0:00:09 > 0:00:14Where would any of us be without a computer?
0:00:14 > 0:00:17From playing games, to developing medicine,
0:00:17 > 0:00:19to watching movies, or exploring Mars,
0:00:19 > 0:00:23computing's influence is continually breaking new ground.
0:00:23 > 0:00:24It may interest you to know
0:00:24 > 0:00:27that computers have also been ever present
0:00:27 > 0:00:31in our parents' and even our grandparents' lives.
0:00:31 > 0:00:35And it wasn't the Americans or the Japanese that first built them,
0:00:35 > 0:00:37it was a British Post Office engineer called Tommy Flowers,
0:00:37 > 0:00:41way back in 1943.
0:00:41 > 0:00:43Now, I bet you didn't think it would look like
0:00:43 > 0:00:45it had been knocked up in a back garden shed,
0:00:45 > 0:00:48but you should always respect your elders,
0:00:48 > 0:00:52and Colossus is as old and as big as they come.
0:00:52 > 0:00:55Colossus was one of the first computers, yes.
0:00:55 > 0:00:59And we can talk about it in academic or engineering terms.
0:00:59 > 0:01:01But it was probably the most significant computer
0:01:01 > 0:01:05because it had a worldwide impact.
0:01:05 > 0:01:09It shortened the war, together with other activities at Bletchley Park,
0:01:09 > 0:01:11by at least two years.
0:01:11 > 0:01:15It saved hundreds of thousands of, not only Allied lives,
0:01:15 > 0:01:17but German lives too.
0:01:17 > 0:01:21So, in terms of the impact of a computer,
0:01:21 > 0:01:24this machine is certainly at the very, very top.
0:01:24 > 0:01:27Colossus was built to solve a colossal problem.
0:01:27 > 0:01:30In World War II, that problem was the Nazis.
0:01:30 > 0:01:33Hitler had overrun Europe and was communicating to his generals
0:01:33 > 0:01:36using highly encrypted messages.
0:01:36 > 0:01:40What we desperately needed to do was find out what he was saying.
0:01:40 > 0:01:44You have to imagine a situation in the middle of a world war,
0:01:44 > 0:01:47where you can hear your enemies sending critical messages,
0:01:47 > 0:01:50but packaged in a cipher.
0:01:50 > 0:01:54A cipher is a mathematical process, or a logical process,
0:01:54 > 0:01:58that is used to disguise the characters in your message.
0:01:58 > 0:02:00A bit like a padlock.
0:02:00 > 0:02:03You can lock it up, and unlock it at the other end,
0:02:03 > 0:02:06and the message is sent securely.
0:02:06 > 0:02:10Even though all this was taking place over 60 years ago,
0:02:10 > 0:02:14a lot of information is still exchanged in the same way now.
0:02:14 > 0:02:17We live in an age of the transfer of data.
0:02:17 > 0:02:19We buy things online.
0:02:19 > 0:02:21We use mobile phones.
0:02:21 > 0:02:24Data is being moved at all sorts of times.
0:02:24 > 0:02:28Every time it's moved, it has to be moved securely.
0:02:28 > 0:02:32So, today, we use ciphers to package our data
0:02:32 > 0:02:34and to give it to somebody else securely.
0:02:34 > 0:02:39And, I'm afraid, there are always people trying to break those ciphers.
0:02:41 > 0:02:45So, the people who were able to break the German codes
0:02:45 > 0:02:48were essentially 1940s-style hackers?
0:02:48 > 0:02:53We could call the codebreakers one of the early hackers, yes.
0:02:53 > 0:02:58Their job was to take apart somebody else's cipher,
0:02:58 > 0:03:00and look inside, and gain an insight
0:03:00 > 0:03:04to the information that they were transferring.
0:03:04 > 0:03:05Unbelievably, at one stage,
0:03:05 > 0:03:08all this was being done without the aid of a computer.
0:03:08 > 0:03:13An incredible achievement, but also incredibly slow.
0:03:13 > 0:03:16To spend weeks cracking a code with pen and paper
0:03:16 > 0:03:18might mean you knew what your enemies were up to.
0:03:18 > 0:03:20But by the time you found out
0:03:20 > 0:03:23they'd already have carried out their plans.
0:03:23 > 0:03:26However, by programming Colossus to do this task in hours,
0:03:26 > 0:03:30the Allies managed to stay one step ahead of the game.
0:03:30 > 0:03:32What they got so right about Colossus
0:03:32 > 0:03:37was keeping their eye on the problem that they had to solve.
0:03:37 > 0:03:41It's a key skill that anybody who has to program a computer today
0:03:41 > 0:03:43still has to have.
