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