0:00:00.340,0:00:02.381 So, I have a strange career. 0:00:02.405,0:00:05.521 I know it because people come up to me,[br]like colleagues, and say, 0:00:05.545,0:00:07.411 "Chris, you have a strange career." 0:00:07.435,0:00:09.078 (Laughter) 0:00:09.102,0:00:10.421 And I can see their point, 0:00:10.445,0:00:14.976 because I started my career[br]as a theoretical nuclear physicist. 0:00:15.000,0:00:19.164 And I was thinking about quarks[br]and gluons and heavy ion collisions, 0:00:19.188,0:00:20.976 and I was only 14 years old -- 0:00:21.593,0:00:24.280 No, no, I wasn't 14 years old. 0:00:25.237,0:00:26.976 But after that, 0:00:27.796,0:00:29.737 I actually had my own lab 0:00:29.761,0:00:31.876 in the Computational[br]Neuroscience department, 0:00:31.900,0:00:33.628 and I wasn't doing any neuroscience. 0:00:33.652,0:00:36.584 Later, I would work[br]on evolutionary genetics, 0:00:36.608,0:00:38.558 and I would work on systems biology. 0:00:38.582,0:00:41.247 But I'm going to tell you[br]about something else today. 0:00:41.271,0:00:45.533 I'm going to tell you[br]about how I learned something about life. 0:00:45.557,0:00:49.038 And I was actually a rocket scientist. 0:00:49.062,0:00:51.365 I wasn't really a rocket scientist, 0:00:51.389,0:00:55.745 but I was working[br]at the Jet Propulsion Laboratory 0:00:55.769,0:00:58.404 in sunny California, where it's warm; 0:00:58.428,0:01:02.276 whereas now I am[br]in the mid-West, and it's cold. 0:01:02.300,0:01:04.976 But it was an exciting experience. 0:01:05.000,0:01:08.443 One day, a NASA manager[br]comes into my office, 0:01:08.467,0:01:10.976 sits down and says, 0:01:11.602,0:01:15.403 "Can you please tell us,[br]how do we look for life outside Earth?" 0:01:16.361,0:01:18.039 And that came as a surprise to me, 0:01:18.063,0:01:21.697 because I was actually hired[br]to work on quantum computation. 0:01:22.213,0:01:23.714 Yet, I had a very good answer. 0:01:23.738,0:01:25.164 I said, "I have no idea." 0:01:25.539,0:01:26.689 (Laughter) 0:01:26.713,0:01:32.055 And he told me, "Biosignatures,[br]we need to look for a biosignature." 0:01:32.079,0:01:33.443 And I said, "What is that?" 0:01:33.467,0:01:36.064 And he said, "It's any[br]measurable phenomenon 0:01:36.088,0:01:38.933 that allows us to indicate[br]the presence of life." 0:01:39.528,0:01:40.678 And I said, "Really? 0:01:41.173,0:01:43.120 Because isn't that easy? 0:01:43.144,0:01:44.975 I mean, we have life. 0:01:44.999,0:01:46.971 Can't you apply a definition, 0:01:46.995,0:01:51.169 for example, a Supreme Court-like[br]definition of life?" 0:01:51.931,0:01:54.473 And then I thought about it[br]a little bit, and I said, 0:01:54.497,0:01:55.972 "Well, is it really that easy? 0:01:55.996,0:01:58.189 Because, yes, if you see[br]something like this, 0:01:58.213,0:02:00.557 then all right, fine,[br]I'm going to call it life -- 0:02:00.581,0:02:01.731 no doubt about it. 0:02:02.257,0:02:03.897 But here's something." 0:02:03.921,0:02:06.976 And he goes, "Right,[br]that's life too. I know that." 0:02:07.000,0:02:11.592 Except, if you think that life[br]is also defined by things that die, 0:02:11.616,0:02:13.369 you're not in luck with this thing, 0:02:13.393,0:02:15.655 because that's actually[br]a very strange organism. 0:02:15.679,0:02:17.726 It grows up into the adult stage like that 0:02:17.750,0:02:19.976 and then goes through[br]a Benjamin Button phase, 0:02:20.000,0:02:24.935 and actually goes backwards and backwards[br]until it's like a little embryo again, 0:02:24.959,0:02:27.873 and then actually grows back up,[br]and back down and back up -- 0:02:27.897,0:02:29.676 sort of yo-yo -- and it never dies. 0:02:29.700,0:02:31.926 So it's actually life, 0:02:31.950,0:02:35.975 but it's actually not[br]as we thought life would be. 0:02:36.491,0:02:38.402 And then you see something like that. 0:02:38.426,0:02:41.299 And he was like, "My God,[br]what kind of a life form is that?" 0:02:41.323,0:02:42.742 Anyone know? 0:02:42.766,0:02:45.768 It's actually not life, it's a crystal. 