0:03:43 > 0:03:45And, by telling a computer to process a complex task,
0:03:45 > 0:03:50we can increase the speed and accuracy a problem can be solved in.
0:03:50 > 0:03:51So, even today,
0:03:51 > 0:03:56we have to think about what the computer's being used for.
0:03:56 > 0:03:59Do you need speed? Do you need accuracy? Do you need reliability?
0:03:59 > 0:04:04Those factors all come together, to make the perfect machine.
0:04:04 > 0:04:08Colossus needed all those things to efficiently break the Nazi codes,
0:04:08 > 0:04:12and the people who built it, programmed it and used it,
0:04:12 > 0:04:15would have been acutely aware of its precise purpose and abilities.
0:04:15 > 0:04:20If we look at Colossus, we can see the data flow.
0:04:20 > 0:04:23We can hear the mechanism.
0:04:23 > 0:04:26We can understand, perhaps, using all our senses,
0:04:26 > 0:04:28what this machine is doing.
0:04:28 > 0:04:31But we have to remember that, as clever as they are,
0:04:31 > 0:04:34they only reflect what we tell them to do.
0:04:34 > 0:04:38We need someone who has an insight into solving the problem.
0:04:38 > 0:04:42We need someone who can express that as a series of instructions.
0:04:42 > 0:04:46And, ultimately, get the machine to reflect us as human beings.
0:04:46 > 0:04:50And the programmers who can rise to this sort of challenge
0:04:50 > 0:04:51in today's day and age
0:04:51 > 0:04:55will be able to embrace infinite computing possibilities,
0:04:55 > 0:04:59compared to the pioneers who built and first used Colossus.
0:04:59 > 0:05:03The principle of the computer is actually flexibility,
0:05:03 > 0:05:05and being general purpose.
0:05:05 > 0:05:07Colossus isn't general purpose.
0:05:07 > 0:05:10And maybe what we're doing is moving now to a world where
0:05:10 > 0:05:14computers can be turned to do lots of different things,
0:05:14 > 0:05:19simply by changing the instructions, the program, inside them.
0:05:19 > 0:05:25That's what makes them unique in the world of machines.
0:05:25 > 0:05:28And, with this kind of potential at our fingertips,
0:05:28 > 0:05:30it's perhaps not so surprising just how many jobs
0:05:30 > 0:05:34we're now programming computers to do on our behalf.
0:05:35 > 0:05:38However, before we can really start to get to grips
0:05:38 > 0:05:41with the amazing capabilities of these machines,
0:05:41 > 0:05:46we first need to understand the machinery that we are working with.
0:05:46 > 0:05:49Computers are not the most animate machines.
0:05:49 > 0:05:53Looking at them, you'd barely believe their hardware was capable
0:05:53 > 0:05:55of such wondrously diverse and clever tasks.
0:05:55 > 0:05:59Their interiors, this hardware, is as unknown quantity to us
0:05:59 > 0:06:03as, say, the inside of a car.
0:06:03 > 0:06:05We rarely delve inside, but, delve inside, we must.
0:06:05 > 0:06:08So let's lift the bonnet of your average games console,
0:06:08 > 0:06:10to give us a sneak peek
0:06:10 > 0:06:15at how this internal architecture works so hard in our favour.
0:06:15 > 0:06:19The UK has the largest videogame industry in Europe.
0:06:19 > 0:06:21Zoe Mode, based in Brighton,
0:06:21 > 0:06:24specialise in leading dance titles, like Zumba.
0:06:24 > 0:06:27And they are the first to admit the important role
0:06:27 > 0:06:30that hardware plays in their day-to-day work.
0:06:30 > 0:06:32The hardware we're making the game for
0:06:32 > 0:06:34defines what the game can be,
0:06:34 > 0:06:37not just in terms of the way it looks,
0:06:37 > 0:06:41but also in terms of the way that you interact with the games.
0:06:41 > 0:06:45All computational devices, from a laptop to a smartphone,
0:06:45 > 0:06:49essentially rely on the following key hardware components to work:
0:06:56 > 0:06:59So, if we are starting with a game, it has to be uploaded first,
0:06:59 > 0:07:03and for us to do that, we need to utilise the memory.
0:07:03 > 0:07:09On all computational devices, memory falls into two distinct areas.
0:07:09 > 0:07:13ROM, or read-only memory, is permanently stored memory.
0:07:13 > 0:07:16It's like a bookshelf with instructions that's always there.
0:07:16 > 0:07:19When you turn on your console,
0:07:19 > 0:07:23it's this internally stored ROM that helps start up the machine.
0:07:23 > 0:07:27But it's also ROM you insert in order to play the game.
