:00:00. > :00:09.How VR is helping the ongoing hunt for war criminals.
:00:10. > :00:42.And, prepare to enter your mind palace.
:00:43. > :00:44.It's estimated that 6 million Jews were killed by the Nazis
:00:45. > :00:52.in the Holocaust with millions of others, many in concentration camps.
:00:53. > :00:55.To try and bring justice to the innocent civilians who died,
:00:56. > :01:01.on November the 20th 1945, the Nuremberg War Trials began.
:01:02. > :01:03.71 years later, the prosecution of Nazi war criminals
:01:04. > :01:14.And now, virtual reality is playing a part in the process.
:01:15. > :01:17.Marc Cieslak travelled to Germany and Poland to find out how.
:01:18. > :01:46.The town of Oswiecim in Poland is the sight of perhaps
:01:47. > :01:48.The town of Oswiecim in Poland is the site of perhaps
:01:49. > :01:50.the most infamous of Nazi concentration camps,
:01:51. > :01:55.Between May 1940 and the camp's liberation by the red
:01:56. > :01:57.Between May 1940 and the camp's liberation by the Red
:01:58. > :02:00.Army in January 1945, 1.1 million people were killed here.
:02:01. > :02:07.Most gassed by a cyanide-based pesticide, Zyklon B.
:02:08. > :02:10.This is the Auschwitz two, Birkenau site.
:02:11. > :02:20.This is where the vast majority of people were killed.
:02:21. > :02:23.Gassed and then their bodies burned in the camp's crematoria.
:02:24. > :02:25.Towards the end of the war, the Nazis destroyed those
:02:26. > :02:28.crematoria, trying to cover up some of the appalling atrocities
:02:29. > :02:39.Pavel Savitski has worked here for nine years.
:02:40. > :02:42.Most of the Jews deported to Auschwitz first came
:02:43. > :02:47.Within minutes they were separated for ever.
:02:48. > :02:50.They told people they would be living here with their families
:02:51. > :02:59.But first they need to go through disinfection process,
:03:00. > :03:03.Usually around 75, 80% of each transporter was taken straight
:03:04. > :03:06.The Nuremberg trials initially prosecuted 21 senior members
:03:07. > :03:10.of the Nazi regime for war crimes, including the crimes in the camps.
:03:11. > :03:12.But many of the perpetrators of these atrocities,
:03:13. > :03:15.SS officers and camp guards, remained at large and they are still
:03:16. > :03:25.being pursued by the authorities to this day.
:03:26. > :03:28.Here at the Bavarian State criminal office in Munich,
:03:29. > :03:30.they are working on new methods to assist with the prosecution
:03:31. > :03:36.of war crimes committed over 70 years ago.
:03:37. > :03:40.Ralph is a digital imaging expert here.
:03:41. > :03:43.He works with technology like 3-D printed re-creations
:03:44. > :03:47.of gunshot wounds to assist in gathering evidence.
:03:48. > :03:50.His team has created a 3-D model of Auschwitz,
:03:51. > :03:55.which can be visited in virtual reality.
:03:56. > :03:58.So Ralph, how long did you spend at Auschwitz capturing
:03:59. > :04:03.TRANSLATION: We spent five days in Auschwitz.
:04:04. > :04:06.We took stock of the buildings that are still standing, then we laser
:04:07. > :04:11.Virtual reality is an incredibly powerful tool for immersing
:04:12. > :04:15.the viewer in the experience they are having.
:04:16. > :04:27.TRANSLATION: I think within five to ten years,
:04:28. > :04:30.virtual reality will become a standard tool for police, not just
:04:31. > :04:42.Because it's a way to make scenes of crime accessible
:04:43. > :04:48.A version of the 3-D Auschwitz which doesn't use VR has already
:04:49. > :04:51.But why is this model necessary in the first place?
:04:52. > :04:54.To find out, I travel to the town of Ludwigsburg near Stuttgart.
:04:55. > :05:00.The building we are just coming up to, for 200 years,
:05:01. > :05:04.And then in the 1960s, it took on a new role,
:05:05. > :05:06.it became the Central Office for the Investigation
:05:07. > :05:16.Essentially, the people that work here are Nazi hunters.
:05:17. > :05:18.A former criminal prosecutor, Yens Rommel now heads
:05:19. > :05:24.Its files contain the names of thousands of possible suspects,
:05:25. > :05:25.along with a staggering number of documents relating
:05:26. > :05:33.What you find here is a paper database system, dealing
:05:34. > :05:39.really with index cards, explaining which person,
:05:40. > :05:42.which location, the scene of a crime, for example.