0:02:46.282,0:02:49.583 So once you start looking and looking[br]at smaller and smaller things -- 0:02:49.607,0:02:52.769 so this particular person wrote[br]a whole article and said, 0:02:52.793,0:02:54.274 "Hey, these are bacteria." 0:02:54.298,0:02:56.269 Except, if you look a little bit closer, 0:02:56.293,0:02:59.929 you see, in fact, that this thing[br]is way too small to be anything like that. 0:02:59.953,0:03:03.111 So he was convinced,[br]but, in fact, most people aren't. 0:03:03.792,0:03:06.976 And then, of course,[br]NASA also had a big announcement, 0:03:07.000,0:03:09.865 and President Clinton[br]gave a press conference, 0:03:09.889,0:03:14.750 about this amazing discovery[br]of life in a Martian meteorite. 0:03:15.400,0:03:18.361 Except that nowadays,[br]it's heavily disputed. 0:03:18.806,0:03:21.241 If you take the lesson[br]of all these pictures, 0:03:21.265,0:03:24.159 then you realize, well, actually,[br]maybe it's not that easy. 0:03:24.183,0:03:27.582 Maybe I do need a definition of life 0:03:27.606,0:03:29.884 in order to make that kind of distinction. 0:03:29.908,0:03:32.439 So can life be defined? 0:03:32.463,0:03:33.970 Well how would you go about it? 0:03:33.994,0:03:38.001 Well of course, you'd go[br]to Encyclopedia Britannica and open at L. 0:03:38.025,0:03:41.037 No, of course you don't do that;[br]you put it somewhere in Google. 0:03:41.061,0:03:42.652 And then you might get something. 0:03:42.676,0:03:43.700 (Laughter) 0:03:43.724,0:03:44.942 And what you might get -- 0:03:44.966,0:03:48.745 and anything that actually refers[br]to things that we are used to, 0:03:48.769,0:03:49.991 you throw away. 0:03:50.015,0:03:52.513 And then you might come up[br]with something like this. 0:03:52.537,0:03:55.794 And it says something complicated[br]with lots and lots of concepts. 0:03:55.818,0:04:01.178 Who on Earth would write something[br]as convoluted and complex and inane? 0:04:02.952,0:04:06.853 Oh, it's actually a really, really,[br]important set of concepts. 0:04:06.877,0:04:08.976 So I'm highlighting just a few words 0:04:09.000,0:04:12.924 and saying definitions[br]like that rely on things 0:04:12.948,0:04:19.097 that are not based on amino acids[br]or leaves or anything that we are used to, 0:04:19.121,0:04:20.872 but in fact on processes only. 0:04:20.896,0:04:22.767 And if you take a look at that, 0:04:22.791,0:04:26.248 this was actually in a book that I wrote[br]that deals with artificial life. 0:04:26.272,0:04:30.499 And that explains why that NASA manager[br]was actually in my office to begin with. 0:04:30.523,0:04:33.610 Because the idea was that,[br]with concepts like that, 0:04:33.634,0:04:37.654 maybe we can actually[br]manufacture a form of life. 0:04:37.678,0:04:42.475 And so if you go and ask yourself,[br]"What on Earth is artificial life?", 0:04:42.499,0:04:46.168 let me give you a whirlwind tour[br]of how all this stuff came about. 0:04:46.192,0:04:49.327 And it started out quite a while ago, 0:04:49.351,0:04:53.676 when someone wrote one of the first[br]successful computer viruses. 0:04:53.985,0:04:56.158 And for those of you[br]who aren't old enough, 0:04:56.182,0:04:58.765 you have no idea[br]how this infection was working -- 0:04:58.789,0:05:01.049 namely, through these floppy disks. 0:05:01.073,0:05:04.960 But the interesting thing[br]about these computer virus infections 0:05:04.984,0:05:08.436 was that, if you look at the rate[br]at which the infection worked, 0:05:08.460,0:05:12.610 they show this spiky behavior[br]that you're used to from a flu virus. 0:05:12.634,0:05:14.976 And it is in fact due to this arms race 0:05:15.000,0:05:18.456 between hackers[br]and operating system designers 0:05:18.480,0:05:20.080 that things go back and forth. 