0:07:27 > 0:07:32And this data is transferred from your DVD-ROM, into your RAM.
0:07:32 > 0:07:34Things are stored in RAM,
0:07:34 > 0:07:38in order to make it quicker for the CPU to take those things out.
0:07:38 > 0:07:40So, for games consoles,
0:07:40 > 0:07:44random access memory's job is to temporarily store programs and data
0:07:44 > 0:07:48that the console uses to let you play the game.
0:07:48 > 0:07:49In all computational devices,
0:07:49 > 0:07:53random access memory is described as "volatile".
0:07:53 > 0:07:56If you were in the middle of playing, and there was a power cut,
0:07:56 > 0:07:58you'd have to start all over again.
0:07:58 > 0:08:02Basically, the more memory you have, the better looking the game is,
0:08:02 > 0:08:04the more sounds there are going to be,
0:08:04 > 0:08:06the more inputs it can understand.
0:08:06 > 0:08:08It's an important part of the computer's architecture.
0:08:08 > 0:08:11And, with our game loaded up and ready to go,
0:08:11 > 0:08:14we'll need to give it some instructions, or "input".
0:08:14 > 0:08:18Inputs relay operating instructions back into the computer,
0:08:18 > 0:08:20where they can be processed.
0:08:20 > 0:08:22They can be numerous things.
0:08:22 > 0:08:25A mouse, a keyboard, joysticks, joypads, touchscreens,
0:08:25 > 0:08:28button presses on a teller machine.
0:08:28 > 0:08:30Even your own voice.
0:08:30 > 0:08:31With regards to this game,
0:08:31 > 0:08:34the input is actually a sensor
0:08:34 > 0:08:38which combines a web camera and an infrared camera,
0:08:38 > 0:08:43which can do lots of clever things, like pick out human beings.
0:08:43 > 0:08:46Your body is the input.
0:08:46 > 0:08:49Then it makes a skeleton of that and tracks your movement,
0:08:49 > 0:08:51which is a lot of information.
0:08:51 > 0:08:54So, the CPU for this console needs to be very powerful
0:08:54 > 0:08:56to deal with all that information,
0:08:56 > 0:08:58to make gameplay interesting and fun.
0:08:58 > 0:09:00The CPU, or central processing unit,
0:09:00 > 0:09:03could be described as the brains of the operation.
0:09:03 > 0:09:07It's the device within all computers that takes the input information,
0:09:07 > 0:09:09decides what's gone on,
0:09:09 > 0:09:11and processes a command using the memory,
0:09:11 > 0:09:14to give you that all-important feedback.
0:09:14 > 0:09:16You can only do one thing at a time.
0:09:16 > 0:09:17It fetches an instruction,
0:09:17 > 0:09:20it will execute that instruction,
0:09:20 > 0:09:24and then it will move onto the next instruction and do that over again.
0:09:24 > 0:09:26So, the faster your CPU,
0:09:26 > 0:09:29the more instructions you can do within a period of time.
0:09:29 > 0:09:32# Right hand in the air, left hand in the air... #
0:09:32 > 0:09:36And the more instructions your CPU processes, for this game at least,
0:09:36 > 0:09:41the more reactive and immersive your game experience will be.
0:09:41 > 0:09:46Predominantly with Zumba, the output device that we are using is the TV.
0:09:46 > 0:09:49The TV provides the visuals,
0:09:49 > 0:09:52it provides feedback to you to let you know how you're doing.
0:09:52 > 0:09:56It also provides the music for you to dance along to.
0:09:56 > 0:09:58So the output device is really key
0:09:58 > 0:10:00for your understanding of what's going on,
0:10:00 > 0:10:02and your interaction with the game.
0:10:02 > 0:10:05Output devices are perhaps the ones we notice the most.
0:10:05 > 0:10:09They project the results of the computer processing to the user.
0:10:09 > 0:10:11They can be speakers for sound output,
0:10:11 > 0:10:13a monitor for visuals,
0:10:13 > 0:10:15or, less important for a dancing game, a printer.
0:10:15 > 0:10:17We're seeing technology developed now
0:10:17 > 0:10:20where output is displayed on glasses,
0:10:20 > 0:10:25or even displayed on contact lenses, so you can put things in your eyes
0:10:25 > 0:10:27and see things in front
0:10:27 > 0:10:32And that's a really exciting thing for games in the future.
0:10:32 > 0:10:35The capabilities of digital electronic devices
0:10:35 > 0:10:38are constantly increasing over time.
0:10:38 > 0:10:41Massive increases in processing speed and memory capacity
0:10:41 > 0:10:46now represent incredible potential in all areas of computing.
