this is bbc news — the headlines. the agent of the british writer — sir salman rushdie — has given details of his condition after he was stabbed on stage in the state of new york. the author is on a ventilator and can't speak. he also suffered injuries to his eye, his arm and his liver. the search warrant executed on donald trump's florida home on monday has been unsealed by a judge — after the former us president made no objection to the move. it shows the search by fbi agents was partly based on suspicions of violations of the us espionage act. a drought has been declared across large parts of england. water companies are now allowed to put stricter measures in place to conserve water supplies. the environment secretary — george eustice — has insisted there is "no reason for people

to be alarmed" and the uk's water supply "remains resilient". now on bbc news: three engineers at the forefront of reimagining the carjoin kevin fong at the science museum in london. hello and welcome to the science museum. i am kevin fong and this is the engineers of the future of cars. i am in the information age gallery sat in front of the road to be tuning coil and a hundred years ago,

this big wheel of copper wrapped in wood was the most powerful transmitter in the world. so, it's an appropriate place rest of this broadcast which brings in an audience of five different continents through the magic of our video link as well as a large audience here in the gallery for a programme that will be broadcast on bbc world service on radio and on television. the climate catastrophe, the sheer weight of traffic on our roads and the horrific rate of accidents the cause is forced a revolution in the way that we think about cars. with me today are three engineers were at the forefront of that revolution. we have the chief technical officer at the company called lightyear who has developed the world first family sized solar powered car. we have jamie, an expert at al and all topmast vehicles, he is an accomplished

scientist and a company called wave and he's there to tell us about autonomous driving vehicles. she is the chief engineer of the f 150 lightning. it has engineer of the f150 lightning. it has managed to somehow electrify one of america's most iconic and brilliant course. to join america's most iconic and brilliant course. tojoin me in welcoming them today. linda, let's start with you. people outside the us will not know what an icon the f150 is. . what an icon the f150 is. , the f series is such an iconic brand it is responsible for $112 billion of revenue. so, that is 17 million units on the road pretty much any given time since 2020.— pretty much any given time since2020. ., , ., ., since 2020. and a bit of a gas auzzler, since 2020. and a bit of a gas guzzler. eight _ since 2020. and a bit of a gas guzzler, eight km _ since 2020. and a bit of a gas guzzler, eight km per- since 2020. and a bit of a gas| guzzler, eight km per litre and your role in electrifying this vehicle has made you woman of

the year, according to usa today and put it on the cover of time magazine. we're expecting all the fuss? for m self, expecting all the fuss? for myself, personally - expecting all the fuss? fr?" myself, personally at that point, no. iwasn�*t myself, personally at that point, no. i wasn't expecting any of that because it's just surreal. but for the vehicle itself, we do expect a lot of us because the fact that it is f—series and it being basically in iconic vehicle, and away, a point for the industry because what it represents, and the way, if you think about with this product is and how people use it, it's notjust electrifying this vehicle but also changing the way that people might perceive what this can be. trucks are generally known for being very masculine and work oriented and being able to get things done. so, people use it almost in a way as a tool whereas in ev, people think of it as an eagle vehicle. those two things don't always go together perfectly. a

lot of people told me that's an oxymoron, you cannot have an ev truck and so, a lot of it has been to convince people that it can be tough and that this technology with the batteries as well as the motors actually can be more tough and in many ways, a better tool for the customer. ways, a better tool for the customer-— customer. you work in engineering _ customer. you work in engineering so - customer. you work in engineering so cars i customer. you work in| engineering so cars and customer. you work in - engineering so cars and again, no less ground—breaking here, i don't want to talk about how you got drawn into that is the thing you wanted to do. i understand that there is something called the solar vehicle race across australia. tell us about that and about this field. tell us about that and about this field-— tell us about that and about this field. i, . ~ ::' this field. back in 2012, were stud in: this field. back in 2012, were studying the _ this field. back in 2012, were studying the university - this field. back in 2012, were studying the university and l this field. back in 2012, were i studying the university and we found — studying the university and we found the solar car to participate and for the first time — participate and for the first time in _ participate and for the first time in 2013 when we competed, the first— time in 2013 when we competed, the first time introduced a new class _ the first time introduced a new class for— the first time introduced a new class for vehicles that, not

