Browse content similar to Fifty Shades of Spray. Check below for episodes and series from the same categories and more!
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This week, wall climbing graffiti bots. All aboard the holodeck. And | :00:00. | :00:20. | |
just watch out for the rodents. Oh, there is a mouth! -- mouse! | :00:21. | :00:43. | |
Data is all around us. We generate around 2.5 billion GB of it every | :00:44. | :00:55. | |
day. Think of it as, well, there is no other word for it, really. | :00:56. | :01:01. | |
Enormous. And we are finding lots of new ways of gathering even more of | :01:02. | :01:06. | |
it. Machines are now able to look at videos and interpret what is in the | :01:07. | :01:11. | |
image, and with the number of CCTV cameras around the town, imagine how | :01:12. | :01:15. | |
much more data we can collect. But the real intelligence is not in | :01:16. | :01:19. | |
capturing the data. It is in analysing it. And this is where | :01:20. | :01:23. | |
artificial intelligence might make a real difference, making connections | :01:24. | :01:28. | |
that we humans never would. Big data has accelerated our understanding of | :01:29. | :01:31. | |
medical science in unimaginable ways. It is now influencing how | :01:32. | :01:37. | |
hospitals treat patients, police forces manage crime, and city | :01:38. | :01:42. | |
officials run our towns. And it is inevitable, in the next 50 years, | :01:43. | :01:47. | |
that AI will play an even bigger role in our society, and influence | :01:48. | :01:54. | |
how we go about living. I recently met DJ Patil, President Barack | :01:55. | :02:00. | |
Obama's chief data scientist, who was in charge of shaping how big | :02:01. | :02:04. | |
data is used by the government to make big policy decisions, while | :02:05. | :02:08. | |
ensuring the AIA created by the tech companies treat everyone fairly and | :02:09. | :02:12. | |
make good decisions. That is where we have to start focusing more about | :02:13. | :02:16. | |
energy, is asking the question of how do we actually make sure that | :02:17. | :02:19. | |
these algorithms are going to work the way we want? People talk about | :02:20. | :02:23. | |
self driving cars. It is a self driving car going to see someone | :02:24. | :02:28. | |
with my skin tone, or someone with a darker skin tone? A person with a | :02:29. | :02:33. | |
wheelchair? Is that a person in the dataset? How do start saying... You | :02:34. | :02:38. | |
are suggesting whether a self driving car would recognise you as | :02:39. | :02:41. | |
something it should avoid. Yes, Boyd, because we have different skin | :02:42. | :02:45. | |
colour. Are people with your skin colour the only ones in the data | :02:46. | :02:49. | |
set, am I ignored? Is that an accident? But what about somebody | :02:50. | :02:54. | |
with a handicap? What about a kid on a tricycle? It is not sufficient to | :02:55. | :02:59. | |
say oops about the algorithm. We have to figure out a more robust | :03:00. | :03:03. | |
process as these things are becoming more integrated into our society. | :03:04. | :03:08. | |
And if we have learned anything from this week's Facebook story, it is | :03:09. | :03:11. | |
that tech companies are not the most transparent lunch. Facebook has been | :03:12. | :03:15. | |
around for more than a decade, and only now, by chance, have we got a | :03:16. | :03:20. | |
glimpse of how its moderators decide what we see on its platform. So how | :03:21. | :03:28. | |
do we make sure the AI built by the same tech companies are using our | :03:29. | :03:33. | |
data responsibly? So the first, it comes down to how are you trained? | :03:34. | :03:37. | |
In our training these days, we often have found that technologists are no | :03:38. | :03:41. | |
longer trained in humanities. One of the most critical components of | :03:42. | :03:45. | |
humanities is the notion of ethics, so what we have called for is that | :03:46. | :03:48. | |
every data scientist, every economist, anybody who works with | :03:49. | :03:52. | |