0:10:49 > 0:10:50It's very important for us
0:10:50 > 0:10:54to understand the capabilities of the machines,
0:10:54 > 0:10:56of the console that the game is going to be played on,
0:10:56 > 0:10:59because we wanted to know where our limits were,
0:10:59 > 0:11:02but also how far we could push things.
0:11:02 > 0:11:06But also, we need to know how the player's going to interact.
0:11:06 > 0:11:09That's a really important thing, because that's where the game is,
0:11:09 > 0:11:12that's where the fun is, the player experience is all about fun.
0:11:12 > 0:11:14And that is driven by the hardware,
0:11:14 > 0:11:18and the limitations of the hardware decides on what we can do
0:11:18 > 0:11:21to entertain the player.
0:11:21 > 0:11:24With the global games industry expected to keep on growing,
0:11:24 > 0:11:26it's not hard to understand
0:11:26 > 0:11:30just how important it is for the next generation of games designers
0:11:30 > 0:11:33to appreciate how these incredible machines work.
0:11:38 > 0:11:40Three stars?!
0:11:44 > 0:11:46It's not just the games industry that's manipulating
0:11:46 > 0:11:50the ever-increasing power of computers in our favour.
0:11:50 > 0:11:54They are playing an ingenious role in space exploration too.
0:11:55 > 0:11:59Mars, the final frontier.
0:11:59 > 0:12:01Well, certainly our nearest frontier,
0:12:01 > 0:12:03and even then we're talking of, at best,
0:12:03 > 0:12:0635 million miles away of nearest frontier.
0:12:06 > 0:12:09That said, it's still the best and most likely place
0:12:09 > 0:12:11we'll be living on after Earth.
0:12:11 > 0:12:14And huge efforts have, and are, being made
0:12:14 > 0:12:19to land robots there to research that very possibility.
0:12:19 > 0:12:20But, with no maps to work off,
0:12:20 > 0:12:24and GPS a technology that's only available back on planet Earth,
0:12:24 > 0:12:29it's proving very hard to tell these robots where they should be going.
0:12:30 > 0:12:35It's a problem that's been engaging space engineers for many years.
0:12:36 > 0:12:40Currently, NASA has at least two rovers on Mars.
0:12:40 > 0:12:42But the real problem that those have is
0:12:42 > 0:12:43that they don't think for themselves.
0:12:43 > 0:12:46All the thinking is done by the scientists on Earth.
0:12:46 > 0:12:49And it takes a very long time to send a command,
0:12:49 > 0:12:52and then get a response back.
0:12:52 > 0:12:57Opportunity has only gone 21 miles in eight years.
0:12:57 > 0:13:02And Spirit has only gone five miles in eight years.
0:13:02 > 0:13:09To travel around on Mars just is a very, very slow, painstaking process.
0:13:09 > 0:13:12Meanwhile, back on Earth, at this lab just outside Oxford,
0:13:12 > 0:13:15the UK is pioneering the idea that, one day,
0:13:15 > 0:13:20robot explorers on Mars will be able to navigate themselves.
0:13:20 > 0:13:26It's a natural progress of robotics and artificial intelligence.
0:13:26 > 0:13:29Nowadays, we have better sensors, faster computers.
0:13:29 > 0:13:32We have all the experience previous programmers have done.
0:13:32 > 0:13:36We have all the experience from previous NASA missions.
0:13:36 > 0:13:38I think we just needed all this background knowledge
0:13:38 > 0:13:41and the availability of new cutting-edge hardware,
0:13:41 > 0:13:43to be able to accomplish this.
0:13:43 > 0:13:48Having this prior knowledge of where their robot was travelling to
0:13:48 > 0:13:50has given programmers a valuable head start
0:13:50 > 0:13:55in being able to design and execute a program that works.
0:13:55 > 0:13:59The rover needs to find its way around, using local reference points.
0:13:59 > 0:14:02And it does this, typically,
0:14:02 > 0:14:06from looking at local features which are fairly close to it.
0:14:06 > 0:14:08So, looking for rocks that can be recognised,
0:14:08 > 0:14:13it goes from one rock to another, as it travels around.
0:14:13 > 0:14:16Every time we encounter an obstacle,
0:14:16 > 0:14:21or some zone which we haven't seen before,
0:14:21 > 0:14:23which the computer is uncertain about,
0:14:23 > 0:14:26it has to make a decision based on all the input it gets.
0:14:26 > 0:14:28So it applies logic to the inputs,
0:14:28 > 0:14:31and converts them into the appropriate outputs.
0:14:31 > 0:14:35And the appropriate "if then, or else" logic commands
0:14:35 > 0:14:37that a navigation system might execute, would simply be,
0:14:37 > 0:14:42"stop, reverse, go right, go left, or continue forwards."
