The Secret Life of Chaos

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0:00:12 > 0:00:17This is a film about one very simple question.

0:00:17 > 0:00:19How did we get here?

0:00:26 > 0:00:30These are the elements and compounds from which all humans are made.

0:00:30 > 0:00:34They're incredibly, almost embarrassingly common.

0:00:34 > 0:00:39In fact, almost 99% of the human body is a mixture of air, water,

0:00:39 > 0:00:43coal and chalk, with traces of other slightly more exotic elements

0:00:43 > 0:00:47like iron, zinc, phosphorus and sulphur.

0:00:47 > 0:00:51In fact, I've estimated that the elements

0:00:51 > 0:00:56which make up the average human cost at most a few pounds.

0:00:56 > 0:01:03But somehow, trillions of these very ordinary atoms conspire miraculously

0:01:03 > 0:01:07to organise themselves into thinking, breathing, living human beings.

0:01:09 > 0:01:12How the wonders of creation are assembled from such simple

0:01:12 > 0:01:18building blocks, is surely the most intriguing question we can ask.

0:01:18 > 0:01:22You may think that answering it is beyond the realm of science.

0:01:22 > 0:01:24But that's changing.

0:01:24 > 0:01:29For the first time, I believe science has pushed past religion

0:01:29 > 0:01:34and philosophy in daring to tackle this most fundamental of questions.

0:01:40 > 0:01:43This film is the story of a series of bizarre

0:01:43 > 0:01:48and interconnected discoveries that reveal a hidden face of nature.

0:01:50 > 0:01:54That woven into its simplest and most basic laws,

0:01:54 > 0:01:57is a power to be unpredictable.

0:01:58 > 0:02:02It's about how inanimate matter with no purpose or design,

0:02:02 > 0:02:08can spontaneously create exquisite beauty.

0:02:08 > 0:02:12It's about how the same laws that make the universe chaotic

0:02:12 > 0:02:17and unpredictable, can turn simple dust into human beings.

0:02:19 > 0:02:22It's about the discovery that there is a strange

0:02:22 > 0:02:28and unexpected relationship between order and chaos.

0:02:59 > 0:03:05The natural world really is one great, blooming, buzzing confusion.

0:03:06 > 0:03:09It's a mess of quirky shapes and blotches.

0:03:09 > 0:03:13What patterns there are, are never quite regular,

0:03:13 > 0:03:16and never seem to repeat exactly.

0:03:19 > 0:03:24The idea that all this mayhem, all this chaos, is underpinned,

0:03:24 > 0:03:27indeed determined, by mathematical rules,

0:03:27 > 0:03:30and that we can work out what those rules might be,

0:03:30 > 0:03:34runs counter to our most dearly held intuitions.

0:03:41 > 0:03:46So not surprisingly, the first man to really take on the momentous task

0:03:46 > 0:03:50of unravelling nature's mysterious mathematics,

0:03:50 > 0:03:54had a very special and unusual mind.

0:03:54 > 0:03:58He was both a great scientist and a tragic hero.

0:03:58 > 0:04:02He was born in 1912, in London.

0:04:02 > 0:04:04His name was Alan Turing.

0:04:06 > 0:04:09Alan Turing was a remarkable man,

0:04:09 > 0:04:12one of the greatest mathematicians who ever lived.

0:04:12 > 0:04:15He discovered many of the fundamental ideas

0:04:15 > 0:04:18that underpin the modern computer.

0:04:18 > 0:04:20Also, during the Second World War,

0:04:20 > 0:04:24he worked here at Bletchley Park, just outside today's Milton Keynes,

0:04:24 > 0:04:28in what was then a secret government project called Station X,

0:04:28 > 0:04:32which was set up to crack the German military codes.

0:04:32 > 0:04:37The Station X code breakers proved highly effective,

0:04:37 > 0:04:40and Turing's contribution was crucial.

0:04:40 > 0:04:44The work he personally did to crack German naval codes,

0:04:44 > 0:04:50saved thousands of Allied lives and was a turning point in the war.

0:04:50 > 0:04:54But code breaking was just one aspect of Turing's genius.

0:04:54 > 0:04:58Just one part of his uncanny ability to see patterns

0:04:58 > 0:05:00that are hidden from the rest of us.

0:05:00 > 0:05:04For Turing, the natural world offered up the ultimate codes.

0:05:04 > 0:05:06And over the course of his life

0:05:06 > 0:05:10he'd come tantalisingly close to cracking them.

0:05:10 > 0:05:12Turing was a very original person.

0:05:12 > 0:05:17And he had realised that there was this possibility

0:05:17 > 0:05:20that simple mathematical equations

0:05:20 > 0:05:23might describe aspects of the biological world.

0:05:23 > 0:05:25And no-one had thought of that before.

0:05:27 > 0:05:31Of all nature's mysteries, the one that fascinated Turing most

0:05:31 > 0:05:34was the idea that there might be a mathematical basis

0:05:34 > 0:05:38to human intelligence.

0:05:38 > 0:05:42Turing had very personal reasons for believing in this.

0:05:42 > 0:05:45It was the death of this young man, Christopher Morcom,

0:05:45 > 0:05:48who...Alan Turing, well, he was gay,

0:05:48 > 0:05:52and it had been the great emotional thing of his life at that point.

0:05:52 > 0:05:54Christopher Morcom suddenly died.

0:05:54 > 0:06:00And, Alan Turing was obviously very emotionally disturbed by this.

0:06:00 > 0:06:02But you can see that he wanted to put this

0:06:02 > 0:06:05in an intellectual context, a scientific context.

0:06:05 > 0:06:08And the question he wanted to put into context was

0:06:08 > 0:06:10what happens to the mind? What is it?

0:06:14 > 0:06:19Turing became convinced that mathematics could be used to describe

0:06:19 > 0:06:24biological systems, and ultimately intelligence.

0:06:24 > 0:06:28This fascination would give rise to the modern computer,

0:06:28 > 0:06:31and later in Turing's life, an even more radical idea.

0:06:31 > 0:06:36The idea that a simple mathematical description could be given

0:06:36 > 0:06:41for a mysterious process that takes place in an embryo.

0:06:44 > 0:06:49The process is called morphogenesis, and it's very puzzling.

0:06:54 > 0:06:58At first, all the cells in the embryo are identical.

0:06:59 > 0:07:03Then, as this footage of a fish embryo shows,

0:07:03 > 0:07:05the cells begin to clump together,

0:07:05 > 0:07:08and also become different from each other.

0:07:10 > 0:07:14How does this happen? With no thought,

0:07:14 > 0:07:16no central co-ordination?

0:07:17 > 0:07:23How do cells that start off identical, know to become say, skin,

0:07:23 > 0:07:27while others become part of an eye?

0:07:31 > 0:07:35Morphogenesis is a spectacular example

0:07:35 > 0:07:38of something called self-organisation.

0:07:39 > 0:07:44And before Turing, no-one had a clue how it worked.

0:07:48 > 0:07:53Then, in 1952, Turing published this, his paper

0:07:53 > 0:07:57with the world's first mathematical explanation for morphogenesis.

