0:00:00 > 0:00:01That's it from me.
0:00:01 > 0:00:06Now on BBC News, Click.
0:00:09 > 0:00:23This week, cars, bars and a police riot. -- ride.
0:00:40 > 0:00:45I am on my way to a reported incident on 1-off Las Vegas's
0:00:45 > 0:00:53busiest highways. With the last rain falling over four months ago, the
0:00:53 > 0:00:57Audley Road is mixed with fresh water have become a lethal recipe
0:00:57 > 0:01:04for disaster. -- oily roads. In the driving seat is a sergeant from the
0:01:04 > 0:01:08Nevada Highway Patrol. He is using a software that alerts into an
0:01:08 > 0:01:15incident as soon as it is reported by someone calling 911 or through
0:01:15 > 0:01:19driving apps and provide him with details and the best route to get to
0:01:19 > 0:01:25the scene.The location, what kind of accident, the degree, and if
0:01:25 > 0:01:31there are any responders that are on their way.It constantly updates in
0:01:31 > 0:01:35on the situation as it develops. Having a robust system in place
0:01:35 > 0:01:41doesn't just help with weather-related collisions.With our
0:01:41 > 0:01:49Route 91 shooting that we had, for the portion that we handled, the
0:01:49 > 0:01:53Highway Patrol, it's getting the public off the highway as quickly as
0:01:53 > 0:01:57possible, closing of the freeways we could have the critical resources,
0:01:57 > 0:02:03fire, medical, ambulances, to get people to the hospital quickly.In
0:02:03 > 0:02:082017 15,000 crashes were attended to, with over 300 people dying on
0:02:08 > 0:02:13average in each year in Rosa -- road accidents in Nevada, getting
0:02:13 > 0:02:16emergency services to be seen as quickly as possible is critical.
0:02:16 > 0:02:23There is an injury. Camera 217.The system has been running through the
0:02:23 > 0:02:28regional transportation commission's traffic centre for the past three
0:02:28 > 0:02:31months.Now because we are getting information through so many
0:02:31 > 0:02:37different data streams, not just dispatches, but social media, things
0:02:37 > 0:02:42like the apps. Because all of this is happening so quickly we might
0:02:42 > 0:02:45have already sent out all of that information and had everybody in
0:02:45 > 0:02:50this room where before the first 911 call comes in. So we are talking
0:02:50 > 0:02:56about possibly ten to 15 minutes of improvement in response time in some
0:02:56 > 0:03:00of these incidents. That's major when you are dealing with these
0:03:00 > 0:03:06kinds of incidents.The app pulls information from various sources, in
0:03:06 > 0:03:10vehicle sensors, TV cameras, information from driving apps. It
0:03:10 > 0:03:15factors in what day of the year it is, the time of day and the weather.
0:03:15 > 0:03:19Responding to incidents rapidly is one thing, but the point is to be
0:03:19 > 0:03:24able to predict them before they happen so the responders can be
0:03:24 > 0:03:29better prepared and in the right location.We look at the historical
0:03:29 > 0:03:34data, running through algorithms to develop patterns that are merging.
0:03:34 > 0:03:40By doing that we can look forward in time to identify where these
0:03:40 > 0:03:52incidents are likely to occur. Unfortunately, the app wasn't able
0:03:52 > 0:03:57to predict this one.It looks like it is the real. You can see how she
0:03:57 > 0:04:03was spinning out. She did a full 180 and struck right here.Being able to
0:04:03 > 0:04:09foresee accidents here could really save lives. The hope is that as the
0:04:09 > 0:04:12data gets more sophisticated the predictions will become more
0:04:12 > 0:04:17accurate.Everyday we get more and more evidence about what causes,
0:04:17 > 0:04:22what triggers, incident and the artificial learning get smarter and
0:04:22 > 0:04:26smarter and more capable.For Nevada now the initial results are
0:04:26 > 0:04:32promising.They get there faster, we clear it faster and that means less
0:04:32 > 0:04:38secondary accidents and if you think about it secondary accidents have
0:04:38 > 0:04:43basically 18% of secondary accidents are fatalities. So we are reducing
0:04:43 > 0:04:47the fatalities on the road.And of course the goal is to prevent
0:04:47 > 0:04:51accidents altogether and Richard Taylor and Lara Lewington have been
0:04:51 > 0:05:00looking at some in car technologies that may help make that a reality.