0:14:42 > 0:14:46Depending, obviously, on what it finds in front of it.
0:14:46 > 0:14:48By using a camera,
0:14:48 > 0:14:52the machine is able to assess the hazards in front of it.
0:14:52 > 0:14:54Choose a route around it,
0:14:54 > 0:14:57and then get to where it knows it's got to go to,
0:14:57 > 0:15:00just by using that simple information.
0:15:00 > 0:15:03Its tasks are all logical task.
0:15:03 > 0:15:06And, although this basic decision-making rings true,
0:15:06 > 0:15:08new state-of-the-art visual sensors
0:15:08 > 0:15:12are feeding back incredible detail to the computer.
0:15:12 > 0:15:16Programmers need to be able to apply logic to all of this information.
0:15:16 > 0:15:20I think the hardest part of this project
0:15:20 > 0:15:26is just the huge number of inputs you get from a real environment.
0:15:26 > 0:15:30Computer programs are really good at making logical decisions
0:15:30 > 0:15:32when the number of inputs is limited.
0:15:32 > 0:15:34But, when you're dealing with the real world,
0:15:34 > 0:15:37you can encounter so many different obstacles,
0:15:37 > 0:15:40you just never know what will be next.
0:15:40 > 0:15:42So it's vitally important that the team of scientists here
0:15:42 > 0:15:47work out programs that can deal with all that Mars might throw at them.
0:15:47 > 0:15:52It's absolutely crucial the programming is right for this mission
0:15:52 > 0:15:54because there's no chance of repairing it.
0:15:54 > 0:15:58So if we allow the machine to make all the decisions on its own,
0:15:58 > 0:15:59which is what we are trying to do,
0:15:59 > 0:16:02then all those decisions have to be right
0:16:02 > 0:16:04because, if it makes the wrong decision,
0:16:04 > 0:16:07then it could be catastrophic, and we could lose the rover.
0:16:10 > 0:16:12And, with NASA's latest Mars rover
0:16:12 > 0:16:16planning to touch down in August 2012,
0:16:16 > 0:16:19costing a staggering 2 billion,
0:16:19 > 0:16:22it's not something you want to get wrong.
0:16:22 > 0:16:26This is a massive leap forward, compared to previous technology.
0:16:26 > 0:16:30This would enable Mars rovers to go much further,
0:16:30 > 0:16:34and get to targets which are in parts of Mars
0:16:34 > 0:16:36where landing would be impossible.
0:16:36 > 0:16:40And, although navigating around Mars is, without doubt,
0:16:40 > 0:16:43the prime objective, the team designing this navigation system
0:16:43 > 0:16:47are more than aware of potential applications back here on Earth.
0:16:47 > 0:16:51This work has never been done by anybody looking for
0:16:51 > 0:16:55sufficient brains in a machine, that it can travel itself
0:16:55 > 0:17:00for six kilometres without any intervention from the ground.
0:17:00 > 0:17:02The technology which we are developing here can be
0:17:02 > 0:17:04directly used on Earth,
0:17:04 > 0:17:08in places, for example, where GPS is not available.
0:17:08 > 0:17:11Computing devices all operate
0:17:11 > 0:17:15entirely on instructions prepared by someone who has done the thinking,
0:17:15 > 0:17:17and reduced the problem to a point
0:17:17 > 0:17:20where logical decisions can deliver the correct answer.
0:17:20 > 0:17:23How you can use this programming know-how
0:17:23 > 0:17:27depends on what problem you want to solve.
0:17:27 > 0:17:30The link between computing and robotics
0:17:30 > 0:17:32is one many would expect to encounter.
0:17:32 > 0:17:35However, computers increasingly play a vital role
0:17:35 > 0:17:37in our very own health and well-being.
0:17:40 > 0:17:42In recent years, biologists have made
0:17:42 > 0:17:45a massive scientific breakthrough in discovering, for the first time,
0:17:45 > 0:17:49how to sequence species' entire genetic code.
0:17:49 > 0:17:52We can see DNA, you can see it by eye.
0:17:52 > 0:17:56You can't decode it, you can't understand what it's saying.
0:17:56 > 0:17:59It's only by sequencing that DNA, you can decode it,
0:17:59 > 0:18:01you can understand the messages, the sequences,
0:18:01 > 0:18:05the genes that are encoded by that DNA.
0:18:05 > 0:18:09What sequencing a species' entire DNA into a genome means
0:18:09 > 0:18:12is that scientists are effectively now capable
0:18:12 > 0:18:15of examining the building blocks of life.