data, must have ethics integrated throughout their entire curriculum. | :03:53. | :03:55. | |
So you can start to have the conversation and dialogue about what | :03:56. | :04:00. | |
are the ethical implications of the choices you make second part of this | :04:01. | :04:03. | |
is how about security of the data? How do you make sure that you are | :04:04. | :04:07. | |
actually building the algorithms with security, the datasets with the | :04:08. | :04:10. | |
purity so people can't just break in. That has to no longer be elected | :04:11. | :04:15. | |
or something outside. That has to be part of the core training. Once you | :04:16. | :04:18. | |
have this component of our training, I think you are going to have a new | :04:19. | :04:22. | |
set of people who have the vocabulary to talk about it. But | :04:23. | :04:26. | |
that doesn't take into account the speed at which it is happening on | :04:27. | :04:29. | |
taking place today. So what we do then? Number one, transparency. | :04:30. | :04:32. | |
President Obama signed an executive order that said by default all data | :04:33. | :04:35. | |
the Federal Government on the US Federal Government, publishers, must | :04:36. | :04:39. | |
be open and machine-readable. And what that allows people to do is be | :04:40. | :04:43. | |
able to access the data, preparing, use it, and innovate with it -- | :04:44. | :04:49. | |
compare it. And that is the problem, how do we strike the balance? We | :04:50. | :04:53. | |
need to know that a AI system is not biased as loan from a dataset which | :04:54. | :04:56. | |
includes all of us, and its decisions are fair, but we also | :04:57. | :04:59. | |
don't want to stifle its process will make progress, because when it | :05:00. | :05:03. | |
is used in the right way it really can change things for the better. | :05:04. | :05:07. | |
What we have found in one of the problems around a local jail system | :05:08. | :05:11. | |
is that there is a huge number of people who are just cycling in and | :05:12. | :05:15. | |
out of the system. I mean, the numbers are extraordinary. More than | :05:16. | :05:17. | |
11 million people through 3100 jails, they stay there on average 23 | :05:18. | :05:22. | |
days. 95% never go to long-term prison. It turns out there are a lot | :05:23. | :05:26. | |
of mental health issues, a lot of drug addiction. So what happens to | :05:27. | :05:30. | |
those people? Where is the data going? It stays in silos. The | :05:31. | :05:35. | |
healthcare system has a silo, criminal justice. So what happens if | :05:36. | :05:38. | |
you just talk and share that information? Is said do you see | :05:39. | :05:46. | |
Sally and data set and say we saw Sally all the time? Well, why are we | :05:47. | :05:52. | |
sending her to jail, let's send her to the right intervention. So doing | :05:53. | :05:58. | |
that, how much can you save? What is the real impact? It costs 1.5 | :05:59. | :06:02. | |
million to train of Ron on the right intervention and share the data, and | :06:03. | :06:06. | |
everything. The first year alone they saved more than $10 million, | :06:07. | :06:11. | |
but more importantly they were able to close a full jail. And later on | :06:12. | :06:15. | |
they close second jail because they are giving people the right care. | :06:16. | :06:17. | |
It was the week that Volvo announced it's working on an AI rubbish truck | :06:18. | :06:23. | |
that will follow collectors from house to house. | :06:24. | :06:26. | |
IKEA said they will release smart light bulbs that can be controlled | :06:27. | :06:29. | |
by voice and sync up with home devices like Alexa | :06:30. | :06:31. | |
And Google fancied another "go" at Go success. | :06:32. | :06:37. | |
The AI system AlphaGo took on the world's number | :06:38. | :06:40. | |
one Go player Ke Jie, and won the series. | :06:41. | :06:44. | |
AlphaGo learned to play by studying old matches and playing thousands | :06:45. | :06:47. | |