0:05:20.104,0:05:24.615 And the result is kind of[br]a tree of life of these viruses, 0:05:24.639,0:05:28.244 a phylogeny that looks very much[br]like the type of life 0:05:28.268,0:05:30.697 that we're used to,[br]at least on the viral level. 0:05:30.721,0:05:32.051 So is that life? 0:05:32.266,0:05:33.882 Not as far as I'm concerned. 0:05:33.906,0:05:36.748 Why? Because these things[br]don't evolve by themselves. 0:05:36.772,0:05:38.725 In fact, they have hackers writing them. 0:05:38.749,0:05:42.079 But the idea was taken[br]very quickly a little bit further, 0:05:42.103,0:05:45.414 when a scientist working[br]at the Santa Fe Institute decided, 0:05:45.438,0:05:48.571 "Why don't we try to package[br]these little viruses 0:05:48.595,0:05:50.810 in artificial worlds[br]inside of the computer 0:05:50.834,0:05:52.105 and let them evolve?" 0:05:52.129,0:05:53.723 And this was Steen Rasmussen. 0:05:53.747,0:05:56.439 And he designed this system,[br]but it really didn't work, 0:05:56.463,0:05:59.347 because his viruses[br]were constantly destroying each other. 0:05:59.371,0:06:02.888 But there was another scientist[br]who had been watching this, an ecologist. 0:06:02.912,0:06:05.404 And he went home and says,[br]"I know how to fix this." 0:06:05.428,0:06:07.072 And he wrote the Tierra system, 0:06:07.096,0:06:08.301 and, in my book, 0:06:08.325,0:06:12.149 is in fact one of the first[br]truly artificial living systems -- 0:06:12.173,0:06:15.635 except for the fact that these programs[br]didn't really grow in complexity. 0:06:15.659,0:06:18.523 So having seen this work,[br]worked a little bit on this, 0:06:18.547,0:06:20.205 this is where I came in. 0:06:20.229,0:06:23.872 And I decided to create a system[br]that has all the properties 0:06:23.896,0:06:27.742 that are necessary to see, in fact,[br]the evolution of complexity, 0:06:27.766,0:06:31.068 more and more complex[br]problems constantly evolving. 0:06:31.092,0:06:34.876 And of course, since I really don't know[br]how to write code, I had help in this. 0:06:34.900,0:06:36.448 I had two undergraduate students 0:06:36.472,0:06:39.201 at California Institute of Technology[br]that worked with me. 0:06:39.225,0:06:42.077 That's Charles Ofria on the left,[br]Titus Brown on the right. 0:06:42.101,0:06:44.436 They are now, actually,[br]respectable professors 0:06:44.460,0:06:46.202 at Michigan State University, 0:06:46.226,0:06:50.727 but I can assure you, back in the day,[br]we were not a respectable team. 0:06:50.751,0:06:52.800 And I'm really happy[br]that no photo survives 0:06:52.824,0:06:55.347 of the three of us[br]anywhere close together. 0:06:56.092,0:06:57.967 But what is this system like? 0:06:57.991,0:07:00.180 Well I can't really go into the details, 0:07:00.204,0:07:02.857 but what you see here[br]is some of the entrails. 0:07:02.881,0:07:06.966 But what I wanted to focus on[br]is this type of population structure. 0:07:06.990,0:07:09.462 There's about 10,000[br]programs sitting here. 0:07:09.486,0:07:12.405 And all different strains[br]are colored in different colors. 0:07:12.429,0:07:16.033 And as you see here, there are groups[br]that are growing on top of each other, 0:07:16.057,0:07:17.398 because they are spreading. 0:07:17.422,0:07:21.526 Any time there is a program[br]that's better at surviving in this world, 0:07:21.550,0:07:23.518 due to whatever mutation it has acquired, 0:07:23.542,0:07:27.012 it is going to spread over the others[br]and drive the others to extinction. 0:07:27.036,0:07:28.591 So I'm going to show you a movie 0:07:28.615,0:07:30.842 where you're going to see[br]that kind of dynamic. 0:07:30.866,0:07:35.142 And these kinds of experiments are started[br]with programs that we wrote ourselves. 0:07:35.166,0:07:38.503 We write our own stuff, replicate it,[br]and are very proud of ourselves. 0:07:38.527,0:07:41.303 And we put them in,[br]and what you see immediately 0:07:41.327,0:07:44.393 is that there are waves[br]and waves of innovation. 