0:18:15 > 0:18:17Sequencing gives you a glimpse,
0:18:17 > 0:18:20it's actually a very privileged view
0:18:20 > 0:18:25of the instruction manual for an organism.
0:18:25 > 0:18:29To give you some idea of the challenge computer programmers face,
0:18:29 > 0:18:34a single genome can be composed of over three billion base pairs of data.
0:18:34 > 0:18:35In computing terms,
0:18:35 > 0:18:38that would equate to over four gigabytes of storage space.
0:18:38 > 0:18:41Or, if you were to read it out loud,
0:18:41 > 0:18:45it would take you over nine years of continuous reading.
0:18:47 > 0:18:49Using the current sequencing technologies,
0:18:49 > 0:18:51we generated, in six months,
0:18:51 > 0:18:55more data than we produced in the previous 10 years.
0:18:55 > 0:18:58This tells you the pace, the development of both sequencing,
0:18:58 > 0:19:02and it also gives you an idea of how computing has had to keep up
0:19:02 > 0:19:04with that pace of sequencing.
0:19:04 > 0:19:08But to explore all the possibilities that reading this data gives them,
0:19:08 > 0:19:12scientists have needed to be able to compare thousands and thousands
0:19:12 > 0:19:14of separate individual codes.
0:19:14 > 0:19:20That's so much data, it's making my head hurt just thinking about it!
0:19:20 > 0:19:21Both the processing power,
0:19:21 > 0:19:24and the memory for storing all the data we are generating,
0:19:24 > 0:19:26is absolutely huge.
0:19:26 > 0:19:27And, without that,
0:19:27 > 0:19:31we wouldn't even be able to entertain many of the projects
0:19:31 > 0:19:33that we are now initiating.
0:19:33 > 0:19:35We wouldn't even be to start those projects.
0:19:35 > 0:19:37So, whilst it's biologists
0:19:37 > 0:19:40who initially have been able to create the data,
0:19:40 > 0:19:43it's people with the knowledge and understanding
0:19:43 > 0:19:45of how to manipulate some serious computer hardware
0:19:45 > 0:19:51that has allowed them to analyse it efficiently, and effectively.
0:19:52 > 0:19:56Here, you are looking at over 16 petabytes of storage.
0:19:56 > 0:19:59That's 16 million gigabytes.
0:19:59 > 0:20:04Or the equivalent of 250,000 top-of-range iPads.
0:20:04 > 0:20:08Or, if you like, over a million of your average smartphones.
0:20:11 > 0:20:15Through programming rigorous data architecture within these systems,
0:20:15 > 0:20:20computer technicians are able to store data, move data,
0:20:20 > 0:20:22test data, analyse and display data,
0:20:22 > 0:20:25in ever more ingenious ways.
0:20:25 > 0:20:28Effectively handing biologists specialist computing tools
0:20:28 > 0:20:33to extract maximum value from this most precious resource.
0:20:34 > 0:20:37(COMPUTERISED VOICE): Now, some impressive genetic detective work
0:20:37 > 0:20:40has analysed the most recent seven cholera pandemics,
0:20:40 > 0:20:44and traced all of them back to the same source.
0:20:44 > 0:20:46We looked into cholera,
0:20:46 > 0:20:50because we wanted to understand where it originated from.
0:20:50 > 0:20:53It is important to know the source population for cholera because,
0:20:53 > 0:20:55once you know the source, you have the possibility
0:20:55 > 0:20:59of controlling and preventing its spread from that source.
0:20:59 > 0:21:03Even bacteria like cholera have DNA that is traceable
0:21:03 > 0:21:05from one generation to the next.
0:21:05 > 0:21:08In being able to compare cholera bacteria from all over the world,
0:21:08 > 0:21:13Nick had valuable insight in tracing where it was originating from.
0:21:13 > 0:21:17Easier than it sounds.
0:21:17 > 0:21:20Just the sequence of one genome is five million base pairs for cholera.
0:21:20 > 0:21:24Within those five million base pairs of DNA sequence,
0:21:24 > 0:21:27we're looking, maybe even for just one base pair change
0:21:27 > 0:21:29between two different bacteria.
0:21:29 > 0:21:32When you have 100, 150 genomes,
0:21:32 > 0:21:36it becomes an unimaginable amount of sequence data.
0:21:36 > 0:21:39It's quite literally like looking for a needle in a haystack.
0:21:39 > 0:21:43But, because of programmers' clever manipulation of these immense datasets,
0:21:43 > 0:21:47it's been possible to find that needle.
0:21:47 > 0:21:49By looking at huge amounts of sequence data,
0:21:49 > 0:21:52we could understand how they related to each other.