The hope now is it will be used in medicine and science in the future. | :06:48. | :06:53. | |
More bad news for Uber this week, as it admitted it underpaid drivers | :06:54. | :06:57. | |
in New York for more than two and a half years. | :06:58. | :07:00. | |
Tens of thousands of drivers will now be paid about $900 each, | :07:01. | :07:03. | |
which will mean Uber paying out tens of millions of dollars. | :07:04. | :07:08. | |
And only one month into the release of Samsung's new Galaxy S8 | :07:09. | :07:12. | |
smartphone virus scanner, and it's already been hacked. | :07:13. | :07:16. | |
German hackers fooled the scanner with only a paper printer | :07:17. | :07:19. | |
and a contact lens to make the fake eye. | :07:20. | :07:25. | |
And is RoboCop from the '80s becoming a reality? | :07:26. | :07:27. | |
Well, not quite, but Dubai police want these robots to make up 25% | :07:28. | :07:31. | |
They launched the unit on Wednesday, which can forward video | :07:32. | :07:39. | |
feeds to the police, settle fines, has facial | :07:40. | :07:41. | |
recognition, and can speak nine languages. | :07:42. | :07:43. | |
Graffiti art has been one of the hottest art movements over | :07:44. | :07:57. | |
Like many graffiti artists, Graeme - or Xenz, the name he goes by - | :07:58. | :08:02. | |
In this case, the streets of Bristol. | :08:03. | :08:06. | |
And he has since grown into the artist that we see on the roof | :08:07. | :08:10. | |
Today, he's taking a break to do this for us. | :08:11. | :08:14. | |
But he's more known these days for these amazing natural scenes | :08:15. | :08:18. | |
which are exhibited and sold all over the world, | :08:19. | :08:21. | |
and which incorporate all of the graffiti techniques that | :08:22. | :08:23. | |
Yeah, over time you really understand what the can | :08:24. | :08:29. | |
You know, you come to rely on these tools, like the nozzle | :08:30. | :08:34. | |
Like the way that I use the edge there to keep one edge | :08:35. | :08:39. | |
sharp and one edge faded, then this, you know, | :08:40. | :08:41. | |
So there's a lot of disciplines that go through painting that | :08:42. | :08:49. | |
No, we don't have that kind of patience. | :08:50. | :08:54. | |
So could we pull off something similar to this by combining | :08:55. | :08:57. | |
technology with someone who has no creative talent whatsoever? | :08:58. | :08:59. | |
To find out, we sent Nick Kwek to Estonia... | :09:00. | :09:02. | |
Tartu, Estonia's second-largest city. | :09:03. | :09:03. | |
Like most cities, graffiti and street art provoke | :09:04. | :09:05. | |
It's also home to one of the biggest spray-painted pieces | :09:06. | :09:24. | |
But Albert's been painted dot by dot, and I've been promised I too | :09:25. | :09:39. | |
can achieve artistic genius with the right tools. | :09:40. | :09:41. | |
Believe it or not, these pictures have all been | :09:42. | :09:44. | |
They've been pieced together splodge by splodge | :09:45. | :09:49. | |
My daughter wanted a unicorn on her wall, but I couldn't draw. | :09:50. | :10:00. | |
So that pushed me towards creating this device. | :10:01. | :10:03. | |
To make these magical masterpieces you need the right kit - | :10:04. | :10:06. | |
a smartphone with the appropriate app installed, an external battery | :10:07. | :10:08. | |
pack to keep it fully juiced, a tripod to hold it steady, | :10:09. | :10:12. | |
some paint, and of course the SprayPrinter. | :10:13. | :10:29. | |
First you select an image and align it against | :10:30. | :10:32. | |
So the image is projected like a giant virtual sticker. | :10:33. | :10:36. | |
The phone's camera exposes for the LED on the device, | :10:37. | :10:40. | |
and when it illuminates it sends the can's location to the app. | :10:41. | :10:43. | |
The phone then tells the printer its coordinates | :10:44. | :10:46. | |
and the printer decides when to spray and when not to. | :10:47. | :10:50. | |
Once you get the knack of it, it's actually surprisingly simple to use. | :10:51. | :10:53. | |