decide _ class for vehicles that, not decide to arrive as fast as they— decide to arrive as fast as they can _ decide to arrive as fast as they can but how many people you take — they can but how many people you take a practical the car is and _ you take a practical the car is and how— you take a practical the car is and how much you need. we took and how much you need. we took a year— and how much you need. we took a year to— and how much you need. we took a year to design the solar powered family car and rested through— powered family car and rested through many kilometres and it set us — through many kilometres and it set us up — through many kilometres and it set us up for the next adventure and so, after he finished _ adventure and so, after he finished his studies in this car over_ finished his studies in this car over the world, we hope to inspire — car over the world, we hope to inspire the _ car over the world, we hope to inspire the industry to show that— inspire the industry to show that we _ inspire the industry to show that we build a car that can drive — that we build a car that can drive off— that we build a car that can drive off the power of the sun but he — drive off the power of the sun but he didn't really happen, at some — but he didn't really happen, at some point, we figured if you want — some point, we figured if you want to— some point, we figured if you want to get out there, we have to do— want to get out there, we have to do it — want to get out there, we have to do it ourselves. and that's how— to do it ourselves. and that's how we — to do it ourselves. and that's how we lightyear six years ago. at the _ how we lightyear six years ago. at the start of all this, but you're racing across the australian desert in solar powered cars, this is an vehicles just creeping along the desert for weeks on end, as

a work come fast are they going? a work come fast are they oiiin ? ., ,., , a work come fast are they uuoin? ., ,., a work come fast are they ioini? ., ,, ., , going? thousands of kilometres and five and _ going? thousands of kilometres and five and a _ going? thousands of kilometres and five and a half _ going? thousands of kilometres and five and a half days - going? thousands of kilometres and five and a half days and - going? thousands of kilometres and five and a half days and 70 l and five and a half days and 70 and five and a half days and 70 an hour— and five and a half days and 70 an hour top speed and it depends a bit between 80 and 90. ., �* , ., , depends a bit between 80 and 90. ._ ,,, 90. that's really impressive. jamie, 90. that's really impressive. jamie. we — 90. that's really impressive. jamie, we heard _ 90. that's really impressive. jamie, we heard about - jamie, we heard about electrification there, we've heard about solar panels and you're in the field of autonomous vehicles and a lot of interest here and biases become your thing? i'zre of interest here and biases become your thing? i've been interested _ become your thing? i've been interested in _ become your thing? i've been interested in machines - become your thing? i've been interested in machines for - become your thing? i've been interested in machines for an | interested in machines for an incredibly— interested in machines for an incredibly young _ interested in machines for an incredibly young age. - interested in machines for an incredibly young age. my- incredibly young age. my interest— incredibly young age. my interest started - incredibly young age. my interest started to - incredibly young age. my interest started to growl incredibly young age. my. interest started to grow in artificiat— interest started to grow in artificial intelligence - interest started to grow in artificial intelligence and i artificial intelligence and studying _ artificial intelligence and studying in— artificial intelligence and studying in my— artificial intelligence and studying in my phd - artificial intelligence and studying in my phd in i artificial intelligence and - studying in my phd in computer vision, — studying in my phd in computer vision, computer— studying in my phd in computer vision, computervision- studying in my phd in computer vision, computer vision is - studying in my phd in computer vision, computer vision is when| vision, computer vision is when you take — vision, computer vision is when you take images _ vision, computer vision is when you take images from - vision, computer vision is when you take images from a - vision, computer vision is when you take images from a camera in the _ you take images from a camera in the trade _ you take images from a camera in the trade understand - you take images from a camera in the trade understand what i you take images from a camera in the trade understand what is| in the trade understand what is in the trade understand what is in that— in the trade understand what is in that image _ in the trade understand what is in that image. that _ in the trade understand what is in that image. that then - in the trade understand what is in that image. that then led i in the trade understand what is in that image. that then led to| in that image. that then led to working — in that image. that then led to working with _ in that image. that then led to working with microsoft - in that image. that then led to working with microsoft in - in that image. that then led to working with microsoft in our l working with microsoft in our research _ working with microsoft in our research labs _ working with microsoft in our research labs and _ working with microsoft in our research labs and started - research labs and started working _ research labs and started working on _ research labs and started working on products - research labs and startedi working on products using research labs and started - working on products using ai and i— working on products using ai and i worked _ working on products using ai and i worked on _ working on products using ai and i worked on the - working on products using ai and i worked on the originall and i worked on the original connector— and i worked on the original connector for— and i worked on the original connector for xbox- and i worked on the original connector for xbox 360 - and i worked on the original. connector for xbox 360 where you would. _ connector for xbox 360 where you would. we _ connector for xbox 360 where you would, we had _ connector for xbox 360 where you would, we had this - connector for xbox 360 where you would, we had this little i