0:07:59 > 0:08:02The sheer chutzpah of this paper was staggering.

0:08:06 > 0:08:09In it, Turing used a mathematical equation

0:08:09 > 0:08:14of the kind normally seen in papers on astronomy or atomic physics,

0:08:14 > 0:08:17to describe a living process.

0:08:18 > 0:08:21No-one had done anything like this.

0:08:22 > 0:08:27Crucially, Turing's equations did, for the first time,

0:08:27 > 0:08:32describe how a biological system could self-organise.

0:08:32 > 0:08:38They showed that something smooth and featureless can develop features.

0:08:39 > 0:08:42One of the astonishing things about Turing's work

0:08:42 > 0:08:44was that starting with the description

0:08:44 > 0:08:46of really very simple processes

0:08:46 > 0:08:51governed by very simple equations, by putting these together,

0:08:51 > 0:08:53suddenly complexity emerged.

0:08:53 > 0:08:57The pattern suddenly came out as a natural consequence.

0:08:57 > 0:09:00And I think in many ways this was very, very unexpected.

0:09:05 > 0:09:10In essence, Turing's equations described something quite familiar,

0:09:10 > 0:09:14but which no-one had thought of in the context of biology before.

0:09:20 > 0:09:23Think of the way a steady wind blowing across sand

0:09:23 > 0:09:26creates all kinds of shapes.

0:09:26 > 0:09:32The grains self-organise into ripples, waves and dunes.

0:09:33 > 0:09:37This happens, even though the grains are virtually identical,

0:09:37 > 0:09:41and have no knowledge of the shapes they become part of.

0:09:44 > 0:09:47Turing argued that in a very similar way,

0:09:47 > 0:09:49chemicals seeping across an embryo

0:09:49 > 0:09:55might cause its cells to self-organise into different organs.

0:10:02 > 0:10:07These are Turing's own very rough scribblings of how this might work.

0:10:13 > 0:10:17They show how a completely featureless chemical soup,

0:10:17 > 0:10:21can evolve these strange blobs and patches.

0:10:24 > 0:10:27In his paper, he refined his sketches

0:10:27 > 0:10:31to show how his equations could spontaneously create markings

0:10:31 > 0:10:34similar to those on the skins of animals.

0:10:36 > 0:10:39Turing went around showing people pictures saying,

0:10:39 > 0:10:42"Doesn't this look a bit like the patterns on a cow?"

0:10:42 > 0:10:44And everyone sort of went, "What is this man on about?"

0:10:44 > 0:10:47But actually, he knew what he was doing.

0:10:47 > 0:10:50They did look like the patterns of a cow, and that's one of

0:10:50 > 0:10:53the reasons why cows have this dappled pattern or whatever.

0:10:53 > 0:10:58So, an area where mathematics had never been used before,

0:10:58 > 0:11:02pattern formation in biology, animal markings,

0:11:02 > 0:11:06suddenly the door was opened and we could see

0:11:06 > 0:11:10that mathematics might be useful in that sort of area.

0:11:10 > 0:11:14So even though Turing's exact equations are not the full story,

0:11:14 > 0:11:19they are the first piece of mathematical work that showed

0:11:19 > 0:11:22there was any possibility of doing this kind of thing.

0:11:28 > 0:11:31Of course, we now know that morphogenesis

0:11:31 > 0:11:36is much more complicated than the process Turing's equations describe.

0:11:36 > 0:11:42In fact, the precise mechanism of how DNA molecules in our cells interact

0:11:42 > 0:11:46with other chemicals, is still fiercely debated by scientists.

0:11:48 > 0:11:52But Turing's idea that whatever is going on is, deep down,

0:11:52 > 0:11:57a simple mathematical process, was truly revolutionary.

0:11:58 > 0:12:02I think Alan Turing's paper is probably the cornerstone

0:12:02 > 0:12:06in the whole idea of how morphogenesis works.

0:12:06 > 0:12:08What it does is it provides us with a mechanism,

0:12:08 > 0:12:12something that Darwin didn't, for how pattern emerges.

0:12:12 > 0:12:15Darwin, of course, tells us that once you have a pattern

0:12:15 > 0:12:19and it is coded for in the genes, that may or may not be passed on,

0:12:19 > 0:12:22depending on circumstances. But what it doesn't do

0:12:22 > 0:12:25is explain where that pattern comes from in the first place.

0:12:25 > 0:12:26That's the real mystery.

0:12:26 > 0:12:30And so, what Turing had done was to suddenly provide

0:12:30 > 0:12:34an accessible chemical mechanism for doing this. That was amazing.

0:12:37 > 0:12:41Turing was onto a really big, bold idea.

0:12:43 > 0:12:47But sadly, we can only speculate how his extraordinary mind

0:12:47 > 0:12:50would have developed his idea.

0:12:51 > 0:12:55Shortly after his groundbreaking paper on morphogenesis,

0:12:55 > 0:13:00a dreadful and completely avoidable tragedy destroyed his life.

0:13:04 > 0:13:08After his work breaking codes at Bletchley Park,

0:13:08 > 0:13:12you might well have assumed that Turing would have been honoured

0:13:12 > 0:13:14by the country he did so much to protect.

0:13:14 > 0:13:17This couldn't be further from the truth.

0:13:17 > 0:13:20What happened to him after the war was a great tragedy,

0:13:20 > 0:13:25and one of the most shameful episodes in the history of British science.

0:13:27 > 0:13:31The same year Turing published his morphogenesis paper,

0:13:31 > 0:13:35he had a brief affair with a man called Arnold Murray.

0:13:35 > 0:13:36The affair went sour

0:13:36 > 0:13:40and Murray was involved in a burglary at Turing's house.

0:13:40 > 0:13:43But when Turing reported this to the police,

0:13:43 > 0:13:46they arrested him as well as Murray.

0:13:48 > 0:13:51In court, the prosecution argued

0:13:51 > 0:13:56that Turing, with his university education, had led Murray astray.

0:13:59 > 0:14:02He was convicted of gross indecency.

0:14:02 > 0:14:06The judge then offered Turing a dreadful choice.

0:14:08 > 0:14:12He could either go to prison, or sign up to a regime of

0:14:12 > 0:14:16female hormone injections to cure him of his homosexuality.

0:14:16 > 0:14:22He chose the latter, and it was to send him into a spiral of depression.

0:14:22 > 0:14:27On 8 June 1954, Turing's body was found by his cleaner.

0:14:27 > 0:14:31He'd died the day before by taking a bite from an apple

0:14:31 > 0:14:34he'd laced with cyanide, ending his own life.

0:14:37 > 0:14:40Alan Turing died aged just 41.

0:14:40 > 0:14:44The loss to science is incalculable.

0:14:44 > 0:14:48Turing would never know that his ideas would inspire

0:14:48 > 0:14:52an entirely new mathematical approach to biology,

0:14:52 > 0:14:55and that scientists would find equations like his

0:14:55 > 0:15:00really do explain many of the shapes that appear on living organisms.