0:07:44.417,0:07:46.311 By the way, this is highly accelerated, 0:07:46.335,0:07:48.532 so it's like a 1000 generations a second. 0:07:48.556,0:07:52.523 But immediately, the system goes like,[br]"What kind of dumb piece of code was this? 0:07:52.547,0:07:56.268 This can be improved upon[br]in so many ways, so quickly." 0:07:56.292,0:08:00.040 So you see waves of new types[br]taking over the other types. 0:08:00.064,0:08:02.626 And this type of activity[br]goes on for quite a while, 0:08:02.650,0:08:07.471 until the main easy things[br]have been acquired by these programs. 0:08:07.495,0:08:10.976 And then, you see[br]sort of like a stasis coming on 0:08:11.000,0:08:12.976 where the system essentially waits 0:08:13.000,0:08:16.183 for a new type of innovation,[br]like this one, 0:08:16.207,0:08:20.489 which is going to spread over[br]all the other innovations that were before 0:08:20.513,0:08:22.976 and is erasing the genes[br]that it had before, 0:08:23.000,0:08:26.976 until a new type of higher level[br]of complexity has been achieved. 0:08:27.000,0:08:29.976 And this process goes on and on and on. 0:08:30.467,0:08:31.782 So what we see here 0:08:31.806,0:08:35.969 is a system that lives in very much[br]the way we're used to how life goes. 0:08:36.688,0:08:40.808 But what the NASA people[br]had asked me really was, 0:08:41.213,0:08:43.975 "Do these guys have a biosignature? 0:08:44.580,0:08:46.393 Can we measure this type of life? 0:08:46.417,0:08:47.609 Because if we can, 0:08:47.633,0:08:51.482 maybe we have a chance of actually[br]discovering life somewhere else 0:08:51.506,0:08:54.660 without being biased[br]by things like amino acids." 0:08:55.221,0:08:59.754 So I said, "Well, perhaps[br]we should construct a biosignature 0:08:59.778,0:09:02.976 based on life as a universal process. 0:09:03.000,0:09:07.864 In fact, it should perhaps make use[br]of the concepts that I developed 0:09:07.888,0:09:11.975 just in order to sort of capture[br]what a simple living system might be." 0:09:11.999,0:09:13.518 And the thing I came up with -- 0:09:13.542,0:09:17.524 I have to first give you[br]an introduction about the idea, 0:09:17.548,0:09:21.087 and maybe that would be[br]a meaning detector, 0:09:21.111,0:09:22.658 rather than a life detector. 0:09:23.226,0:09:24.976 And the way we would do that -- 0:09:25.000,0:09:27.636 I would like to find out[br]how I can distinguish text 0:09:27.660,0:09:32.307 that was written by a million monkeys,[br]as opposed to text that is in our books. 0:09:32.645,0:09:34.522 And I would like to do it in such a way 0:09:34.546,0:09:37.424 that I don't actually have to be able[br]to read the language, 0:09:37.448,0:09:39.218 because I'm sure I won't be able to. 0:09:39.242,0:09:41.742 As long as I know[br]that there's some sort of alphabet. 0:09:41.766,0:09:44.096 So here would be a frequency plot 0:09:44.120,0:09:47.502 of how often you find[br]each of the 26 letters of the alphabet 0:09:47.526,0:09:49.745 in a text written by random monkeys. 0:09:50.195,0:09:54.749 And obviously, each of these letters[br]comes off about roughly equally frequent. 0:09:54.773,0:09:58.365 But if you now look at the same[br]distribution in English texts, 0:09:58.389,0:09:59.637 it looks like that. 0:10:00.202,0:10:03.750 And I'm telling you,[br]this is very robust across English texts. 0:10:03.774,0:10:06.758 And if I look at French texts,[br]it looks a little bit different, 0:10:06.782,0:10:07.960 or Italian or German. 0:10:07.984,0:10:11.400 They all have their own type[br]of frequency distribution, 0:10:11.424,0:10:12.857 but it's robust. 0:10:12.881,0:10:16.088 It doesn't matter whether it writes[br]about politics or about science. 0:10:16.112,0:10:21.892 It doesn't matter whether it's a poem[br]or whether it's a mathematical text. 0:10:21.916,0:10:23.753 It's a robust signature, 0:10:23.777,0:10:25.597 and it's very stable. 