0:05:00 > 0:05:04At CES as you might expect there's a lot of interest in self driving cars
0:05:04 > 0:05:08and it's pretty clear that we are on a 1-way street towards full
0:05:08 > 0:05:12autonomy.But that does still seem to be a way off, although we don't
0:05:12 > 0:05:15know exactly how far. In the meantime there is plenty of
0:05:15 > 0:05:21innovation to be seen before we reach our final destination.
0:05:21 > 0:05:25Unsurprisingly, the move towards autonomy to driving is focused
0:05:25 > 0:05:30largely on safety, with healing day creating a system to intervene when
0:05:30 > 0:05:35we needed the most. -- with Hyundai. With accommodation of biometric
0:05:35 > 0:05:38sensors in the seat, they are tracking heart rate and a low
0:05:38 > 0:05:42resolution camera which is tracking your facial movements. The reason it
0:05:42 > 0:05:46is low resolution is so that the refresh rate is quicker. So if
0:05:46 > 0:05:49there's a problem, if you've lost concentration or you are drifting
0:05:49 > 0:05:53off to sleep, then the car can quickly react. So autonomously be
0:05:53 > 0:05:58moved off the road to a safe spot. And the basic tremors of this
0:05:58 > 0:06:05technology could be available in just a year. -- a sick premise.
0:06:05 > 0:06:09Meanwhile, Nissan has a more futuristic twist on biometrics. The
0:06:09 > 0:06:14idea of this system is really to provide an interaction between man
0:06:14 > 0:06:21and machine, between my brain and the AI. The concept here with Nissan
0:06:21 > 0:06:26is even in a world of autonomous vehicles, there will be roles for
0:06:26 > 0:06:31humans to play. After all, a lot of people find driving a positive
0:06:31 > 0:06:36experience. It can interpret signals coming from the human and actually
0:06:36 > 0:06:42in -- enhance the ride. This sort of brain the vehicle text currently
0:06:42 > 0:06:46involves wearing this bizarre helmet to capture my brain activity and
0:06:46 > 0:06:51interpret signals as much as half a second before my muscles do. So, as
0:06:51 > 0:06:55I'm about to say change lane or hit the brakes on it will initiate the
0:06:55 > 0:06:59action for me, giving me a smoother ride, and yet still allowing me a
0:06:59 > 0:07:03sense of control. They do need to sort out that helmet, though. Oh
0:07:03 > 0:07:08dear. I'm not driving very well here.Yet what we can't hide away
0:07:08 > 0:07:13from is the fact that when full autonomy does come to pass, it is
0:07:13 > 0:07:19not simply about cars. This is Yamaha's concept motorbike. A self
0:07:19 > 0:07:24driving racing vehicle that should be able to do speeds of over 120
0:07:24 > 0:07:29mph, although not on actual roads you would hope. But whatever the
0:07:29 > 0:07:33form of autonomous vehicle it will need to interact safely with
0:07:33 > 0:07:39pedestrians at and cyclists, a challenge that Ford are hoping to
0:07:39 > 0:07:42overcome in their vehicles. Initially cyclists will have to be
0:07:42 > 0:07:45seen by the vehicles and we are building the reception into our
0:07:45 > 0:07:50autonomous vehicle that allows it to detect the cyclists, objects,
0:07:50 > 0:07:53understand their intent and make sure we can be safely navigating
0:07:53 > 0:07:59same space.And Ford are just one of the big brands that have called on
0:07:59 > 0:08:03the help of a company, whose processes, combined with
0:08:03 > 0:08:06intelligence software, can make the environment around the vehicles
0:08:06 > 0:08:10safer. For example using light as sensors to alert the driver who is
0:08:10 > 0:08:16about to open a car door onto a cyclist. -- lidar sensors.And AI is
0:08:16 > 0:08:20fuelling other experiences. Speech recognition specialists power many
0:08:20 > 0:08:25of the day's in car interactions how they are looking in the future as
0:08:25 > 0:08:32well.Today we think about interacting with using voice, but
0:08:32 > 0:08:36there are other modalities. Of course we have a touchscreen, but
0:08:36 > 0:08:43maybe we can use gestures and in this particular prototype we
0:08:43 > 0:08:48introduced eye tracking, to help the assistant understand what am I as a
0:08:48 > 0:08:52driver looking at and then I can ask questions about my environment. If I
0:08:52 > 0:08:57see a coffeeshop in front of me, I can just ask a question about it.