0:15:03 > 0:15:07Looking back, we now know Turing had really grasped the idea

0:15:07 > 0:15:12that the wonders of creation are derived from the simplest of rules.

0:15:12 > 0:15:18He had, perhaps unexpectedly, taken the first step

0:15:18 > 0:15:20to a new kind of science.

0:15:36 > 0:15:40The next step in the story was just as unexpected,

0:15:40 > 0:15:44and in many ways, just as tragic as Turing's.

0:15:46 > 0:15:51In the early 1950s, around the time of Turing's seminal paper

0:15:51 > 0:15:55on morphogenesis, a brilliant Russian chemist by the name of

0:15:55 > 0:15:59Boris Belousov was beginning his own investigations

0:15:59 > 0:16:01into the chemistry of nature.

0:16:01 > 0:16:06Deep behind the iron curtain, in a lab at the Soviet Ministry of Health,

0:16:06 > 0:16:09he was beginning to investigate the way our bodies

0:16:09 > 0:16:11extract energy from sugars.

0:16:15 > 0:16:20Just like Turing, Belousov was working on a personal project, having

0:16:20 > 0:16:25just finished a distinguished career as a scientist in the military.

0:16:25 > 0:16:29In his lab, Belousov had formulated a mixture of chemicals

0:16:29 > 0:16:34to mimic one part of the process of glucose absorption in the body.

0:16:34 > 0:16:38The mix of chemicals sat on the lab bench in front of him,

0:16:38 > 0:16:41clear and colourless while being shaken.

0:16:41 > 0:16:46As he mixed in the final chemical, the whole solution changed colour.

0:16:46 > 0:16:49Now this isn't particularly remarkable.

0:16:49 > 0:16:52If we mix ink into water, it changes colour.

0:16:52 > 0:16:58But then something happened that made no sense at all.

0:16:58 > 0:17:02The mixture began to go clear again.

0:17:07 > 0:17:09Belousov was astounded.

0:17:09 > 0:17:12Chemicals can mix together and react.

0:17:12 > 0:17:16But they shouldn't be able to go back on themselves,

0:17:16 > 0:17:19to apparently unmix without intervention.

0:17:19 > 0:17:23You can change from a clear mixture to a coloured mixture, fine.

0:17:23 > 0:17:25But surely not back again?

0:17:28 > 0:17:30And it got weirder.

0:17:30 > 0:17:34Belousov's chemicals didn't just spontaneously go into reverse.

0:17:34 > 0:17:36They oscillated.

0:17:36 > 0:17:40They switched back and forth from coloured to clear,

0:17:40 > 0:17:46as if they were being driven by some sort of hidden chemical metronome.

0:17:46 > 0:17:52With meticulous care, he repeated his experiments again and again.

0:17:52 > 0:17:55It was the same every time.

0:17:55 > 0:18:00His mixture would cycle from clear to coloured and back again, repeatedly.

0:18:00 > 0:18:03He'd discovered something that was almost like magic,

0:18:03 > 0:18:07a physical process that seemed to violate the laws of nature.

0:18:11 > 0:18:14'Convinced he'd discovered something of great importance, Belousov

0:18:14 > 0:18:20'wrote up his findings, keen to share his discovery with the wider world.

0:18:20 > 0:18:24'But when he submitted his paper to a leading Russian scientific journal,

0:18:24 > 0:18:29'he received a wholly unexpected and damning response.'

0:18:29 > 0:18:33The editor of the journal told Belousov that his findings in the lab

0:18:33 > 0:18:36were quite simply impossible.

0:18:36 > 0:18:39They contravened the fundamental laws of physics.

0:18:39 > 0:18:43The only explanation was that Belousov had made a mistake

0:18:43 > 0:18:48in his experiment, and the work was simply not fit for publication.

0:18:53 > 0:18:56'The rejection crushed Belousov.

0:18:56 > 0:19:00'Deeply insulted by the suggestion his work had been botched,

0:19:00 > 0:19:02'he abandoned his experiments.

0:19:02 > 0:19:05'Soon he gave up science altogether.'

0:19:07 > 0:19:11The tragic irony was that, divided as they were by the Iron Curtain,

0:19:11 > 0:19:15Belousov never encountered Turing's work.

0:19:15 > 0:19:20For if he had, he would have been completely vindicated.

0:19:20 > 0:19:24It turns out that Belousov's oscillating chemicals,

0:19:24 > 0:19:27far from contravening the laws of physics,

0:19:27 > 0:19:30were actually a real world example

0:19:30 > 0:19:34of precisely the behaviour Turing's equations predicted.

0:19:45 > 0:19:49While the connection might not appear obvious at first sight,

0:19:49 > 0:19:52other scientists showed that if you left a variation

0:19:52 > 0:19:56of Belousov's chemicals, unstirred in a Petri dish,

0:19:56 > 0:20:01instead of simply oscillating, they self-organise into shapes.

0:20:01 > 0:20:05In fact, they go beyond Turing's simple blobs and stripes

0:20:05 > 0:20:10to create stunningly beautiful structures and patterns

0:20:10 > 0:20:12out of nowhere.

0:20:22 > 0:20:26The amazing and very unexpected thing about the BZ reaction

0:20:26 > 0:20:28is that someone had discovered a system

0:20:28 > 0:20:32which essentially reproduces the Turing equations.

0:20:32 > 0:20:36And so, from what looks like a very, very bland solution

0:20:36 > 0:20:41emerge these astonishing patterns of waves and scrolls and spirals.

0:20:45 > 0:20:49Now this is emphatically not abstract science.

0:20:49 > 0:20:53The way Belousov's chemicals move as co-ordinated waves

0:20:53 > 0:20:58is exactly the way our heart cells are co-ordinated as they beat.

0:21:01 > 0:21:04Animal skins and heart beats.

0:21:04 > 0:21:08Self-organisation seems to operate all over the natural world.

0:21:15 > 0:21:20So why were the scientific community in Turing and Belousov's day,

0:21:20 > 0:21:25so uninterested, or even hostile to this astonishing and beautiful idea?

0:21:29 > 0:21:33Well, the reason was all too human.

0:21:34 > 0:21:38Mainstream scientists simply didn't like it.

0:21:38 > 0:21:41To them it seemed to run counter to science,

0:21:41 > 0:21:44and all that it had achieved.

0:21:52 > 0:21:56To change that view would require a truly shocking

0:21:56 > 0:21:59and completely unexpected discovery.

0:22:02 > 0:22:06In essence, by the beginning of the 20th century,

0:22:06 > 0:22:09scientists saw the universe as a giant,

0:22:09 > 0:22:12complicated, mechanical device.

0:22:12 > 0:22:17Kind of a super-sized version of this orrery.

0:22:21 > 0:22:26The idea was that the universe is a huge and intricate machine

0:22:26 > 0:22:30that obeys orderly mathematical rules.

0:22:30 > 0:22:33If you knew the rules of how the machine was configured to start with,

0:22:33 > 0:22:37as you turned the handle, over and over again,

0:22:37 > 0:22:40it would behave in an entirely predictable way.