0:10:25.621,0:10:27.778 As long as our books[br]are written in English -- 0:10:27.802,0:10:30.593 because people are rewriting them[br]and recopying them -- 0:10:30.617,0:10:31.976 it's going to be there. 0:10:32.000,0:10:37.761 So that inspired me to think about,[br]well, what if I try to use this idea 0:10:37.785,0:10:41.540 in order, not to detect random texts[br]from texts with meaning, 0:10:41.564,0:10:45.293 but rather detect the fact[br]that there is meaning 0:10:45.317,0:10:47.844 in the biomolecules that make up life. 0:10:47.868,0:10:49.036 But first I have to ask: 0:10:49.060,0:10:50.548 what are these building blocks, 0:10:50.572,0:10:52.868 like the alphabet, elements[br]that I showed you? 0:10:52.892,0:10:55.765 Well it turns out, we have[br]many different alternatives 0:10:55.789,0:10:58.103 for such a set of building blocks. 0:10:58.127,0:10:59.375 We could use amino acids, 0:10:59.399,0:11:02.601 we could use nucleic acids,[br]carboxylic acids, fatty acids. 0:11:02.625,0:11:06.063 In fact, chemistry's extremely rich,[br]and our body uses a lot of them. 0:11:06.087,0:11:08.393 So that we actually, to test this idea, 0:11:08.417,0:11:11.964 first took a look at amino acids[br]and some other carboxylic acids. 0:11:11.988,0:11:13.459 And here's the result. 0:11:13.483,0:11:16.649 Here is, in fact, what you get 0:11:16.673,0:11:19.696 if you, for example, look[br]at the distribution of amino acids 0:11:19.720,0:11:24.455 on a comet or in interstellar space[br]or, in fact, in a laboratory, 0:11:24.479,0:11:27.138 where you made very sure[br]that in your primordial soup, 0:11:27.162,0:11:29.080 there is no living stuff in there. 0:11:29.104,0:11:31.983 What you find is mostly[br]glycine and then alanine 0:11:32.007,0:11:34.366 and there's some trace elements[br]of the other ones. 0:11:34.390,0:11:36.819 That is also very robust -- 0:11:36.843,0:11:40.675 what you find in systems like Earth 0:11:40.699,0:11:43.844 where there are amino acids,[br]but there is no life. 0:11:43.868,0:11:48.498 But suppose you take some dirt[br]and dig through it 0:11:48.522,0:11:51.482 and then put it into these spectrometers, 0:11:51.506,0:11:53.604 because there's bacteria[br]all over the place; 0:11:53.628,0:11:55.859 or you take water anywhere on Earth, 0:11:55.883,0:11:57.400 because it's teaming with life, 0:11:57.424,0:11:59.174 and you make the same analysis; 0:11:59.198,0:12:01.775 the spectrum looks completely different. 0:12:01.799,0:12:05.174 Of course, there is still[br]glycine and alanine, 0:12:05.198,0:12:08.518 but in fact, there are these heavy[br]elements, these heavy amino acids, 0:12:08.542,0:12:11.937 that are being produced[br]because they are valuable to the organism. 0:12:13.067,0:12:17.005 And some other ones[br]that are not used in the set of 20, 0:12:17.029,0:12:19.927 they will not appear at all[br]in any type of concentration. 0:12:19.951,0:12:22.656 So this also turns out[br]to be extremely robust. 0:12:22.680,0:12:25.798 It doesn't matter what kind of sediment[br]you're using to grind up, 0:12:25.822,0:12:29.101 whether it's bacteria[br]or any other plants or animals. 0:12:29.125,0:12:30.549 Anywhere there's life, 0:12:30.573,0:12:32.524 you're going to have this distribution, 0:12:32.548,0:12:34.365 as opposed to that distribution. 0:12:34.389,0:12:37.626 And it is detectable[br]not just in amino acids. 0:12:37.650,0:12:38.867 Now you could ask: 0:12:38.891,0:12:42.050 Well, what about these Avidians? 0:12:42.074,0:12:45.125 The Avidians being the denizens[br]of this computer world 0:12:45.149,0:12:48.594 where they are perfectly happy[br]replicating and growing in complexity. 0:12:48.618,0:12:53.635 So this is the distribution that you get[br]if, in fact, there is no life. 0:12:53.659,0:12:56.377 They have about 28 of these instructions. 