You just have to make sure you go from left to right, or right to | :10:54. | :10:57. | |
left, very smoothly, in a straight line. | :10:58. | :10:59. | |
For all its geeky brilliance, it's a real labour of love. | :11:00. | :11:02. | |
Even the most simple of designs takes several | :11:03. | :11:04. | |
Depending on how complex the picture, | :11:05. | :11:06. | |
and the size, the amount of | :11:07. | :11:08. | |
layers, the different colours you want to paint with, | :11:09. | :11:10. | |
you know, that determines how long doing one of | :11:11. | :11:13. | |
You need to move your hand relatively | :11:14. | :11:26. | |
steady, so if you start moving your hand very | :11:27. | :11:28. | |
Not sure I could really stand your for | :11:29. | :11:31. | |
With the next model, you should be able to | :11:32. | :11:38. | |
move your hand relatively freely as you would with | :11:39. | :11:41. | |
rest, the team have already started developing robotic | :11:42. | :11:56. | |
versions to do the spraying for them, meaning larger more complex | :11:57. | :11:59. | |
I developed this extra accessory for the SprayPrinter to | :12:00. | :12:02. | |
atomise the process, because for high scale | :12:03. | :12:04. | |
images the hand-held method takes too much time and | :12:05. | :12:07. | |
too, hopefully speeding things up a bit. | :12:08. | :12:18. | |
But does the printer help artistic expression, or | :12:19. | :12:20. | |
gives like guidelines of how to paint. | :12:21. | :12:27. | |
It's like sort of a colouring book, but | :12:28. | :12:29. | |
you can go over the lines, but the paint | :12:30. | :12:31. | |
will still only land in the | :12:32. | :12:33. | |
I think for people like myself, we call them | :12:34. | :12:46. | |
LAUGHTER And I think this device gives them | :12:47. | :12:48. | |
It started off only a few small dots. | :12:49. | :12:52. | |
You actually have to stand back a few feet to get the | :12:53. | :12:55. | |
full view, to get the right perspective on it. | :12:56. | :12:58. | |
So what would you like to see spray-painted next? | :12:59. | :13:12. | |
Well, the guys have been holding a competition | :13:13. | :13:15. | |
and this winning submission, just announced, will soon be painted on | :13:16. | :13:18. | |
a local giant abandoned power station | :13:19. | :13:19. | |
chimney for all to see, but painting on this | :13:20. | :13:22. | |
curved structure has posed new | :13:23. | :13:23. | |
problems, which Mihkel is determined to solve. | :13:24. | :13:25. | |
I thought it would be a good idea to use a vacuum | :13:26. | :13:29. | |
Rover, so this is just a four wheeled platform that drives across | :13:30. | :13:32. | |
It attaches to the wall using vacuum. | :13:33. | :13:42. | |
Yeah, and in true Blue Peter fashion, here's one I made | :13:43. | :13:45. | |
Well, that was Nick Kwek with the SprayPrinter. | :13:46. | :13:59. | |
It helps us to get these large images | :14:00. | :14:09. | |
up easier but no, I think I'm quite comfortable | :14:10. | :14:12. | |
It definitely has its advantages, for | :14:13. | :14:17. | |
Well, in the meantime, this is beautiful. | :14:18. | :14:20. | |
Thanks so much for doing this for us. | :14:21. | :14:22. | |
We're going to stay on and art tip now. | :14:23. | :14:29. | |
Here at Photo London art takes many forms. | :14:30. | :14:37. | |
But the thing I've seen that I've grappled with the | :14:38. | :14:39. | |
most is the idea of a virtual reality gallery. | :14:40. | :14:43. | |
Is this really a way to fully experience art? | :14:44. | :14:48. | |
So what's going on in here, and in here? | :14:49. | :14:57. | |
Well, in the 1800s when people saw photography for the first time they | :14:58. | :15:00. | |
were absolutely wowed by it, but of course now | :15:01. | :15:03. | |
So what's happening is some of those initial images are being | :15:04. | :15:09. | |
brought back to life in virtual reality. | :15:10. | :15:15. | |
original original photographic images were shown has been recreated | :15:16. | :15:21. | |