0:22:43 > 0:22:44Back in the times of Isaac Newton

0:22:44 > 0:22:48when people were discovering the laws that drove the universe,

0:22:48 > 0:22:52they came up with this kind of metaphor of a clockwork universe.

0:22:52 > 0:22:56The universe looked like a machine which had been set going at the

0:22:56 > 0:23:00instant of creation and just followed the rules and ticked along.

0:23:00 > 0:23:04And it was a complicated machine and therefore complicated things happen.

0:23:04 > 0:23:08But once you set it going it would only do one thing,

0:23:08 > 0:23:11and the message that people drew from this

0:23:11 > 0:23:14was that anything describable by mathematical rules

0:23:14 > 0:23:17must actually basically be fairly simple.

0:23:21 > 0:23:25Find the mathematics that describes a system

0:23:25 > 0:23:28and you can then predict how that system will unfold.

0:23:28 > 0:23:30That was the big idea.

0:23:30 > 0:23:33It began with Newton's law of gravity

0:23:33 > 0:23:37which can be used to predict how a planet moves around the sun.

0:23:37 > 0:23:42Scientists soon found many other equations just like it.

0:23:44 > 0:23:49Newtonian physics seemed like the ultimate crystal-ball.

0:23:49 > 0:23:51It held up the tantalising possibility

0:23:51 > 0:23:54that the future could, in principle, be known.

0:23:54 > 0:23:57The more careful your measurements are today,

0:23:57 > 0:24:00the better you can predict what will happen tomorrow.

0:24:05 > 0:24:10But Newtonianism had a dangerous consequence.

0:24:10 > 0:24:13If a nice mathematical system, that worked in a similar way

0:24:13 > 0:24:19to my orrery, did sometimes become unpredictable, scientists assumed

0:24:19 > 0:24:24some malign outside force was causing it. Perhaps dirt had got in?

0:24:24 > 0:24:26Perhaps the cogs were wearing out?

0:24:26 > 0:24:30Or perhaps someone had tampered with it?

0:24:30 > 0:24:34Basically we used to think, if you saw very irregular behaviour

0:24:34 > 0:24:39in some problem you're working on, this must be the result of some sort

0:24:39 > 0:24:43of random outside influences, it couldn't be internally generated.

0:24:43 > 0:24:45It wasn't an intrinsic part of the problem,

0:24:45 > 0:24:47it was some other thing impacting on it.

0:24:50 > 0:24:53Looked at from this point of view,

0:24:53 > 0:24:57the whole idea of self-organisation seemed absurd.

0:24:57 > 0:25:02The idea that patterns of the kind Turing and Belousov had found

0:25:02 > 0:25:04could appear of their own accord,

0:25:04 > 0:25:09without any outside influence, was a complete taboo.

0:25:12 > 0:25:15The only way for self-organisation to be accepted

0:25:15 > 0:25:21was for the domineering Newtonian view to collapse.

0:25:21 > 0:25:23But that seemed very unlikely.

0:25:26 > 0:25:28After all, by the late '60s it had delivered

0:25:28 > 0:25:32all the wonders of the modern age.

0:25:32 > 0:25:34Beautiful, beautiful.

0:25:34 > 0:25:36- Ain't that something? - Magnificent desolation.

0:25:39 > 0:25:43But then, at the same time as the moon mission,

0:25:43 > 0:25:47a small group of scientists, all ardent Newtonians,

0:25:47 > 0:25:52quite unexpectedly found something wasn't right.

0:25:52 > 0:25:55Not right at all.

0:25:58 > 0:26:01During the second half of the 20th century,

0:26:01 > 0:26:06a devil was found in the detail. A devil that would ultimately

0:26:06 > 0:26:11shatter the Newtonian dream and plunge us literally into chaos.

0:26:20 > 0:26:25Ironically, the events that forced scientists to take self-organisation

0:26:25 > 0:26:31seriously was the discovery of a phenomenon known as chaos.

0:26:33 > 0:26:37Chaos is one of the most over-used words in English, but in science

0:26:37 > 0:26:43it has a very specific meaning. It says that a system that is completely

0:26:43 > 0:26:48described by mathematical equations is more than capable

0:26:48 > 0:26:53of being unpredictable without any outside interference whatsoever.

0:26:55 > 0:26:59There's a widespread misapprehension that chaos is just somehow saying,

0:26:59 > 0:27:03the very familiar fact, that everything's complicated.

0:27:03 > 0:27:06I mean, the nitwit chaoticist in Jurassic Park,

0:27:06 > 0:27:08was under that confusion.

0:27:08 > 0:27:12It's something much simpler and yet much more complicated than that.

0:27:12 > 0:27:17It says, some very, very simple rules or equations,

0:27:17 > 0:27:21with nothing random in them, they're completely determined,

0:27:21 > 0:27:23we know everything about the rule,

0:27:23 > 0:27:29can have outcomes that are entirely unpredictable.

0:27:31 > 0:27:37Chaos is one of the most unwelcome discoveries in science.

0:27:37 > 0:27:41The man who forced the scientific community to confront it

0:27:41 > 0:27:45was an American meteorologist called Edward Lorenz.

0:27:45 > 0:27:49In the early 1960s he tried to find mathematical equations

0:27:49 > 0:27:52that could help predict the weather.

0:27:55 > 0:28:00Like all his contemporaries, he believed that in principle

0:28:00 > 0:28:03the weather system was no different to my orrery.

0:28:03 > 0:28:06A mechanical system that could be described

0:28:06 > 0:28:09and predicted mathematically.

0:28:10 > 0:28:11But he was wrong.

0:28:15 > 0:28:19When Lorenz wrote down what looked like perfectly simple mathematical

0:28:19 > 0:28:23equations to describe the movement of air currents,

0:28:23 > 0:28:26they didn't do what they were supposed to.

0:28:26 > 0:28:30They made no useful predictions whatsoever.

0:28:33 > 0:28:37It was as if the lightest breath of wind one day could make the

0:28:37 > 0:28:44difference a month later between a snowstorm and a perfectly sunny day.

0:28:46 > 0:28:51How can a simple system that works in the regular clockwork manner

0:28:51 > 0:28:54of my orrery become unpredictable?

0:28:54 > 0:28:57It's all down to how it's configured.

0:28:57 > 0:28:59How the gears are connected.

0:28:59 > 0:29:02In essence, under certain circumstances,

0:29:02 > 0:29:07the tiniest difference in the starting positions of the cogs,

0:29:07 > 0:29:10differences that are too small to measure,

0:29:10 > 0:29:15can get bigger and bigger with each turn of the handle.

0:29:15 > 0:29:18With each step in the process the system then moves

0:29:18 > 0:29:23further and further away from where you thought it was going.

0:29:23 > 0:29:28Lorenz captured this radical idea in an influential talk he gave called,

0:29:28 > 0:29:35"Does a flap of a butterfly's wings in Brazil set off a tornado in Texas?"

0:29:40 > 0:29:42It was a powerful and evocative image

0:29:42 > 0:29:46and within months a new phrase had entered our language.

0:29:46 > 0:29:48"The butterfly effect."

