Earth 00:11:40.699 --> 00:11:43.844 where there are amino acids, but there is no life. NOTE Paragraph 00:11:43.868 --> 00:11:48.498 But suppose you take some dirt and dig through it 00:11:48.522 --> 00:11:51.482 and then put it into these spectrometers, 00:11:51.506 --> 00:11:53.604 because there's bacteria all over the place; 00:11:53.628 --> 00:11:55.859 or you take water anywhere on Earth, 00:11:55.883 --> 00:11:57.400 because it's teaming with life, 00:11:57.424 --> 00:11:59.174 and you make the same analysis; 00:11:59.198 --> 00:12:01.775 the spectrum looks completely different. 00:12:01.799 --> 00:12:05.174 Of course, there is still glycine and alanine, 00:12:05.198 --> 00:12:08.518 but in fact, there are these heavy elements, these heavy amino acids, 00:12:08.542 --> 00:12:11.937 that are being produced because they are valuable to the organism. 00:12:13.067 --> 00:12:17.005 And some other ones that are not used in the set of 20, 00:12:17.029 --> 00:12:19.927 they will not appear at all in any type of concentration. 00:12:19.951 --> 00:12:22.656 So this also turns out to be extremely robust. 00:12:22.680 --> 00:12:25.798 It doesn't matter what kind of sediment you're using to grind up, 00:12:25.822 --> 00:12:29.101 whether it's bacteria or any other plants or animals. 00:12:29.125 --> 00:12:30.549 Anywhere there's life, 00:12:30.573 --> 00:12:32.524 you're going to have this distribution, 00:12:32.548 --> 00:12:34.365 as opposed to that distribution. 00:12:34.389 --> 00:12:37.626 And it is detectable not just in amino acids. NOTE Paragraph 00:12:37.650 --> 00:12:38.867 Now you could ask: 00:12:38.891 --> 00:12:42.050 Well, what about these Avidians? 00:12:42.074 --> 00:12:45.125 The Avidians being the denizens of this computer world 00:12:45.149 --> 00:12:48.594 where they are perfectly happy replicating and growing in complexity. 00:12:48.618 --> 00:12:53.635 So this is the distribution that you get if, in fact, there is no life. 00:12:53.659 --> 00:12:56.377 They have about 28 of these instructions. 00:12:56.401 --> 00:12:59.753 And if you have a system where they're being replaced one by the other, 00:12:59.777 --> 00:13:01.962 it's like the monkeys writing on a typewriter. 00:13:01.986 --> 00:13:06.206 Each of these instructions appears with roughly the equal frequency. 00:13:07.115 --> 00:13:11.895 But if you now take a set of replicating guys 00:13:11.919 --> 00:13:13.869 like in the video that you saw, 00:13:13.893 --> 00:13:15.412 it looks like this. 00:13:16.199 --> 00:13:17.672 So there are some instructions 00:13:17.696 --> 00:13:20.129 that are extremely valuable to these organisms, 00:13:20.153 --> 00:13:22.123 and their frequency is going to be high. 00:13:22.147 --> 00:13:26.188 And there's actually some instructions that you only use once, if ever. 00:13:26.212 --> 00:13:27.735 So they are either poisonous 00:13:27.759 --> 00:13:32.264 or really should be used at less of a level than random. 00:13:32.288 --> 00:13:34.976 In this case, the frequency is lower. 00:13:35.932 --> 00:13:38.603 And so now we can see, is that really a robust signature? 00:13:38.627 --> 00:13:39.984 I can tell you indeed it is, 00:13:40.008 --> 00:13:43.256 because this type of spectrum, just like what you've seen in books, 00:13:43.280 --> 00:13:45.433 and just like what you've seen in amino acids, 00:13:45.457 --> 00:13:48.099 it doesn't really matter how you change the environment, 00:13:48.123 --> 00:13:50.747 it's very robust, it's going to reflect the environment. NOTE Paragraph 00:13:50.771 --> 00:13:53.720 So I'm going to show you now a little experiment that we did. 00:13:53.744 --> 00:13:55.128 And I have to explain to you, 00:13:55.152 --> 00:13:56.334 the top of this graph 00:13:56.358 --> 00:13:59.102 shows you that frequency distribution that I talked about. 00:13:59.126 --> 00:14:02.933 Here, that's the lifeless environment 00:14:02.957 --> 00:14:06.369 where each instruction occurs at an equal frequency. 00:14:07.304 --> 00:14:12.297 And below there, I show, in fact, the mutation rate in the environment. 00:14:12.321 --> 00:14:15.624 And I'm starting this at a mutation rate that is so high 00:14:15.648 --> 00:14:19.614 that even if you would drop a replicating program 00:14:19.638 --> 00:14:23.763 that would otherwise happily grow up to fill the entire world, 00:14:23.787 --> 00:14:26.797 if you drop it in, it gets mutated to death immediately. 00:14:26.821 --> 00:14:32.167 So there is no life possible at that type of mutation rate. 00:14:32.191 --> 00:14:36.227 But then I'm going to slowly turn down the heat, so to speak, 00:14:36.251 --> 00:14:38.436 and then there's this viability threshold 00:14:38.460 --> 00:14:42.352 where now it would be possible for a replicator to actually live. 00:14:42.376 --> 00:14:47.721 And indeed, we're going to be dropping these guys into that soup all the time. NOTE Paragraph 00:14:48.159 --> 00:14:49.795 So let's see what that looks like. 00:14:49.819 --> 00:14:52.817 So first, nothing, nothing, nothing. 00:14:52.841 --> 00:14:54.656 Too hot, too hot. 00:14:54.680 --> 00:14:56.976 Now the viability threshold is reached, 00:14:57.000 --> 00:15:01.492 and the frequency distribution has dramatically changed 00:15:01.516 --> 00:15:02.992 and, in fact, stabilizes. 