:05:43. > :06:03.We have 1.7 million cards here, dealing alone with 700,000 people.
:06:04. > :06:06.So how does this 3-D model, virtual reality model of Auschwitz
:06:07. > :06:12.When it comes to a specific line of defence, a defence strategy used
:06:13. > :06:19.in almost all cases, the defendant admits
:06:20. > :06:23.that he was exactly in Auschwitz, but generally he says
:06:24. > :06:25.I didn't know anything about what was going
:06:26. > :06:36.It can help to understand what the person involved could see
:06:37. > :06:45.For examples, from a watchtower over the camp, or from the fence
:06:46. > :06:51.We saw a trial this year with Mr Hanning,
:06:52. > :07:10.Former SS guard Reinhold Hanning was convicted of accessory
:07:11. > :07:12.to 170,000 murders and sentenced to five years in prison.
:07:13. > :07:15.The judge in this case pointed out the 3-D model made it clear
:07:16. > :07:26.what he would have been able to see from his watchtower.
:07:27. > :07:32.We are going to go inside one of the watchtowers and see
:07:33. > :07:34.what you can actually see from inside here.
:07:35. > :07:36.Using the virtual reality model of Auschwitz, I went
:07:37. > :07:40.inside a watchtower to see what the lines of sight were and see
:07:41. > :07:46.And you can see pretty much everything.
:07:47. > :07:48.There is an urgency to the work of prosecuting the perpetrators
:07:49. > :08:03.Well, it's not an easy job to do, to look each day into these crimes,
:08:04. > :08:12.And sometimes it can be frustrating to see that 95% of the names
:08:13. > :08:15.we are checking here when it comes to suspects,
:08:16. > :08:20.that these persons have died already.
:08:21. > :08:36.The virtual reality model of Auschwitz was uncannily accurate,
:08:37. > :08:40.but there's one thing it can't recreate and that is the unusual
:08:41. > :08:49.atmosphere of this place, perhaps the most notorious of all
:08:50. > :09:02.A place where 1.1 million people were killed.
:09:03. > :09:06.Hello and welcome to the Week in Tech.
:09:07. > :09:09.It was the week that Google and Facebook introduced measures
:09:10. > :09:12.they say will help curb the spread of fake news stories
:09:13. > :09:17.Twitter also tried to clean up its act, putting the mute
:09:18. > :09:20.on hateful content, suspending several American activists
:09:21. > :09:25.and announcing new ways to tackle abusive messages.
:09:26. > :09:32.And, not content with showing you a street view of the world,
:09:33. > :09:41.Google this week also showed off the entire world in virtual reality.
:09:42. > :09:43.Exclusive to, no, not its Daydream headset, but the HTC
:09:44. > :09:45.Vive, users could zoom around iconic skyscrapers.
:09:46. > :09:47.Soar above beautiful landscapes, but no doubt will have many just
:09:48. > :09:53.And if getting about by bike is your bag, it was also the week
:09:54. > :09:57.that a safety helmet made of paper won the James Dyson Design Award.
:09:58. > :10:00.The recyclable eco-helmet is designed to disintegrate
:10:01. > :10:05.with age, and so it can only be used a limited number of times,
:10:06. > :10:09.but it can fold up to fit snugly into your rucksack.
:10:10. > :10:18.And finally, if you're sick of your pizza delivery being stuck
:10:19. > :10:20.in traffic, a company in New Zealand has started
:10:21. > :10:26.The aim is to have piping hot pizza in your lap less than ten
:10:27. > :10:30.It could only be a matter of time before the skies are filled
:10:31. > :10:46.Ever tried to learn a language but never quite got round to it
:10:47. > :10:49.or kept up the good work for long enough?
:10:50. > :10:53.Well, some of the latest apps and software could be just
:10:54. > :10:58.And in my quest to learn a little bit of Spanish,
:10:59. > :11:06.And here at the University of Westminster, this
:11:07. > :11:12.Combining the ancient concept of the memory palace
:11:13. > :11:20.This visual way of organising information aims to help you learn,
:11:21. > :11:22.retain and recall things by picturing objects
:11:23. > :11:24.and creating your own connections to remember them.
:11:25. > :11:31.So why not do this with learning a language?