0:29:50 > 0:29:54And the butterfly effect, the hallmark of all chaotic systems,

0:29:54 > 0:29:56started turning up everywhere.

0:30:00 > 0:30:04In the early '70s, a young Australian called Robert May,

0:30:04 > 0:30:07was investigating a mathematical equation

0:30:07 > 0:30:12that modelled how animal populations changed over time.

0:30:12 > 0:30:16But here too lurked the dreaded butterfly effect.

0:30:16 > 0:30:20Immeasurably small changes to the rates at which the animals reproduced

0:30:20 > 0:30:23could sometimes have huge consequences

0:30:23 > 0:30:25on their overall population.

0:30:25 > 0:30:31Numbers could go up and down wildly for no obvious reason.

0:30:31 > 0:30:35The idea that a mathematical equation gave you the power

0:30:35 > 0:30:41to predict how a system will behave, was dead.

0:30:41 > 0:30:44In some sense this is the end of the Newtonian dream.

0:30:44 > 0:30:48When I was a graduate student, the belief was,

0:30:48 > 0:30:52as we got more and more computer power,

0:30:52 > 0:30:57we'd be able to solve ever more complicated sets of equations.

0:30:57 > 0:31:00But this said that's not necessarily true.

0:31:00 > 0:31:03You could have the simplest equations you can think of,

0:31:03 > 0:31:07with nothing random in them, you know everything.

0:31:07 > 0:31:12And yet, if they have behaviour

0:31:12 > 0:31:15that gives you chaotic solutions,

0:31:15 > 0:31:20then you can never know the starting point accurately enough.

0:31:23 > 0:31:29Centuries of scientific certainty dissolved in just a few short years.

0:31:29 > 0:31:34The truth of the clockwork universe turned out to be just an illusion.

0:31:34 > 0:31:37Something which had seemed a logical certainty,

0:31:37 > 0:31:40revealed itself merely as an act of faith.

0:31:40 > 0:31:44And what's worse, the truth had been staring us in the face all the time.

0:31:44 > 0:31:47Because chaos is everywhere.

0:31:51 > 0:31:55It seemed unpredictability was hard-wired

0:31:55 > 0:31:58into every aspect of the world we live in.

0:32:00 > 0:32:04The global climate could dramatically change

0:32:04 > 0:32:07in the course of a few short years.

0:32:07 > 0:32:09The stock markets could crash without warning.

0:32:09 > 0:32:14We could be wiped from the face of the planet overnight

0:32:14 > 0:32:18and there is nothing anyone could do about it.

0:32:23 > 0:32:28Unfortunately, I have to tell you that all of this is true.

0:32:28 > 0:32:31And yet to be scared of chaos is pointless.

0:32:33 > 0:32:37It's woven into the basic laws of physics.

0:32:37 > 0:32:42And we really all have to accept it as a fact of life.

0:32:42 > 0:32:47The idea of chaos really did have a big impact over a period of about 20

0:32:47 > 0:32:50or 30 years, because it changed the way everyone thought about

0:32:50 > 0:32:52what they were doing in science.

0:32:52 > 0:32:53It changed it to the point

0:32:53 > 0:32:56that they forgot that they'd ever believed otherwise.

0:32:56 > 0:33:02What chaos did was to show us that the possibilities inherent

0:33:02 > 0:33:07in the simple mathematics are much broader and much more general

0:33:07 > 0:33:12than you might imagine. And so a clockwork universe can

0:33:12 > 0:33:17nonetheless behave in the rich, complex way that we experience.

0:33:19 > 0:33:21The discovery of chaos

0:33:21 > 0:33:24was a real turning point in the history of science.

0:33:24 > 0:33:27As it tore down the Newtonian dream,

0:33:27 > 0:33:30scientists began to look more favourably at Turing and

0:33:30 > 0:33:34Belousov's work on spontaneous pattern formation.

0:33:34 > 0:33:38And perhaps more importantly, as they did so,

0:33:38 > 0:33:41they realised something truly astonishing.

0:33:41 > 0:33:44That there was a very deep and unexpected link.

0:33:44 > 0:33:47A truly cosmic connection

0:33:47 > 0:33:51between nature's strange power to self-organise

0:33:51 > 0:33:55and the chaotic consequences of the butterfly effect.

0:33:55 > 0:34:00Between them, Turing, Belousov, May and Lorenz,

0:34:00 > 0:34:05had all discovered different faces of just one really big idea.

0:34:08 > 0:34:12They discovered that the natural world could be deeply,

0:34:12 > 0:34:16profoundly, unpredictable. But the very same things that make it

0:34:16 > 0:34:21unpredictable also allow it to create pattern and structure.

0:34:21 > 0:34:24Order and chaos.

0:34:24 > 0:34:26It seems the two are more deeply linked

0:34:26 > 0:34:28than we could have ever imagined.

0:34:30 > 0:34:32So how is this possible?

0:34:32 > 0:34:36What do phenomena as apparently different as the patterns in

0:34:36 > 0:34:40Belousov's chemicals and the weather, have in common?

0:34:43 > 0:34:47First, though both systems behave in very complicated ways,

0:34:47 > 0:34:52they are both based on surprisingly simple mathematical rules.

0:34:56 > 0:35:00Secondly, these rules have a unique property.

0:35:00 > 0:35:05A property that's often referred to as coupling, or feedback.

0:35:10 > 0:35:15To show you what I mean, to show you both order and chaos can emerge

0:35:15 > 0:35:20on the their own from a simple system with feedback, I'm going to do

0:35:20 > 0:35:24what seems at first glance like a rather trivial experiment.

0:35:29 > 0:35:35This screen behind me is connected up to the camera that's filming me.

0:35:35 > 0:35:39But the camera in turn is filming me with the screen.

0:35:39 > 0:35:43This creates a loop with multiple copies of me

0:35:43 > 0:35:45appearing on the screen.

0:35:46 > 0:35:51This is a classic example of a feedback loop.

0:35:51 > 0:35:55We get a picture, in a picture, in a picture.

0:35:55 > 0:35:57At first it seems fairly predictable.

0:35:57 > 0:36:00But as we zoom the camera in

0:36:00 > 0:36:03some pretty strange things begin to happen.

0:36:05 > 0:36:08The first thing I notice is that the object I'm filming

0:36:08 > 0:36:13stops bearing much resemblance to what now appears on the screen.

0:36:17 > 0:36:22Small changes in the movement of the match become rapidly amplified

0:36:22 > 0:36:27as they loop round from the camera to the screen and back to the camera.

0:36:30 > 0:36:35So even though I can describe each step in the process mathematically,

0:36:35 > 0:36:39I still have no way of predicting how tiny changes

0:36:39 > 0:36:42in the flickering of the flame will end up in the final image.

0:36:46 > 0:36:49This is the butterfly effect in action.

0:36:55 > 0:36:58But now here comes the spooky bit.

0:37:00 > 0:37:03With just a slight tweak to the system,

0:37:03 > 0:37:09these strange and rather beautiful patterns begin to emerge.

0:37:11 > 0:37:16The same system, one that's based on simple rules with feedback,

0:37:16 > 0:37:19produces chaos and order.