0:08:57 > 0:09:03What is the user rating of this copy shop?Starbucks coffee has a user
0:09:03 > 0:09:08rating of three stars.So the other part of the system is that there are
0:09:08 > 0:09:11microphones in different parts of the car, which means the AIA can
0:09:11 > 0:09:15respond according to whether different passengers are. So here on
0:09:15 > 0:09:20the passenger seat I can say, "hello, Dragon, I'm cold".OK,
0:09:20 > 0:09:25raising the temperature in zone two...
0:09:25 > 0:09:29There's definitely a trend towards making our journeys more enjoyable
0:09:29 > 0:09:35as well as safer. To you to have updated their happiness concept,
0:09:35 > 0:09:38aiming for a more pleasurable journey and even suggesting where
0:09:38 > 0:09:43you might want to go -- Toyota. For anyone needs their car to tell them.
0:09:43 > 0:09:49I will tell you something interesting. There are many options
0:09:49 > 0:09:53around Union Square for casual dining the Michelin stars. Do you
0:09:53 > 0:10:02like it?Yes. That was a bit of fun, but I didn't need the AI to tell me
0:10:02 > 0:10:04that I was ready for dinner. Let's go.
0:10:10 > 0:10:15Welcome to the Week in Tech. The week Ford announced it would have £8
0:10:15 > 0:10:20billion in electric cars in the next five years. A flaw in a VR app left
0:10:20 > 0:10:2720,000 users' names exposed. And hackers stole $400,000 worth of
0:10:27 > 0:10:32cryptic currency by hijacking a server. It was a busy week for
0:10:32 > 0:10:36crypto currency, as big coin encountered its busiest daily crash
0:10:36 > 0:10:41in four months. -- biggest. It is thought fears over increased
0:10:41 > 0:10:45regulation, especially in Asia, would be an issue. A contraceptive
0:10:45 > 0:10:49app previously thought as effective as the pill has been criticised by a
0:10:49 > 0:10:52Swedish hospital for a number of unintended pregnancies they say were
0:10:52 > 0:10:56linked to the app. The company behind it have defended the product,
0:10:56 > 0:11:00saying that as with any form of contraception it isn't 100%
0:11:00 > 0:11:04effective. They are now launching an internal investigation, however. And
0:11:04 > 0:11:08I bet you didn't expect the latest Nintendo offering to include a whole
0:11:08 > 0:11:13lot of cardboard. The latest add-ons for the switch console are cardboard
0:11:13 > 0:11:18packs, turning the consoles into a fishing rod, motorbike and even a
0:11:18 > 0:11:22robot suit. Gimmick or brilliant? Finally, the rescue with a
0:11:22 > 0:11:27difference. A drone was used to save two swimmers off the coast of NSW in
0:11:27 > 0:11:31Australia. Lifeguards were being trained to use the rescue drone when
0:11:31 > 0:11:35practice became reality and it was launched, robbing a flotation device
0:11:35 > 0:11:44to the teenagers. The whole rescue took just 72nd. -- 70 seconds.