0:21:52 > 0:21:55And, by understanding, just like a family tree,
0:21:55 > 0:21:58understanding how they relate to each other,
0:21:58 > 0:22:01we can actually find out where they were originating from.
0:22:01 > 0:22:03And, whilst cholera and other diseases
0:22:03 > 0:22:06are not going to vanish off the face of the earth overnight,
0:22:06 > 0:22:11computing has allowed us to plan ways of starting to make it happen.
0:22:11 > 0:22:14Computing is effectively central to everything we do,
0:22:14 > 0:22:18when you are trying to answer large questions relating to human health,
0:22:18 > 0:22:23rely on large computing facilities and processing power.
0:22:23 > 0:22:27And, with the kind of technologies that biologists will use
0:22:27 > 0:22:29likely to improve over time,
0:22:29 > 0:22:34the opportunities available for the next generation of computer scientists are enormous.
0:22:34 > 0:22:36In biological research,
0:22:36 > 0:22:39I think, mostly, computers are taken from granted.
0:22:39 > 0:22:42We assume there will be processing power,
0:22:42 > 0:22:44we assume there will be memory.
0:22:44 > 0:22:45We assume there will be good people
0:22:45 > 0:22:49that can actually write programs to analyse the data.
0:22:49 > 0:22:51But that's an unsafe assumption.
0:22:51 > 0:22:54From a biological point of view, you need those people.
0:22:54 > 0:22:58Because, as I say, you are asking really key questions
0:22:58 > 0:23:00that have fundamental importance to human health.
0:23:00 > 0:23:04So, programming a computer could allow you to play a role
0:23:04 > 0:23:08in fighting killer diseases as diverse as cystic fibrosis, cancer,
0:23:08 > 0:23:11and even alcoholism.
0:23:11 > 0:23:15Computers, without doubt, have a huge impact on the real world.
0:23:15 > 0:23:17But they are proving just as key
0:23:17 > 0:23:20in merging the worlds of reality and make-believe.
0:23:23 > 0:23:26Once you understand the fundamentals of how a computer works,
0:23:26 > 0:23:28and the language that it speaks,
0:23:28 > 0:23:32then you can challenge it to do a wider range of tasks.
0:23:32 > 0:23:34However, programming a computer to carry out what you want it to do
0:23:34 > 0:23:38is as much about being able to make sense of the world around us,
0:23:38 > 0:23:41as it is about understanding the computers themselves.
0:23:41 > 0:23:44To be able to impress a world-class director is an a difficult thing.
0:23:44 > 0:23:47And that's what we have to do on a regular basis.
0:23:47 > 0:23:51We are there, from the word go, during film production,
0:23:51 > 0:23:54and all through post-production, throughout the edit.
0:23:54 > 0:23:58Visual effects is entirely integrated into film production now.
0:23:58 > 0:24:03Visual effects is a really central part of the film-making process now.
0:24:03 > 0:24:05Every artist will be designing something,
0:24:05 > 0:24:10or deciding how a shot is composed, how it breaks down.
0:24:10 > 0:24:12Those decisions make it up on to the big screen.
0:24:12 > 0:24:16We are as central a part of the film-making process as the actors,
0:24:16 > 0:24:20the set designers, the costume designers.
0:24:20 > 0:24:23And, with the ever advancing power of computers,
0:24:23 > 0:24:25visual effects companies, like DNeg,
0:24:25 > 0:24:28are capable of creating ever more complex animations.
0:24:28 > 0:24:31Imagination simply knows no bounds.
0:24:31 > 0:24:33My job, as effects supervisor,
0:24:33 > 0:24:36is to take any part of a film that needs to be computer-generated,
0:24:36 > 0:24:39and that moves under the forces of physics.
0:24:39 > 0:24:43So, things like natural phenomena, water, fire.
0:24:43 > 0:24:46Anything that follows the rules of nature.
0:24:46 > 0:24:48Newton's laws of motion.
0:24:48 > 0:24:52It's something that we can definitely represent inside the computer.
0:24:52 > 0:24:55We take things in the real world, and you make a computer program.
0:24:55 > 0:24:56That's was a programmer will do.
0:24:56 > 0:25:00The person is the intermediary that writes the software.
0:25:00 > 0:25:03The software dictates what the computer does.
0:25:03 > 0:25:06But the software is a set of rules derived from the real world.
0:25:06 > 0:25:08Computer modelling, or simulation,
0:25:08 > 0:25:11underpins much of their initial work.
0:25:11 > 0:25:14We start by looking at the effect that we want to achieve.
0:25:14 > 0:25:16So, in the case of something like fire,
0:25:16 > 0:25:18we look at how it behaves in the real world.