0:37:27 > 0:37:31The same mathematics is generating chaotic behaviour

0:37:31 > 0:37:34and patterned behaviour.

0:37:34 > 0:37:38This changes completely how you think about all of this.

0:37:38 > 0:37:41The idea that there are regularities in nature and then,

0:37:41 > 0:37:44totally separately from them,

0:37:44 > 0:37:47are irregularities, and these are just two different things,

0:37:47 > 0:37:49is just not true.

0:37:49 > 0:37:51These are two ends of a spectrum of behaviour

0:37:51 > 0:37:55which can be generated by the same kind of mathematics.

0:37:55 > 0:38:00And it's the closest thing we have at the moment to the kind of true mathematics of nature.

0:38:01 > 0:38:06I think one of the great take home messages from Turing's work and from

0:38:06 > 0:38:10the discoveries in chemistry and biology and so on, is that

0:38:10 > 0:38:13ultimately, pattern formation seems to be woven, very, very deeply

0:38:13 > 0:38:17into the fabric of the universe. And it actually takes some very simple

0:38:17 > 0:38:20and familiar processes, like diffusion,

0:38:20 > 0:38:22like the rates of chemical reactions,

0:38:22 > 0:38:26and the interplay between them naturally gives rise to pattern.

0:38:26 > 0:38:30So pattern is everywhere, it's just waiting to happen.

0:38:32 > 0:38:36From the '70s on, more and more scientists

0:38:36 > 0:38:39began to embrace the concept that chaos

0:38:39 > 0:38:44and pattern are built into nature's most basic rules.

0:38:44 > 0:38:48But one scientist more than any other brought a fundamentally new

0:38:48 > 0:38:52understanding to this astonishing and often puzzling idea.

0:38:54 > 0:38:58He was a colourful character and something of a maverick.

0:38:58 > 0:39:01His name is Benoit Mandelbrot.

0:39:03 > 0:39:07Benoit Mandelbrot wasn't an ordinary child.

0:39:07 > 0:39:09He skipped the first two years of school

0:39:09 > 0:39:14and as a Jew in war-torn Europe his education was very disrupted.

0:39:14 > 0:39:18He was largely self-taught or tutored by relatives.

0:39:18 > 0:39:21He never formally learned the alphabet,

0:39:21 > 0:39:24or even multiplication beyond the five times table.

0:39:27 > 0:39:29But, like Alan Turing,

0:39:29 > 0:39:33Mandelbrot had a gift for seeing nature's hidden patterns.

0:39:33 > 0:39:37He could see rules where the rest of us see anarchy.

0:39:37 > 0:39:39He could see form and structure,

0:39:39 > 0:39:42where the rest of us just see a shapeless mess.

0:39:42 > 0:39:47And above all, he could see that a strange new kind of mathematics

0:39:47 > 0:39:49underpinned the whole of nature.

0:39:53 > 0:39:57Mandelbrot's lifelong quest was to find a simple mathematical basis

0:39:57 > 0:40:02for the rough and irregular shapes of the real world.

0:40:05 > 0:40:07Mandelbrot was working for IBM

0:40:07 > 0:40:10and he was not in the normal academic environment.

0:40:10 > 0:40:13And he was working on a pile of different problems

0:40:13 > 0:40:17about irregularities in nature, in the financial markets,

0:40:17 > 0:40:18all over the place.

0:40:18 > 0:40:21And I think at some point it dawned on him that everything

0:40:21 > 0:40:25he was doing seen to be really parts of the same big picture.

0:40:25 > 0:40:30And he was a sufficiently original and unusual person that

0:40:30 > 0:40:34he realised that pursuing this big picture was what

0:40:34 > 0:40:37- he really wanted to do.- To Mandelbrot, it seemed perverse that

0:40:37 > 0:40:42mathematicians had spent centuries contemplating idealised shapes

0:40:42 > 0:40:45like straight lines or perfect circles.

0:40:45 > 0:40:49And yet had no proper or systematic way of describing the rough

0:40:49 > 0:40:53and imperfect shapes that dominate the real world.

0:40:55 > 0:40:57Take this pebble.

0:40:58 > 0:41:01Is it a sphere or a cube?

0:41:01 > 0:41:03Or maybe a bit of both?

0:41:03 > 0:41:08And what about something much bigger? Look at the arch behind me.

0:41:08 > 0:41:12From a distance, it looks like a semi-circle.

0:41:12 > 0:41:15But up close, we see that it's bent and crooked.

0:41:17 > 0:41:19So what shape is it?

0:41:23 > 0:41:25Mandelbrot asked if there's something unique

0:41:25 > 0:41:29that defines all the varied shapes in nature.

0:41:29 > 0:41:33Do the fluffy surfaces of clouds, the branches in trees and rivers,

0:41:33 > 0:41:39the crinkled edges of shorelines, share a common mathematical feature?

0:41:39 > 0:41:42Well, they do.

0:41:42 > 0:41:47Underlying nearly all the shapes in the natural world is a mathematical

0:41:47 > 0:41:53principle known as self-similarity. This describes anything in which the

0:41:53 > 0:42:00same shape is repeated over and over again at smaller and smaller scales.

0:42:02 > 0:42:04A great example are the branches of trees.

0:42:04 > 0:42:08They fork and fork again, repeating that simple process

0:42:08 > 0:42:13over and over at smaller and smaller scales.

0:42:14 > 0:42:19The same branching principle applies in the structure of our lungs

0:42:19 > 0:42:23and the way our blood vessels are distributed throughout our bodies.

0:42:25 > 0:42:30It even describes how rivers split into ever smaller streams.

0:42:30 > 0:42:33And nature can repeat all sorts of shapes in this way.

0:42:35 > 0:42:38Look at this Romanesco broccoli.

0:42:38 > 0:42:42Its overall structure is made up of a series of repeating cones

0:42:42 > 0:42:46at smaller and smaller scales.

0:42:47 > 0:42:50Mandelbrot realised self-similarity

0:42:50 > 0:42:54was the basis of an entirely new kind of geometry.

0:42:54 > 0:42:58And he even gave it a name - fractal.

0:43:00 > 0:43:03Now, that's a pretty neat observation.

0:43:03 > 0:43:07But what if you could represent this property of nature in mathematics?

0:43:07 > 0:43:11What if you could capture its essence to draw a picture?

0:43:11 > 0:43:13What would that picture look like?

0:43:13 > 0:43:17Could you use a simple set of mathematical rules

0:43:17 > 0:43:20to draw an image that didn't look man-made?

0:43:20 > 0:43:23The answer would come from Mandelbrot.

0:43:23 > 0:43:26Who had taken a job at IBM in the late 1950s

0:43:26 > 0:43:30to gain access to its incredible computing power

0:43:30 > 0:43:35and pursue his obsession with the mathematics of nature.

0:43:35 > 0:43:38Armed with a new breed of super-computer,

0:43:38 > 0:43:42he began investigating a rather curious

0:43:42 > 0:43:44and strangely simple-looking equation

0:43:44 > 0:43:48that could be used to draw a very unusual shape.