Well, initially I wasn't sure that looking at these images in | :15:22. | :15:27. | |
virtual reality seemed like something that actually makes | :15:28. | :15:30. | |
sense, but apparently you can pick up the | :15:31. | :15:33. | |
images by holding your hand over it like that, | :15:34. | :15:37. | |
and then you can hold the image in your hand... | :15:38. | :15:40. | |
You can really see the texture of it as well. | :15:41. | :15:47. | |
This genuinely feels like I'm standing in | :15:48. | :15:49. | |
In fact, it actually feels quite hazardous | :15:50. | :15:53. | |
because you can see smoke coming off it and that is proper serious heat. | :15:54. | :15:57. | |
But whilst the juxtaposition between the origins of photography | :15:58. | :16:06. | |
and a new visual medium are deliberate, making sure it | :16:07. | :16:09. | |
provides a meaningful experience for those with a yearning for art | :16:10. | :16:13. | |
Nothing fills me with a greater melancholy than going | :16:14. | :16:21. | |
into an exhibition and seeing somebody with a virtual reality | :16:22. | :16:24. | |
headset on, and having to queue and wait for your turn on it - | :16:25. | :16:28. | |
So what I've tried to do in this installation is to make that part | :16:29. | :16:33. | |
of the actual experience, so when you're not in the room | :16:34. | :16:36. | |
you can look at people with their headsets | :16:37. | :16:38. | |
Watching the goings-on of people wandering around is quite strange | :16:39. | :16:42. | |
and surreal to look at, so hopefully it's still interesting | :16:43. | :16:45. | |
as an artwork even when you're not in the headset. | :16:46. | :16:49. | |
So I can hear some sound coming from over here. | :16:50. | :16:52. | |
That's because of the binaural sound that's built in, | :16:53. | :16:54. | |
and there seems to be something happening outside... | :16:55. | :16:59. | |
I believe this is the Chartists' revolt. | :17:00. | :17:02. | |
This is a lot of people objecting to photography. | :17:03. | :17:06. | |
This wasn't the only VR at the show, though. | :17:07. | :17:09. | |
One family of art collectors wanted to virtually take | :17:10. | :17:11. | |
You can have your art museum in your pocket. | :17:12. | :17:24. | |
I can have 200 metre museum just in my laptop. | :17:25. | :17:26. | |
That could be sharing a collection internationally, a trip to a | :17:27. | :17:29. | |
virtual art gallery for those who are housebound, or | :17:30. | :17:32. | |
introducing a new audience to art who might be more | :17:33. | :17:35. | |
The real-life version of this statue is | :17:36. | :17:38. | |
I will head towards it and have a closer look. | :17:39. | :17:42. | |
I can actually see the size of it by those | :17:43. | :17:44. | |
And in fact the size of that piece of art behind | :17:45. | :17:48. | |
it, the scale of all of this, is absolutely massive. | :17:49. | :17:51. | |
It would require such a large building to actually | :17:52. | :17:54. | |
Amidst the physical art were the latest | :17:55. | :17:59. | |
imaging, entire film is superimposed on | :18:00. | :18:03. | |
single images, and this Paris park scene. | :18:04. | :18:07. | |
So behind this photograph we are looking at here is actually a | :18:08. | :18:10. | |
massive plate of LED lights, all spread out with an inch between | :18:11. | :18:14. | |
them, so each time you can see a person crossing the screen it's | :18:15. | :18:21. | |
actually a combination of these lights being dimmed in that pattern, | :18:22. | :18:24. | |
and what the human eye fills an in between to make it | :18:25. | :18:29. | |
One thing that seemed clear by the end of the day, | :18:30. | :18:34. | |
though, was that VR can feel a natural part of an art show, and | :18:35. | :18:38. | |
that I'm never going to be an art expert. | :18:39. | :18:42. | |
One of the brilliant things about working | :18:43. | :18:56. | |
ambitions at one point or another, which is why | :18:57. | :19:01. | |
this week Mark Cieslak became the captain of a starship! | :19:02. | :19:06. | |