0:12:56.401,0:12:59.753 And if you have a system where[br]they're being replaced one by the other, 0:12:59.777,0:13:01.962 it's like the monkeys[br]writing on a typewriter. 0:13:01.986,0:13:06.206 Each of these instructions[br]appears with roughly the equal frequency. 0:13:07.115,0:13:11.895 But if you now take[br]a set of replicating guys 0:13:11.919,0:13:13.869 like in the video that you saw, 0:13:13.893,0:13:15.412 it looks like this. 0:13:16.199,0:13:17.672 So there are some instructions 0:13:17.696,0:13:20.129 that are extremely valuable[br]to these organisms, 0:13:20.153,0:13:22.123 and their frequency is going to be high. 0:13:22.147,0:13:26.188 And there's actually some instructions[br]that you only use once, if ever. 0:13:26.212,0:13:27.735 So they are either poisonous 0:13:27.759,0:13:32.264 or really should be used[br]at less of a level than random. 0:13:32.288,0:13:34.976 In this case, the frequency is lower. 0:13:35.932,0:13:38.603 And so now we can see,[br]is that really a robust signature? 0:13:38.627,0:13:39.984 I can tell you indeed it is, 0:13:40.008,0:13:43.256 because this type of spectrum,[br]just like what you've seen in books, 0:13:43.280,0:13:45.433 and just like what you've seen[br]in amino acids, 0:13:45.457,0:13:48.099 it doesn't really matter[br]how you change the environment, 0:13:48.123,0:13:50.747 it's very robust, it's going[br]to reflect the environment. 0:13:50.771,0:13:53.720 So I'm going to show you now[br]a little experiment that we did. 0:13:53.744,0:13:55.128 And I have to explain to you, 0:13:55.152,0:13:56.334 the top of this graph 0:13:56.358,0:13:59.102 shows you that frequency[br]distribution that I talked about. 0:13:59.126,0:14:02.933 Here, that's the lifeless environment 0:14:02.957,0:14:06.369 where each instruction occurs[br]at an equal frequency. 0:14:07.304,0:14:12.297 And below there, I show, in fact,[br]the mutation rate in the environment. 0:14:12.321,0:14:15.624 And I'm starting this[br]at a mutation rate that is so high 0:14:15.648,0:14:19.614 that even if you would drop[br]a replicating program 0:14:19.638,0:14:23.763 that would otherwise happily grow up[br]to fill the entire world, 0:14:23.787,0:14:26.797 if you drop it in, it gets mutated[br]to death immediately. 0:14:26.821,0:14:32.167 So there is no life possible[br]at that type of mutation rate. 0:14:32.191,0:14:36.227 But then I'm going to slowly[br]turn down the heat, so to speak, 0:14:36.251,0:14:38.436 and then there's this viability threshold 0:14:38.460,0:14:42.352 where now it would be possible[br]for a replicator to actually live. 0:14:42.376,0:14:47.721 And indeed, we're going to be dropping[br]these guys into that soup all the time. 0:14:48.159,0:14:49.795 So let's see what that looks like. 0:14:49.819,0:14:52.817 So first, nothing, nothing, nothing. 0:14:52.841,0:14:54.656 Too hot, too hot. 0:14:54.680,0:14:56.976 Now the viability threshold is reached, 0:14:57.000,0:15:01.492 and the frequency distribution[br]has dramatically changed 0:15:01.516,0:15:02.992 and, in fact, stabilizes. 0:15:03.016,0:15:04.526 And now what I did there 0:15:04.550,0:15:08.148 is, I was being nasty,[br]I just turned up the heat again and again. 0:15:08.172,0:15:10.518 And of course, it reaches[br]the viability threshold. 0:15:10.542,0:15:13.410 And I'm just showing this to you[br]again because it's so nice. 0:15:13.434,0:15:14.976 You hit the viability threshold. 0:15:15.000,0:15:16.976 The distribution changes to "alive!" 0:15:17.431,0:15:20.648 And then, once you hit the threshold 0:15:20.672,0:15:24.721 where the mutation rate is so high[br]that you cannot self-reproduce, 0:15:24.745,0:15:29.666 you cannot copy the information[br]forward to your offspring 0:15:29.690,0:15:34.420 without making so many mistakes[br]that your ability to replicate vanishes. 