0:43:48 > 0:43:52What I'm about to show you is one of the most remarkable

0:43:52 > 0:43:59mathematical images ever discovered. Epic doesn't really do it justice.

0:43:59 > 0:44:03This is the Mandelbrot set.

0:44:03 > 0:44:07It's been called the thumbprint of God.

0:44:07 > 0:44:10And when we begin to explore it, you'll understand why.

0:44:18 > 0:44:21Just as with the tree or the broccoli,

0:44:21 > 0:44:25the closer you study this picture, the more detail you see.

0:44:29 > 0:44:31Each shape within the set

0:44:31 > 0:44:34contains an infinite number of smaller shapes.

0:44:34 > 0:44:37Baby Mandelbrots that go on for ever.

0:44:43 > 0:44:48Yet all this complexity stems from just one incredibly simple equation.

0:44:49 > 0:44:53This equation has a very important property.

0:44:53 > 0:44:55It feeds back on itself.

0:44:56 > 0:45:02Like a video loop, each output becomes the input for the next go.

0:45:06 > 0:45:09This feedback means that an incredibly simple mathematical

0:45:09 > 0:45:14equation can produce a picture of infinite complexity.

0:45:31 > 0:45:33The really fascinating thing

0:45:33 > 0:45:38is that the Mandelbrot set isn't just a bizarre mathematical quirk.

0:45:38 > 0:45:42Its fractal property of being similar at all scales

0:45:42 > 0:45:46mirrors a fundamental ordering principle in nature.

0:45:51 > 0:45:57Turing's patterns, Belousov's reaction and Mandelbrot's fractals

0:45:57 > 0:46:02are all signposts pointing to a deep underlying natural principle.

0:46:05 > 0:46:08When we look at complexities in nature, we tend to ask,

0:46:08 > 0:46:10"Where did they come from?"

0:46:10 > 0:46:13There is something in our heads that says

0:46:13 > 0:46:15complexity does not arise out of simplicity.

0:46:15 > 0:46:19It must arise from something complicated. We conserve complexity.

0:46:19 > 0:46:22But what the mathematics in this whole area is telling us

0:46:22 > 0:46:27is that very simple rules naturally give rise to very complex objects.

0:46:27 > 0:46:30And so if you look at the object, it looks complex, and you think about

0:46:30 > 0:46:32the rule that generates it, it's simple.

0:46:32 > 0:46:35So the same thing is both complex and simple

0:46:35 > 0:46:38from two different points of view. And that means we have to rethink

0:46:38 > 0:46:42completely the relation between simplicity and complexity.

0:46:45 > 0:46:50Complex systems can be based on simple rules.

0:46:50 > 0:46:52That's the big revelation.

0:46:52 > 0:46:55And it's an astonishing idea.

0:46:56 > 0:46:59It seems to apply all over our world.

0:47:10 > 0:47:15Look at a flock of birds. Each bird obeys very simple rules.

0:47:15 > 0:47:19But the flock as a whole does incredibly complicated things.

0:47:19 > 0:47:25Avoiding obstacles, navigating the planet with no single leader

0:47:25 > 0:47:31or even conscious plan. But amazing though this flock's behaviour is,

0:47:31 > 0:47:34it's impossible to predict how it will behave.

0:47:36 > 0:47:39It never repeats exactly what it does,

0:47:39 > 0:47:42even in seemingly identical circumstances.

0:47:45 > 0:47:48It's just like the Belousov reaction.

0:47:48 > 0:47:53Each time you run it, the patterns produced are slightly different.

0:47:53 > 0:47:56They may look similar, but they are never identical.

0:47:56 > 0:48:01The same is true of video loops and sand dunes.

0:48:01 > 0:48:05We know they'll produce a certain kind of pattern,

0:48:05 > 0:48:08but we can't predict the exact shapes.

0:48:12 > 0:48:17The big question is, can nature's ability to turn simplicity

0:48:17 > 0:48:21into complexity in this mysterious and unpredictable way

0:48:21 > 0:48:24explain why life exists?

0:48:26 > 0:48:29Can it explain how a universe full of simple dust

0:48:29 > 0:48:32can turn into human beings?

0:48:33 > 0:48:37How inanimate matter can spawn intelligence?

0:48:39 > 0:48:43At first, you might think that this is beyond the remit of science.

0:48:43 > 0:48:46If nature's rules are really unpredictable,

0:48:46 > 0:48:48should we simply give up?

0:48:48 > 0:48:51Absolutely not. In fact, quite the opposite.

0:48:54 > 0:48:58Fittingly, the answer to this problem lies in the natural world.

0:48:58 > 0:49:03All around us, there exists a process that engineers

0:49:03 > 0:49:05these unpredictable complex systems

0:49:05 > 0:49:10and hones them to perform almost miraculous tasks.

0:49:12 > 0:49:15The process is called evolution.

0:49:17 > 0:49:20Evolution has built on these patterns.

0:49:20 > 0:49:22It's taken them as the raw ingredients.

0:49:22 > 0:49:26It's combined them together in various ways,

0:49:26 > 0:49:29experimented to see what works and what doesn't,

0:49:29 > 0:49:34kept the things that do work and then built on that.

0:49:34 > 0:49:36It's a completely unconscious process,

0:49:36 > 0:49:38but basically that's what's happening.

0:49:38 > 0:49:41Everywhere you look, you can see evolution

0:49:41 > 0:49:45using nature's self-organising patterns.

0:49:45 > 0:49:50Our hearts use Belousov-type reactions to regulate how they beat.

0:49:50 > 0:49:54Our blood vessels are organised like fractals.

0:49:54 > 0:50:00Even our brain cells interact according to simple rules.

0:50:00 > 0:50:05The way evolution refines and enriches complex systems

0:50:05 > 0:50:09is one of the most intriguing ideas in recent science.

0:50:12 > 0:50:15My interest in my PhD research in complex systems was to see

0:50:15 > 0:50:18how complex systems interact with evolution.

0:50:18 > 0:50:22So, on the one hand you have systems that almost organise themselves

0:50:22 > 0:50:26as complex systems, so they exhibit order that you wouldn't expect,

0:50:26 > 0:50:30but on the other hand, you still have to have evolution interact with

0:50:30 > 0:50:33that to create something that is truly adapted to the environment.

0:50:33 > 0:50:38Evolution's mindless, yet creative, power to develop

0:50:38 > 0:50:42and shape complex systems is indeed incredible.

0:50:43 > 0:50:46But it operates on a cosmic timescale.

0:50:48 > 0:50:51From the first life on Earth, to us walking about,

0:50:51 > 0:50:55took in the region of 3.5 billion years.

0:50:56 > 0:50:59But we now have in our hands

0:50:59 > 0:51:04a device that can mimic this process on a much shorter timescale.

0:51:04 > 0:51:08What is the invention I'm talking about?

0:51:08 > 0:51:12Well, there's a good chance you've been sitting in front of one all day.

0:51:13 > 0:51:16It is, of course, the computer.

0:51:21 > 0:51:27Computers today can churn through trillions of calculations per second.

0:51:27 > 0:51:30And that gives them the power to do something very special.