He took some of the rest of the Click family | :19:07. | :19:09. | |
with him, to boldly go where no Mark has gone before. | :19:10. | :19:14. | |
These are the virtual voyages of the BBC Click | :19:15. | :19:19. | |
Our mission: To wear VR headsets and discover strange, new | :19:20. | :19:25. | |
technology, and boldly go where no TV reporter has gone before. | :19:26. | :19:50. | |
Virtual reality game Star Trek Bridge Crew | :19:51. | :19:54. | |
brings together up to four players, each | :19:55. | :19:55. | |
taking a different role on the | :19:56. | :19:57. | |
The beauty of going where no one has gone before | :19:58. | :20:03. | |
is that starship travel involves an awful lot of sitting down. | :20:04. | :20:07. | |
Sitting down is great for virtual reality | :20:08. | :20:09. | |
because the headsets have got these cables. | :20:10. | :20:12. | |
If you're moving around it easy to get caught up with them. | :20:13. | :20:16. | |
And where better to be sitting in the | :20:17. | :20:24. | |
Captain's chair of a Federation starship? | :20:25. | :20:26. | |
Headsets on, it's time for the Click team to become a starship | :20:27. | :20:29. | |
The early missions are all about orientating us with the bridge | :20:30. | :20:54. | |
As helmsman, you are the ship's navigator. | :20:55. | :20:58. | |
The headset shows us what the bridge looks like, but the | :20:59. | :21:01. | |
PlayStation motion controllers allow us to interact with the various | :21:02. | :21:03. | |
controls we have to master in order to fly the ship. | :21:04. | :21:07. | |
We don't have time for sight seeing, though, as we receive | :21:08. | :21:29. | |
a distress signal from a stricken vessel. | :21:30. | :21:31. | |
My vessel has lost all power and our life-support systems are | :21:32. | :21:34. | |
Can you transport the survivors to here? | :21:35. | :21:44. | |
CHUCKLES That wasn't in the training. | :21:45. | :21:54. | |
LAUGHTER We're homing in at an alarming rate, | :21:55. | :21:56. | |
There are no options within transporter. | :21:57. | :21:58. | |
It's at this moment that the action takes | :21:59. | :22:07. | |
a turn which will appeal to Star Trek superfans. | :22:08. | :22:11. | |
OK, guys, this is the Kobayashi Maru scenario. | :22:12. | :22:16. | |
This is an impossible to win situation. | :22:17. | :22:19. | |
Bring us about so we can actually see that | :22:20. | :22:41. | |
Line up the phasers, and torpedoes away. | :22:42. | :22:56. | |
Yeah, everybody, we just violated a peace treaty. | :22:57. | :23:06. | |
It's pretty warm work being in virtual reality. | :23:07. | :23:11. | |
It feels like it's social VR at its best, really. | :23:12. | :23:14. | |
If you don't have it you're not going to complete the mission. | :23:15. | :23:18. | |
I thought we actually had our lives on the | :23:19. | :23:22. | |
That ably demonstrates the power of teamwork. | :23:23. | :23:25. | |
It's really, really important that everybody plays their role on the | :23:26. | :23:28. | |
bridge, because if you don't then chaos ensues. | :23:29. | :23:31. | |
We had a couple of sticky moments there, but I think we | :23:32. | :23:34. | |
managed to pull it back and keep it together as a crew. | :23:35. | :23:38. | |
And the result was a successful mission. | :23:39. | :23:41. | |
Or like us on Facebook, too, where you can see | :23:42. | :23:50. | |
Now, while you're watching this we are doing a live show at the Hay | :23:51. | :23:55. | |
And next week on the programme you can see a | :23:56. | :24:02. | |
little bit of what we're getting up to. | :24:03. | :24:07. | |
And if you're coming, I hope you enjoy the | :24:08. | :24:10. | |
With a bank holiday weekend now upon us, | :24:11. | :24:36. | |
we are set to see a change in the hot, dry weather, | :24:37. | :24:39. | |
that has been with us for the past few days. | :24:40. | :24:42. | |
Here was the scene on Friday in Moray. | :24:43. | :24:44. | |
One of our Weather Watchers captured this. | :24:45. | :24:47. |