0:11:44 > 0:11:48In this trendy part of downtown Las Vegas, these passengers are waiting
0:11:48 > 0:11:54to hop on a special kind arrive. For the past two months, this French
0:11:54 > 0:11:58autonomous vehicle company has been offering free bus ride to the
0:11:58 > 0:12:02public. Admittedly it doesn't travel far, it just does a loop around the
0:12:02 > 0:12:07block with one stop at a doughnut shop. At least they are getting a
0:12:07 > 0:12:13taste of the future! Down the road I am waiting to catch a more private
0:12:13 > 0:12:20road which I've built on an app -- booked. As if by magic the door
0:12:20 > 0:12:28opened! The team was still ironing out a few issues, shall we say. I
0:12:28 > 0:12:35think this is the first genuinely autonomous vehicle I've been in
0:12:35 > 0:12:40where there really is no driver and their really is no place for a
0:12:40 > 0:12:49drive. There's just a safety man here. That's it. Safety man has an
0:12:49 > 0:12:55Xbox one controller down by his side. NAVYA is not alone in this
0:12:55 > 0:12:59space. Other companies have been battling it out to become the first
0:12:59 > 0:13:05fully autonomous cab sharing service. Self driving cars use a lot
0:13:05 > 0:13:08of sensors to be able to navigate the road safely. That's one of the
0:13:08 > 0:13:16most important is LIdar, how the car judges its surroundings. The design
0:13:16 > 0:13:22of these centres is at the heart of a court case. NAVYA's car is no
0:13:22 > 0:13:28different. It also uses Lidar to look around. What it is not doing is
0:13:28 > 0:13:32looking at the traffic lights to judge what colour they are. They've
0:13:32 > 0:13:35fitted special sensors to each traffic light and those sensors talk
0:13:35 > 0:13:40to the car. That doesn't sound very scalable to me. That sounds like you
0:13:40 > 0:13:43wouldn't be able to put this sort of technology on the open road without
0:13:43 > 0:13:47fitting every single traffic light in the US with these centres. It is
0:13:47 > 0:13:51much more just for predetermined routes for this kind of shuttle
0:13:51 > 0:13:58vehicles. While I've been riding around in
0:13:58 > 0:14:02this particular smart vehicle, Dave Lee has been up in Reno, not that
0:14:02 > 0:14:07far away, looking at a system that is making use of data collected by
0:14:07 > 0:14:11vehicles like this to help an entire city to move more smoothly.
0:14:19 > 0:14:22There's been great strides made in self driving technology over the
0:14:22 > 0:14:26past decade or so, but the thing about autonomy is that it often
0:14:26 > 0:14:30tested in bright and clear conditions. The real world is much
0:14:30 > 0:14:36more distracting.
0:14:36 > 0:14:38conditions. The real world is much more distracting. In fact, it is not
0:14:38 > 0:14:38just
0:14:38 > 0:14:41more distracting. In fact, it is not just darkness that is difficult for
0:14:41 > 0:14:45existing autonomous technologies. Whether it is through rain, snow, or
0:14:45 > 0:14:50just Faarup ahead on the road, there is a lot self driving vehicles
0:14:50 > 0:14:55struggle to see. Important work is taking place at the University of
0:14:55 > 0:15:00Reno, Nevada, that is attempting to solve that problem, making autonomy
0:15:00 > 0:15:07more intelligent. And it all begins here, on the corner of 15th and
0:15:07 > 0:15:12Virginia.So at that corner we have a light sensor. That light sensor
0:15:12 > 0:15:16used to be on the autonomous vehicle. But if we move it from the
0:15:16 > 0:15:20vehicle to the intersection, so it can track each pedestrian here, each
0:15:20 > 0:15:25vehicle here.What kind of things is that picking up? Is it recognising
0:15:25 > 0:15:29who people are?No, it only recognises this as a pedestrian or
0:15:29 > 0:15:34this is a vehicle. It does not recognise who the person is.Think
0:15:34 > 0:15:39of this intersection as providing more eyes to an autonomous vehicle.
0:15:39 > 0:15:43It could detect the threat and communicate that to a car heading in
0:15:43 > 0:15:48its direction, telling it to slow down, beware.So what these centres
0:15:48 > 0:15:52are doing in essence is giving autonomous car is more eyes on the
0:15:52 > 0:15:57road. Yes.They just know more about what is coming up ahead.Exactly, so
0:15:57 > 0:16:06no black spots.Part of the same programme is this connected car. A
0:16:06 > 0:16:10modified Lincoln that can not only drive itself around, but also
0:16:10 > 0:16:14communicate with other vehicles and components in the city, signalling
0:16:14 > 0:16:18its intention is to others.The hardware that you see is pretty
0:16:18 > 0:16:22similar to what you are going to see in most autonomous vehicles, if not
0:16:22 > 0:16:26all of them. Where we really dissing wish ourselves as in the software.