0:51:30 > 0:51:34They can simulate evolution.

0:51:35 > 0:51:40More precisely, computers can use the principles of evolution to shape

0:51:40 > 0:51:44and refine their own programs, in the same way the natural world

0:51:44 > 0:51:49uses evolution to shape and refine living organisms.

0:51:49 > 0:51:55And today, computer scientists find that this evolved software

0:51:55 > 0:52:00can solve problems that would be beyond the smartest of humans.

0:52:00 > 0:52:04One thing that we found particularly in our original research is how

0:52:04 > 0:52:08powerful evolution is as a system, as an algorithm, to create something

0:52:08 > 0:52:12that is very complex and to create something that is very adaptive.

0:52:12 > 0:52:16Torsten and his team's goal was nothing less

0:52:16 > 0:52:18than to use computerised evolution

0:52:18 > 0:52:23to create a virtual brain that would control a virtual body.

0:52:24 > 0:52:29To begin with, they created 100 random brains.

0:52:29 > 0:52:31As you can see, they weren't up to much.

0:52:33 > 0:52:35Evolution then took over.

0:52:35 > 0:52:40The computer selected the brains that were slightly better

0:52:40 > 0:52:43at moving their bodies and got them to breed.

0:52:45 > 0:52:49The algorithm then takes those individuals that do the best

0:52:49 > 0:52:51and it allows them to create offspring.

0:52:53 > 0:52:56The best movers of the next generation

0:52:56 > 0:52:59were then bred together and so on and on.

0:52:59 > 0:53:03Amazingly, after just 10 generations,

0:53:03 > 0:53:08although they're still a bit unsteady, the figures could walk.

0:53:09 > 0:53:11Eventually, miraculously, you actually end up

0:53:11 > 0:53:14with something that works. The slightly scary thing

0:53:14 > 0:53:17is you don't know why it works and how it works.

0:53:17 > 0:53:20You look at that brain and you have no idea actually what's going on

0:53:20 > 0:53:23because evolution has optimised it automatically.

0:53:26 > 0:53:31In 20 generations, evolution had turned this...

0:53:31 > 0:53:33..into this.

0:53:36 > 0:53:41But these evolved computer beings soon went far beyond just walking.

0:53:44 > 0:53:46They evolved to do things

0:53:46 > 0:53:49that really are impossible to program conventionally.

0:53:53 > 0:53:57They react realistically to unexpected events.

0:53:57 > 0:54:00Like being hit or falling over.

0:54:03 > 0:54:07Even though we programmed these algorithms, what actually happens

0:54:07 > 0:54:10when it unfolds live, we don't control any more

0:54:10 > 0:54:12and things happen that we never expected.

0:54:12 > 0:54:14And it's quite a funny feeling

0:54:14 > 0:54:18that you create these algorithms but then they do their own thing.

0:54:24 > 0:54:28An unthinking process of evolutionary trial and error

0:54:28 > 0:54:34has created these virtual creatures that can move and react in real time.

0:54:39 > 0:54:43What we're seeing here is fantastic experimental evidence

0:54:43 > 0:54:47for the creative power of systems based on simple rules.

0:54:57 > 0:55:02Watching how computers can unconsciously evolve programs

0:55:02 > 0:55:05to do things that no human could consciously program

0:55:05 > 0:55:11is a fantastic example of the power of self-organisation.

0:55:11 > 0:55:14It demonstrates that evolution is itself

0:55:14 > 0:55:18just like the other systems we've encountered.

0:55:18 > 0:55:21One based on simple rules and feedback.

0:55:21 > 0:55:25From which complexity spontaneously emerges.

0:55:26 > 0:55:30Think about it. The simple rule is that the organism

0:55:30 > 0:55:36must replicate with a few random mutations now and again.

0:55:36 > 0:55:39The feedback comes from the environment

0:55:39 > 0:55:43which favours the mutations that are best suited to it.

0:55:43 > 0:55:47The result is ever-increasing complexity,

0:55:47 > 0:55:51produced without thought or design.

0:55:52 > 0:55:55The interesting thing is that one can move up

0:55:55 > 0:55:58to a higher level of organisation. Once you have organisms

0:55:58 > 0:56:02that actually have patterns on them, these can be selected for

0:56:02 > 0:56:07or selected against by processes which are essentially feedbacks.

0:56:07 > 0:56:11And so evolution itself, the whole Darwinian scheme,

0:56:11 > 0:56:14is, in a sense, Turing again

0:56:14 > 0:56:17with feedbacks happening through different processes.

0:56:19 > 0:56:21And that's the essence of this story.

0:56:21 > 0:56:26Unthinking, simple rules have the power to create

0:56:26 > 0:56:30amazingly complex systems without any conscious thought.

0:56:31 > 0:56:36In that sense, these computer beings are self-organised systems,

0:56:36 > 0:56:41just like the one Belousov observed happening in his chemicals.

0:56:42 > 0:56:46Just like the ones in sand dunes and the Mandelbrot sets,

0:56:46 > 0:56:51in our lungs, our hearts, in weather

0:56:51 > 0:56:53and in the geography of our planet.

0:56:53 > 0:56:58Design does not need an active, interfering designer.

0:56:58 > 0:57:02It's an inherent part of the universe.

0:57:06 > 0:57:10One of the things that makes people so uncomfortable about this idea of,

0:57:10 > 0:57:15if you will, spontaneous pattern formation, is that somehow or other

0:57:15 > 0:57:19you don't need a creator. But perhaps a really clever designer,

0:57:19 > 0:57:22what he would do, is to kind of treat the universe

0:57:22 > 0:57:26like a giant simulation, where you set some initial condition

0:57:26 > 0:57:30and just let the whole thing spontaneously happen

0:57:30 > 0:57:32in all of its wonder and all of its beauty.

0:57:35 > 0:57:39The mathematics of pattern formation shows that the same kind of pattern

0:57:39 > 0:57:42can show up in an enormous range of different physical,

0:57:42 > 0:57:46chemical, biological systems. Somewhere deep down inside,

0:57:46 > 0:57:49it's happening for the same mathematical reason.

0:57:49 > 0:57:53Implicit in those facts are these beautiful patterns

0:57:53 > 0:57:55that we see everywhere.

0:57:55 > 0:57:58This, I think, is a mind-blowing thought.

0:58:07 > 0:58:12So, what is the ultimate lesson we can take from all this?

0:58:12 > 0:58:15Well, it's that all the complexity of the universe,

0:58:15 > 0:58:18all its infinite richness,

0:58:18 > 0:58:23emerges from mindless simple rules, repeated over and over again.

0:58:23 > 0:58:27But remember, powerful though this process is,

0:58:27 > 0:58:30it's also inherently unpredictable.

0:58:30 > 0:58:36So although I can confidently tell you that the future will be amazing,

0:58:36 > 0:58:40I can also say, with scientific certainty,

0:58:40 > 0:58:43that I have no idea what it holds.

0:59:04 > 0:59:07Subtitles by Red Bee Media Ltd

0:59:07 > 0:59:10E-mail subtitling@bbc.co.uk