:11:32. > :11:36.This exercise teaches how to conjugate the verb
:11:37. > :11:46.The objects I'm seeing represent the ending, so the 'O'
:11:47. > :11:49.for ostrich is hablo, I speak, and so on.
:11:50. > :11:51.Hablan, so it's just a woman named Ann.
:11:52. > :12:10.When engrossed in it, it's easy to memorise and then
:12:11. > :12:13.you've learned a pattern are many other Spanish verbs follow.
:12:14. > :12:16.So now, if you actually take off the headset...
:12:17. > :12:18.So, how did I do once the headset was off?
:12:19. > :12:27.It is amazing because you do come away from the experience,
:12:28. > :12:30.and I think that's partly VR, you come away from the feeling
:12:31. > :12:35.I'm certainly visualising those things.
:12:36. > :12:38.But it's a very slow way to learn a language, isn't it?
:12:39. > :12:40.People spend years trying to learn these things.
:12:41. > :12:42.The most important thing, particularly as an adult learner,
:12:43. > :12:45.if you are looking to use a language at a high level,
:12:46. > :12:48.is to understand the structure and the grammar of the language.
:12:49. > :12:52.So those aren't actually, it's not that much in terms
:12:53. > :12:55.of content, but it's complex content and it's all
:12:56. > :12:57.The software is already being created in Arabic,
:12:58. > :13:01.French, German, Italian, Spanish and English.
:13:02. > :13:03.And after a few more tweaks, will be available in beta
:13:04. > :13:09.Of course, apps coaching numerous languages have
:13:10. > :13:15.But for the purpose of this piece, I've looked at the Spanish lessons
:13:16. > :13:25.Babble teaches you to read, write, speak and
:13:26. > :13:30.It even tests your pronunciation skills, which is actually
:13:31. > :13:33.The only problem is, if it takes you a few
:13:34. > :13:35.times to get it right, it becomes quite irritating
:13:36. > :13:55.Duo Lingo works in a similar way, gamifying the experience
:13:56. > :13:58.and letting you achieve a Street count for how many days
:13:59. > :14:02.Pursue pictures itself as a social network for language learning.
:14:03. > :14:05.Its 16 million worldwide users can communicate with and give or receive
:14:06. > :14:09.But the team behind the Mem Rise app have prioritised the importance
:14:10. > :14:10.of learning conversational language from locals,
:14:11. > :14:13.as well as giving the app a bit of character.
:14:14. > :14:15.They've recently returned from a four-month road trip
:14:16. > :14:17.across Europe, collecting video content for their Meet
:14:18. > :14:22.Having this added feature of a person actually talking
:14:23. > :14:26.to you in a conversational way, I think does help.
:14:27. > :14:29.In a way, it just makes you feel that little bit more pleased
:14:30. > :14:32.with yourself that you've understood a real person talking
:14:33. > :14:41.As well as having big gaming features and off-line mode
:14:42. > :14:48.similar to other apps, it also uses means to help
:14:49. > :14:50.similar to other apps, it also uses memes to help
:14:51. > :14:53.Like this Chinese symbol for the woman.
:14:54. > :14:55.Ultimately though, all apps take commitment and whilst the memory
:14:56. > :14:58.palace has clearly etched place in my mind now a week later,
:14:59. > :15:00.the only full sentence I think I've actually
:15:01. > :15:02.learnt is "Lo siento, no hablo Espanol."
:15:03. > :15:04.translation - "sorry I don't speak Spanish."
:15:05. > :15:26.Right, Spanish viewers, marks out of ten please,
:15:27. > :15:30.Now this fascinating idea that you can bring a mind palace
:15:31. > :15:32.into virtual reality, but I did find myself thinking
:15:33. > :15:34.the idea of a mind palace was that it imagines,
:15:35. > :15:37.so you did a lot of work within your brain.
:15:38. > :15:40.Now you can visualise it in VR, does that kind of spoiled
:15:41. > :15:44.I understand your point, but I do think that actually
:15:45. > :15:46.having done it in VR, in what is probably the most
:15:47. > :15:49.engaging environment I could, I can really commit the things to memory.
:15:50. > :15:52.Because you know that funny feeling where you come out of a VR
:15:53. > :15:56.experience and you feel old we had to be back in the real world.
:15:57. > :15:58.And I think if at the same time you've actually learned
:15:59. > :16:00.something in the process, then that's pretty good.