0:16:26 > 0:16:30So our research focuses on what I call social intelligence. We are
0:16:30 > 0:16:34trying to build machines that understand people, and understand
0:16:34 > 0:16:38human social behaviour, and can predict what other people are going
0:16:38 > 0:16:42to do, and then act appropriately. It is a skill that humans have. We
0:16:42 > 0:16:46navigate driving effortlessly, even though we can't read other people's
0:16:46 > 0:16:50mines, and it is a skill that computers are going to have to have
0:16:50 > 0:16:54if they are ever going to drive cars in the world with the rest of us.
0:16:54 > 0:16:57And then there is the challenge of making the technology work in
0:16:57 > 0:17:01difficult conditions. Inspired by an earlier project to help drone see in
0:17:01 > 0:17:04the dark, the team at the University's autonomous robots lab
0:17:04 > 0:17:12has confined lidar, radar and cameras, to dramatically improve
0:17:12 > 0:17:19what car can copperhead. It is also cheap. Once that technology is safe
0:17:19 > 0:17:23and ready, the plan is to deploy it on electric losses like this one.
0:17:23 > 0:17:27Until then, the team plans to use the autonomous tech together large
0:17:27 > 0:17:34amounts of data in preparation for a self driving future. This bus made
0:17:34 > 0:17:38by a California -based company is already out on Reno's roads, but
0:17:38 > 0:17:43right now with a more traditional type of driver.It is not autonomous
0:17:43 > 0:17:47yet. The idea is to at some point focus on that project. However,
0:17:47 > 0:17:51right now we are focusing on data collection for what we call the
0:17:51 > 0:17:56living lab, and data collection is going to be used for the mobility
0:17:56 > 0:17:59programme.For the foreseeable future, these buses will gather data
0:17:59 > 0:18:04for the living lab programme in Reno, a city that perhaps knows more
0:18:04 > 0:18:08about what is going on on its streets than almost any other city
0:18:08 > 0:18:17in the world. That was Dave, and now the something we have been hearing a
0:18:17 > 0:18:21lot about recently. Augmented reality. Now, it works by overlaying
0:18:21 > 0:18:27graphics on top of the real world, and while AR games like Pokemon Go
0:18:27 > 0:18:32have enjoyed global success, the most hyped it of AR kit, Magic to
0:18:32 > 0:18:36get leap, is still waiting to be released. AR remains a technology
0:18:36 > 0:18:42that promises more than it delivers -- Magic Leap. But by combining AR
0:18:42 > 0:18:46with AI, researchers in Florida are hoping to create new ways to train
0:18:46 > 0:18:52people to perform complex tasks. We took them AR kit for a test drive,
0:18:52 > 0:18:59or should that be a test flight? The University of Central Florida has a
0:18:59 > 0:19:04long established relationship with the simulation industry. Helping
0:19:04 > 0:19:08create simulated experiences for everything from driving to
0:19:08 > 0:19:17supermarket shopping. The simulation lab here's latest project is a bit
0:19:17 > 0:19:22more highflying than High Street, though. As long as we have had PCs,
0:19:22 > 0:19:26we have had flight simulators. But if you are really serious about
0:19:26 > 0:19:30learning how to fly, then you need an aircraft and a human pilot to
0:19:30 > 0:19:35teach you what to do. But this lab is about to be transformed into an
0:19:35 > 0:19:38aircraft cop that, with the help of this augmented reality headset. And
0:19:38 > 0:19:43when I put it on, it will also provide me with my very own virtual
0:19:43 > 0:19:52captain. Called Project Cap, it is a collaboration with aerospace giants
0:19:52 > 0:19:58Boeing.Necessary information. Sure, I have doubled my flow. Give it your
0:19:58 > 0:20:04best try.The aerial cockpit is designed as a training simulator for
0:20:04 > 0:20:08pilots. They can brush up on skills or practice in almost any
0:20:08 > 0:20:12environment. It does feel as if I can reach out and touch the
0:20:12 > 0:20:16controls, and I am very much tempted to. And I do that, and of course
0:20:16 > 0:20:24there is nothing there. The net. OK, cap, you seem to have a good idea of
0:20:24 > 0:20:29what to do in this aircraft. So taxi.Roger, you are clear to start
0:20:29 > 0:20:35number two.Ready. At the moment, Cap response to a very small number
0:20:35 > 0:20:44of voice commands or questions. Beacon.On.Might check.My cheque,
0:20:44 > 0:20:49one, two on three.But this can still be useful for training pilots.