0:15:34.444,0:15:36.303 And then, that signature is lost. 0:15:37.956,0:15:39.662 What do we learn from that? 0:15:39.686,0:15:43.482 Well, I think we learn[br]a number of things from that. 0:15:43.506,0:15:44.976 One of them is, 0:15:45.000,0:15:50.224 if we are able to think about life[br]in abstract terms -- 0:15:50.248,0:15:52.879 and we're not talking[br]about things like plants, 0:15:52.903,0:15:54.828 and we're not talking about amino acids, 0:15:54.852,0:15:56.616 and we're not talking about bacteria, 0:15:56.640,0:15:58.750 but we think in terms of processes -- 0:15:58.774,0:16:00.976 then we could start to think about life 0:16:01.000,0:16:03.619 not as something[br]that is so special to Earth, 0:16:03.643,0:16:06.153 but that, in fact, could exist anywhere. 0:16:06.177,0:16:10.490 Because it really only has to do[br]with these concepts of information, 0:16:10.514,0:16:14.572 of storing information[br]within physical substrates -- 0:16:14.596,0:16:18.612 anything: bits, nucleic acids,[br]anything that's an alphabet -- 0:16:18.636,0:16:20.515 and make sure that there's some process 0:16:20.539,0:16:24.254 so that this information can be stored[br]for much longer than you would expect -- 0:16:24.816,0:16:29.152 the time scales for[br]the deterioration of information. 0:16:29.176,0:16:32.344 And if you can do that,[br]then you have life. 0:16:32.368,0:16:34.622 So the first thing that we learn 0:16:34.646,0:16:39.858 is that it is possible to define life[br]in terms of processes alone, 0:16:39.882,0:16:44.859 without referring at all[br]to the type of things that we hold dear, 0:16:44.883,0:16:47.554 as far as the type of life on Earth is. 0:16:47.578,0:16:50.219 And that, in a sense, removes us again, 0:16:50.243,0:16:53.074 like all of our scientific discoveries,[br]or many of them -- 0:16:53.098,0:16:55.869 it's this continuous dethroning of man -- 0:16:55.893,0:16:58.620 of how we think we're special[br]because we're alive. 0:16:58.644,0:17:01.700 Well, we can make life;[br]we can make life in the computer. 0:17:01.724,0:17:03.541 Granted, it's limited, 0:17:03.565,0:17:08.682 but we have learned what it takes[br]in order to actually construct it. 0:17:08.706,0:17:11.494 And once we have that, 0:17:11.518,0:17:14.165 then it is not such[br]a difficult task anymore 0:17:14.189,0:17:18.341 to say, if we understand[br]the fundamental processes 0:17:18.365,0:17:21.707 that do not refer[br]to any particular substrate, 0:17:21.731,0:17:25.499 then we can go out and try other worlds, 0:17:25.523,0:17:29.304 figure out what kind of chemical[br]alphabets might there be, 0:17:30.033,0:17:34.758 figure enough about the normal chemistry,[br]the geochemistry of the planet, 0:17:34.782,0:17:38.556 so that we know what this distribution[br]would look like in the absence of life, 0:17:38.580,0:17:41.551 and then look for large[br]deviations from this -- 0:17:41.575,0:17:46.687 this thing sticking out, which says,[br]"This chemical really shouldn't be there." 0:17:46.711,0:17:48.666 Now we don't know that there's life then, 0:17:48.690,0:17:49.897 but we could say, 0:17:49.921,0:17:53.690 "Well at least I'm going to have to take[br]a look very precisely at this chemical 0:17:53.714,0:17:55.759 and see where it comes from." 0:17:55.783,0:17:59.494 And that might be our chance[br]of actually discovering life 0:17:59.518,0:18:01.637 when we cannot visibly see it. 0:18:01.661,0:18:06.225 And so that's really the only[br]take-home message that I have for you. 0:18:06.249,0:18:10.480 Life can be less mysterious[br]than we make it out to be 0:18:10.504,0:18:13.709 when we try to think[br]about how it would be on other planets. 0:18:14.280,0:18:17.667 And if we remove the mystery of life, 0:18:17.691,0:18:22.376 then I think it is a little bit easier[br]for us to think about how we live, 0:18:22.400,0:18:25.458 and how perhaps we're not as special[br]as we always think we are. 0:18:25.482,0:18:27.728 And I'm going to leave you with that. 0:18:27.752,0:18:28.976 And thank you very much. 0:18:29.000,0:18:31.174 (Applause)