00:15:03.016 --> 00:15:04.526 And now what I did there 00:15:04.550 --> 00:15:08.148 is, I was being nasty, I just turned up the heat again and again. 00:15:08.172 --> 00:15:10.518 And of course, it reaches the viability threshold. 00:15:10.542 --> 00:15:13.410 And I'm just showing this to you again because it's so nice. 00:15:13.434 --> 00:15:14.976 You hit the viability threshold. 00:15:15.000 --> 00:15:16.976 The distribution changes to "alive!" 00:15:17.431 --> 00:15:20.648 And then, once you hit the threshold 00:15:20.672 --> 00:15:24.721 where the mutation rate is so high that you cannot self-reproduce, 00:15:24.745 --> 00:15:29.666 you cannot copy the information forward to your offspring 00:15:29.690 --> 00:15:34.420 without making so many mistakes that your ability to replicate vanishes. 00:15:34.444 --> 00:15:36.303 And then, that signature is lost. NOTE Paragraph 00:15:37.956 --> 00:15:39.662 What do we learn from that? 00:15:39.686 --> 00:15:43.482 Well, I think we learn a number of things from that. 00:15:43.506 --> 00:15:44.976 One of them is, 00:15:45.000 --> 00:15:50.224 if we are able to think about life in abstract terms -- 00:15:50.248 --> 00:15:52.879 and we're not talking about things like plants, 00:15:52.903 --> 00:15:54.828 and we're not talking about amino acids, 00:15:54.852 --> 00:15:56.616 and we're not talking about bacteria, 00:15:56.640 --> 00:15:58.750 but we think in terms of processes -- 00:15:58.774 --> 00:16:00.976 then we could start to think about life 00:16:01.000 --> 00:16:03.619 not as something that is so special to Earth, 00:16:03.643 --> 00:16:06.153 but that, in fact, could exist anywhere. 00:16:06.177 --> 00:16:10.490 Because it really only has to do with these concepts of information, 00:16:10.514 --> 00:16:14.572 of storing information within physical substrates -- 00:16:14.596 --> 00:16:18.612 anything: bits, nucleic acids, anything that's an alphabet -- 00:16:18.636 --> 00:16:20.515 and make sure that there's some process 00:16:20.539 --> 00:16:24.254 so that this information can be stored for much longer than you would expect -- 00:16:24.816 --> 00:16:29.152 the time scales for the deterioration of information. 00:16:29.176 --> 00:16:32.344 And if you can do that, then you have life. NOTE Paragraph 00:16:32.368 --> 00:16:34.622 So the first thing that we learn 00:16:34.646 --> 00:16:39.858 is that it is possible to define life in terms of processes alone, 00:16:39.882 --> 00:16:44.859 without referring at all to the type of things that we hold dear, 00:16:44.883 --> 00:16:47.554 as far as the type of life on Earth is. 00:16:47.578 --> 00:16:50.219 And that, in a sense, removes us again, 00:16:50.243 --> 00:16:53.074 like all of our scientific discoveries, or many of them -- 00:16:53.098 --> 00:16:55.869 it's this continuous dethroning of man -- 00:16:55.893 --> 00:16:58.620 of how we think we're special because we're alive. 00:16:58.644 --> 00:17:01.700 Well, we can make life; we can make life in the computer. 00:17:01.724 --> 00:17:03.541 Granted, it's limited, 00:17:03.565 --> 00:17:08.682 but we have learned what it takes in order to actually construct it. 00:17:08.706 --> 00:17:11.494 And once we have that, 00:17:11.518 --> 00:17:14.165 then it is not such a difficult task anymore 00:17:14.189 --> 00:17:18.341 to say, if we understand the fundamental processes 00:17:18.365 --> 00:17:21.707 that do not refer to any particular substrate, 00:17:21.731 --> 00:17:25.499 then we can go out and try other worlds, 00:17:25.523 --> 00:17:29.304 figure out what kind of chemical alphabets might there be, 00:17:30.033 --> 00:17:34.758 figure enough about the normal chemistry, the geochemistry of the planet, 00:17:34.782 --> 00:17:38.556 so that we know what this distribution would look like in the absence of life, 00:17:38.580 --> 00:17:41.551 and then look for large deviations from this -- 00:17:41.575 --> 00:17:46.687 this thing sticking out, which says, "This chemical really shouldn't be there." 00:17:46.711 --> 00:17:48.666 Now we don't know that there's life then, 00:17:48.690 --> 00:17:49.897 but we could say, 00:17:49.921 --> 00:17:53.690 "Well at least I'm going to have to take a look very precisely at this chemical 00:17:53.714 --> 00:17:55.759 and see where it comes from." 00:17:55.783 --> 00:17:59.494 And that might be our chance of actually discovering life 00:17:59.518 --> 00:18:01.637 when we cannot visibly see it. NOTE Paragraph 00:18:01.661 --> 00:18:06.225 And so that's really the only take-home message that I have for you. 00:18:06.249 --> 00:18:10.480 Life can be less mysterious than we make it out to be 00:18:10.504 --> 00:18:13.709 when we try to think about how it would be on other planets. 00:18:14.280 --> 00:18:17.667 And if we remove the mystery of life, 00:18:17.691 --> 00:18:22.376 then I think it is a little bit easier for us to think about how we live, 00:18:22.400 --> 00:18:25.458 and how perhaps we're not as special as we always think we are. 00:18:25.482 --> 00:18:27.728 And I'm going to leave you with that. NOTE Paragraph 00:18:27.752 --> 00:18:28.976 And thank you very much. NOTE Paragraph 00:18:29.000 --> 00:18:31.174 (Applause)