0:20:49 > 0:20:53Augmented reality gives us a chance to bridge the thing strapped on the
0:20:53 > 0:20:56digital world and the things around us. How can we start to merge those
0:20:56 > 0:21:00things together in effective ways? How can we create holograms right
0:21:00 > 0:21:04before you for things that would be less safe if you were to do them in
0:21:04 > 0:21:07the real world, or that you might need additional information besides
0:21:07 > 0:21:11what you can build around you in the real world?Closed and locked. Looks
0:21:11 > 0:21:18behind him to check that.VR 140.It is a very convincing illusion that
0:21:18 > 0:21:25there is a pilot in here with me. Any questions?Do we have a specific
0:21:25 > 0:21:29altitude restriction?Per year in development, Cap is actually
0:21:29 > 0:21:34modelled on a real pilot.We have an opportunity to take some of our
0:21:34 > 0:21:37friends who are pilots, in this case one in particular, and see if he
0:21:37 > 0:21:41would actually subject himself to a full body scan, the then be able to
0:21:41 > 0:21:45use him as our avatar. So that is who we have, and actual pilots, who
0:21:45 > 0:21:50knows the mannerisms and gestures, that we can put into that virtual
0:21:50 > 0:21:54pilot's seat.But is this another instance of technology putting
0:21:54 > 0:22:01people out of their jobs?No, not at all. It is to provide student pilots
0:22:01 > 0:22:05with the opportunity to practise interpersonal skills before they
0:22:05 > 0:22:09actually get to a flight training centre, with real pilots. And we can
0:22:09 > 0:22:12provide them with a greater breadth of experiences, through introducing
0:22:12 > 0:22:15different variables, such as different cultural types of
0:22:15 > 0:22:19personality styles that they can practice with.I do wonder about
0:22:19 > 0:22:24other applications for this sort of kit. Somebody that might be able to
0:22:24 > 0:22:28teach you how to drive a car, for instance, will teach you how to
0:22:28 > 0:22:32operate various bits of equipment and machinery.Some of the work that
0:22:32 > 0:22:37we had done before doing the work with Boeing was in things like
0:22:37 > 0:22:40medical simulation, being able to have a holographic overlays that you
0:22:40 > 0:22:44could see the x-rays laid on top, exactly placed, or the CT scans or
0:22:44 > 0:22:48MRI is. Those are things that we think hold great promise, not only
0:22:48 > 0:22:51just because they will help with visualisation, but they might also
0:22:51 > 0:22:55lead to better quality of care, or lifesaving, because you have better
0:22:55 > 0:23:01access to data right when you need it.So one day, beyond the cockpit,
0:23:01 > 0:23:05Cap's digital descendants might help teachers teach us how to do all
0:23:05 > 0:23:15kinds of things. -- might help teach arts. And from Boeing to boosting. I
0:23:15 > 0:23:23am on my way to the Tipsy Robots, where mythology has been given a
0:23:23 > 0:23:29hi-tech makeover -- boozing. Here, the drinks are shaken and served by
0:23:29 > 0:23:33these two chaps. I can even invent my own cocktail by choosing from
0:23:33 > 0:23:39some of the 120 odd spirits hanging from the ceiling, or I assume all of
0:23:39 > 0:23:44the 120 odd spirits, in one. Can I do that? No, I can't do that,
0:23:44 > 0:23:49apparently. These droids can mix 100 cocktails are now between the two of
0:23:49 > 0:23:53them. That sounded impressive until I discovered some human bartenders
0:23:53 > 0:23:58can do ten times that. And that is it for Click in the US for this
0:23:58 > 0:24:02week. Don't forget, you can follow us on Twitter, where you can see
0:24:02 > 0:24:05loads of extra backstage videos and photos, although trust me, you don't
0:24:05 > 0:24:09want to see what happens after I have one or two of these. Cheers,
0:24:09 > 0:24:11see you soon.