:16:01. > :16:03.So, if I were to ask you conjugate verbs are now,
:16:04. > :16:07.you would be able to go to that space and pick out the right thing?
:16:08. > :16:10.Because I've learned the ending is still a lot of verbs,
:16:11. > :16:13.but I still don't have a great deal of vocabulary and that's
:16:14. > :16:16.what I would need to develop, so I actually knew what the words
:16:17. > :16:18.were, so I could then conjugate the verb.
:16:19. > :16:25.We're going to Australia now, would you believe?
:16:26. > :16:27.Jen Copestake is there and she's been taking a look at some
:16:28. > :16:31.Week in, week out on Click, we see technologies that
:16:32. > :16:35.But could they also change what fundamentally makes us human?
:16:36. > :16:37.This is something being discussed in Sydney at the BBC
:16:38. > :16:47.Addressing our increasingly complex relationship with artificial
:16:48. > :16:49.intelligence, the Earth's fragile ecosystem and space,
:16:50. > :16:51.leading researchers and a couple of astronauts brought their ideas
:16:52. > :16:54.for how people could use technology to enhance our species
:16:55. > :17:01.Retired astronaut Ron Garan was deeply moved by his time
:17:02. > :17:03.in space and believes travel above the Earth could bring
:17:04. > :17:06.a new perspective to our lives on the ground.
:17:07. > :17:09.He has made two trips to the International Space Station
:17:10. > :17:12.and is now the chief pilot at World View,
:17:13. > :17:18.Its aim is to bring tourists to the outer
:17:19. > :17:23.atmosphere using gigantic, high altitude balloons.
:17:24. > :17:25.Blown up, they are the size of a professional football pitch.
:17:26. > :17:27.Attached is a pressurised, gondola-like craft with
:17:28. > :17:30.room for eight people - two crew and six passengers.
:17:31. > :17:32.Travelling 30 kilometres up, there will also be a bar
:17:33. > :17:40.The plan is to send the first trip up before the end of 2018
:17:41. > :17:48.and at a cost of $75,000 per ticket, it's a relatively cheap trip.
:17:49. > :17:52.I think the price will initially go up, but we are looking to find ways
:17:53. > :17:57.to bring the prices as low as we possibly can.
:17:58. > :18:00.We called World View for a reason, it is written in our DNA,
:18:01. > :18:03.that this will be a transformative experience and I believe,
:18:04. > :18:05.the company believes, that the more people who get
:18:06. > :18:08.to see our planet from that vantage point the better of all of us
:18:09. > :18:14.Back on Earth, with great technological progress,
:18:15. > :18:16.comes increasing piles of electronic waste.
:18:17. > :18:19.There are more than 2 billion smartphones in use around the world,
:18:20. > :18:21.all containing small amounts of precious metals including
:18:22. > :18:25.gold, silver, copper, platinum and palladium.
:18:26. > :18:30.And finding simple ways to locally recycled the precious materials
:18:31. > :18:33.And finding simple ways to locally recycle the precious materials
:18:34. > :18:35.from smartphones is the focus of Venus, who presented the case
:18:36. > :18:39.So here we have a fragment, which actually is pretty cool
:18:40. > :18:41.because it applies high voltage to pull apart the components
:18:42. > :18:59.So it's really like using a super powerful lightning bolt to separate
:19:00. > :19:01.out the case, the glass, the circuit board from mobile
:19:02. > :19:09.A drone is programmed to identify a circuit board in a pile of waste
:19:10. > :19:12.and relate this info to a robot, who picks up the circuit board
:19:13. > :19:16.The furnace uses uses precisely controlled high-temperature
:19:17. > :19:18.reactions to draw out the viable metal alloys.
:19:19. > :19:20.Any toxic or unwanted materials can be safely incinerated
:19:21. > :19:27.So, I mentioned the conference was also challenging our ideas
:19:28. > :19:33.I had a role here too, giving an artificially
:19:34. > :19:38.intelligent Chatbot named Rose, a human body to speak
:19:39. > :19:47.What do you think, should we fear artificial intelligence?
:19:48. > :19:50.I am baffled as to what Stephen Hawking and the others think
:19:51. > :19:53.This experiment attempts to challenge our idea
:19:54. > :19:55.of where we end and artificial intelligence begins.
:19:56. > :19:58.I'll have more on that experience in a later episode of Click,
:19:59. > :20:19.That was Jen in Australia and now to a truly American phenomenon.