0:25:18 > 0:25:23What are the forces of physics that define how fire moves?
0:25:23 > 0:25:28What's the chemistry of what's going on inside the flame?
0:25:28 > 0:25:31And we would break it down to the maths that dictates that motion.
0:25:31 > 0:25:35And then we return that maths into a list of exact instructions
0:25:35 > 0:25:37that the computer needs to follow.
0:25:37 > 0:25:39That process is called abstraction.
0:25:39 > 0:25:44Abstraction essentially tries to reduce and factor out irrelevant details,
0:25:44 > 0:25:47so that the programmer can focus on a few concepts at a time.
0:25:47 > 0:25:50It's really important to shoot reference wherever possible.
0:25:50 > 0:25:53It's very easy to think, I know what lightning looks like.
0:25:53 > 0:25:55But you probably don't.
0:25:55 > 0:26:01If I said, how long exactly in seconds does it exist? You wouldn't know.
0:26:01 > 0:26:04So, to program a computer how to replicate lightning,
0:26:04 > 0:26:07we need to understand lightning ourselves.
0:26:07 > 0:26:10We'd look at that reference footage, and work out what we want to inherit
0:26:10 > 0:26:12and what we'd don't want to inherit from real life.
0:26:12 > 0:26:16We would then program those rules into the computer,
0:26:16 > 0:26:19and encourage it to follow them over and over again.
0:26:19 > 0:26:22And usually we will have to adapt it, rework it.
0:26:22 > 0:26:26And shape it to where we need it to be to do the effects work.
0:26:26 > 0:26:30But, even then, we are by no means dealing with the finished article.
0:26:30 > 0:26:33Directors can be a picky bunch,
0:26:33 > 0:26:36and changes will often be required.
0:26:36 > 0:26:39There will be notes about the movement of the flames.
0:26:39 > 0:26:41They will say, "Can flames be more chaotic at this point?
0:26:41 > 0:26:43"Can the flames be calm at this point?"
0:26:43 > 0:26:48So you're always balancing a line between stylised and natural.
0:26:48 > 0:26:52Say, if you wanted to have the flames more swirly,
0:26:52 > 0:26:55more curled shapes rather than sharp shapes,
0:26:55 > 0:26:57you might go into the algorithm,
0:26:57 > 0:27:02look at where rotational shapes have been introduced, and exaggerate them.
0:27:02 > 0:27:05It's not something that would happen in real life,
0:27:05 > 0:27:07but it could change the character of the flames.
0:27:07 > 0:27:10So, writing a program's one thing.
0:27:10 > 0:27:12But being able to go back into a pre-written program,
0:27:12 > 0:27:15and adjust it to your requirements has many advantages.
0:27:15 > 0:27:18Reinventing the wheel is incredibly wasteful.
0:27:18 > 0:27:22Once you have software which is able to create flames and modify flames,
0:27:22 > 0:27:25you should use that to your best advantage.
0:27:25 > 0:27:30I think debugging skills, reasoning skills, testing skills,
0:27:30 > 0:27:34are even more important than writing software in the beginning.
0:27:34 > 0:27:37It's great to have people who can pick those tools up,
0:27:37 > 0:27:41try using them, say, "This works but this didn't.
0:27:41 > 0:27:43"This creatively hinders me.
0:27:43 > 0:27:46"This part could be much more useful if it worked like this."
0:27:46 > 0:27:50And can feed that stuff back, so we end up writing the best software.
0:27:50 > 0:27:53It's not just about writing accurate software.
0:27:53 > 0:27:55You need to be creative enough
0:27:55 > 0:27:58to manipulate it in the director's favour.
0:27:58 > 0:28:02It's important we try to represent real-life in our simulations.
0:28:02 > 0:28:05But it's also important that we do things that help the story,
0:28:05 > 0:28:06that help the drama.
0:28:06 > 0:28:09It's really important everyone in the visual effects industry
0:28:09 > 0:28:11has a technical side to them and an artistic side to them.
0:28:11 > 0:28:16So, if you have any doubts about the creative possibilities
0:28:16 > 0:28:18opened up by a career in computer programming,
0:28:18 > 0:28:21simply look to the stars.
0:28:21 > 0:28:23I think it's absolutely vital
0:28:23 > 0:28:26that kids today learn all these concepts,
0:28:26 > 0:28:29get really into computer programming, understand the logic behind it.
0:28:29 > 0:28:30It's really fantastic,
0:28:30 > 0:28:32And when you get to use it
0:28:32 > 0:28:35you can do absolutely amazing stuff, like the work that we do.
0:28:42 > 0:28:45Subtitles by Red Bee Media Ltd