you would, we had this little camera _ you would, we had this little camera and _ you would, we had this little camera and would _ you would, we had this little camera and would track- you would, we had this little j camera and would track your motions— camera and would track your motions you _ camera and would track your motions you could _ camera and would track your motions you could stand - camera and would track your motions you could stand upl camera and would track your. motions you could stand up in front— motions you could stand up in front of— motions you could stand up in front of this _ motions you could stand up in front of this camera _ motions you could stand up in front of this camera and - motions you could stand up inj front of this camera and move around — front of this camera and move around and _ front of this camera and move around and the _ front of this camera and move around and the algorithms, i front of this camera and move i around and the algorithms, the ai around and the algorithms, the al systems _ around and the algorithms, the ai systems that _ around and the algorithms, the ai systems that we _ around and the algorithms, the ai systems that we build - ai systems that we build started _ ai systems that we build started to _ ai systems that we build started to understand i ai systems that we build i started to understand what you're _ started to understand what you're doing _ started to understand what you're doing with— started to understand what you're doing with your- started to understand what| you're doing with your body started to understand what - you're doing with your body and then— you're doing with your body and then translate _ you're doing with your body and then translate that _ you're doing with your body and then translate that into - you're doing with your body and then translate that into a - then translate that into a representation— then translate that into a representation that - then translate that into a representation that the l then translate that into a - representation that the xbox in the game — representation that the xbox in the game could _ representation that the xbox in the game could then _ representation that the xbox inl the game could then understand and then— the game could then understand and then used _ the game could then understand and then used to _ the game could then understand and then used to control. - the game could then understand and then used to control. that . and then used to control. that interest— and then used to control. that interest is— and then used to control. that interest is involved _ and then used to control. that interest is involved ever- and then used to control. that interest is involved ever sincel interest is involved ever since and the — interest is involved ever since and the field _ interest is involved ever since and the field of— interest is involved ever since and the field of ai _ interest is involved ever since and the field of ai in- interest is involved ever since and the field of ai in generall and the field of ai in general realty— and the field of ai in general really advanced _ and the field of ai in general really advanced over- and the field of ai in general really advanced over the - and the field of ai in generalj really advanced over the last 20 years _ really advanced over the last 20 years in _ really advanced over the last 20 years in the _ really advanced over the last 20 years in the phone - really advanced over the last 20 years in the phone your. 20 years in the phone your pocket _ 20 years in the phone your pocket witt— 20 years in the phone your pocket will have _ 20 years in the phone your pocket will have all - 20 years in the phone your pocket will have all sorts l 20 years in the phone yourl pocket will have all sorts of ai algorithms _ pocket will have all sorts of ai algorithms and - pocket will have all sorts ofi ai algorithms and improving pocket will have all sorts of- ai algorithms and improving the quality— ai algorithms and improving the quality of— ai algorithms and improving the quality of your _ ai algorithms and improving the quality of your photos, - quality of your photos, recognising _ quality of your photos, recognising text - quality of your photos, recognising text and l quality of your photos, . recognising text and etc. quality of your photos, - recognising text and etc. the iconic f1 50 _ recognising text and etc. the iconic f1 50 pick-up - recognising text and etc. iconic f150 pick—up truck, that vehicle is very much about power, huge footprints, huge petrol engines. this engine underneath it that she pulled out and it still retains that power, tell me a bit about how