:20:20. > :20:22.After nine months and 35 races, this weekend marks the culmination
:20:23. > :20:31.As you are undoubtedly aware, for drivers are all tied for first
:20:32. > :20:34.As you are undoubtedly aware, four drivers are all tied for first
:20:35. > :20:36.place, they've all got the same number of points.
:20:37. > :20:39.So, whoever wins this weekend's race, wins the championship.
:20:40. > :20:42.The tiniest advantage could do it, so Dave Lee stuck in his earplugs
:20:43. > :20:54.and spent a weekend with the teams who are targeting immortality.
:20:55. > :20:57.In the USA, only American football gets more viewers than NASCAR,
:20:58. > :20:59.and that's because of the drama out there on the track,
:21:00. > :21:02.where every fraction of a second can make the difference
:21:03. > :21:05.Which is why NASCAR teams are constantly looking
:21:06. > :21:07.to new technology to help them understand more about how
:21:08. > :21:16.I jumped at the chance to check out the teams and their tech
:21:17. > :21:18.when they raced in Sonoma, part of California's
:21:19. > :21:26.So we are in the bustling garage area where all the teams are making
:21:27. > :21:31.the final touches to their cars for the racing this weekend.
:21:32. > :21:33.All the changes they make end up being inspected
:21:34. > :21:36.just around the corner, to make sure none of the teams
:21:37. > :21:41.are doing anything unfairly to gain an advantage over everyone else.
:21:42. > :21:45.The teams must line up around the block to be inspected.
:21:46. > :21:49.Until recently, this process used to rely on paper documents.
:21:50. > :21:51.Now, it's all synced up in the Cloud with data
:21:52. > :21:57.It's saved more than 20,000 sheets of paper and saved many hours
:21:58. > :22:01.Basically, everything used to be done with hand-held
:22:02. > :22:06.It took seven, eight, nine people to inspect a vehicle.
:22:07. > :22:09.Now, as you can see, we can do it with three people,
:22:10. > :22:12.just based on the fact everything now is automated and we have
:22:13. > :22:18.The partnership with Microsoft is designed to help the teams
:22:19. > :22:20.and the fans make sense of the vast amount of data
:22:21. > :22:26.But the new technology is also being used to stop teams
:22:27. > :22:31.The system can automatically detect certain infractions.
:22:32. > :22:36.The system will automatically detect if they've driven through more
:22:37. > :22:38.than three pit boxes on entry or exit.
:22:39. > :22:40.It will automatically detect the vehicle position,
:22:41. > :22:43.so if the vehicle is outside of the box and they start to work
:22:44. > :22:45.on it the system automatically flags that.
:22:46. > :22:48.And when the crew is potentially over the wall too soon,
:22:49. > :22:52.the system, again, will automatically flags that.
:22:53. > :22:54.The system uses Hawk-Eye, the same tech used in tennis matches,
:22:55. > :22:58.to spot things like when a pit crew jumps over a barrier to early.
:22:59. > :23:01.If you are a driver, it's now a lot harder to get away
:23:02. > :23:07.with some of the more sneaky tactics in racing.
:23:08. > :23:10.If they were going to get rid of one type of technology, it
:23:11. > :23:13.would be all the technology they use to police others,
:23:14. > :23:16.You can't get away with much, especially race time
:23:17. > :23:18.with all those cameras, that system they have set up,
:23:19. > :23:23.Exhaust for drivers, but technology has seemed
:23:24. > :23:25.to have won over most of NASCAR's fanatical followers.
:23:26. > :23:28.As a fan I can look up how my driver's doing,
:23:29. > :23:33.I can see all the specs, I can listen online
:23:34. > :23:38.Sometimes it's good to kind of see the old days, let them race and do
:23:39. > :23:41.I think technology can take away some of the uncertainties,
:23:42. > :23:44.where people were not really sure what the call was.
:23:45. > :23:46.You can have the technology help settle that for them.
:23:47. > :23:49.The winner this weekend was Tony Stewart,
:23:50. > :23:52.who managed to win it using a refreshing low-tech tactic.
:23:53. > :23:57.He bashed another driver off the track.
:23:58. > :24:01.That was Dave Lee at the NASCAR and that it for this week.
:24:02. > :24:36.Thanks for watching, follow us on Twitter throughout
:24:37. > :24:38.It's been cold and frosty this Saturday morning, with icy issues