that works and how much power you can deliver out of electric motors and mother was a problem for you. motors and mother was a problem for ou. ,., ., , for you. the power on this vehicle is _ for you. the power on this vehicle is actually - for you. the power on this vehicle is actually great. i for you. the power on this i vehicle is actually great. 775 foot—pounds of torque which is higher than the highest out of any f150 and it's 584 horsepower. it's also the quickest f1 50 that we ever built but a lot of people have a hard time even getting to that point because they view it as it's electric. and we really had to work through changing some of those concepts. your initial power is actually really magnificent. it's near instant work of 775 whereas with a traditional gas vehicle, yet the engine combustion, you have the gears in the transmission and that torque actually has to grow. so, you have a very different curve, and away. the difficulty with ev is that maintaining towing in this case of a truck over

time, the longevity and that fatigue is something that we had to work through with the cooling system and really making sure that the cooling system was designed adequately to toe in a hole into all the same things that occur in truck customers can do.— customers can do. moving on from that _ customers can do. moving on from that point, _ customers can do. moving on from that point, whatever - customers can do. moving on. from that point, whatever they want to know is you're from the netherlands, it's lovely when the sun is shining, when it's not pretty cloudy out there, what's the range that i can expect that of your vehicle in northern europe? blue and an electric car you can still drive it, you have the battery, you can drive and many kilometres in the battery in the solar— kilometres in the battery in the solar panel continues to trickle — the solar panel continues to trickle charges on a single day if you're — trickle charges on a single day if you're in— trickle charges on a single day if you're in the full sun and ina— if you're in the full sun and in a good _ if you're in the full sun and in a good place, you may add up to 70 _ in a good place, you may add up to 70 km — in a good place, you may add up to 70 km range from the sun that— to 70 km range from the sun that does— to 70 km range from the sun that does not sound like a lot compared to the 625 but in practice, _ compared to the 625 but in practice, we don't use her car

every— practice, we don't use her car every day— practice, we don't use her car every day and we don't use it every— every day and we don't use it every day— every day and we don't use it every day for very long trips. white — every day for very long trips. white the _ every day for very long trips. while the solar system is always _ while the solar system is always on. it would look at is how— always on. it would look at is how much— always on. it would look at is how much you get in a year. so, in one _ how much you get in a year. so, in one year. _ how much you get in a year. so, in one year, even there, sega two _ in one year, even there, sega two 7000 _ in one year, even there, sega two 7000 km per year and more than _ two 7000 km per year and more than the — two 7000 km per year and more than the energy that it needs for an— than the energy that it needs for an average driver's —— so you — for an average driver's —— so you get _ for an average driver's —— so you get i_ for an average driver's -- so you get-— you get. i can imagine autonomous _ you get. i can imagine autonomous cars - you get. i can imagine | autonomous cars being you get. i can imagine - autonomous cars being graded north american cities with great light structures. here in london, less so. there's a huge challenge to solving autonomous driving and the kinds of unstructured compact, busy environments that we have here in london in many cities across the world in the traditional technology stack uses three main pillars, one is mapping and so, for the system store,

use an vehicles much like google since vehicles around the streets to map out street view images so we can navigate ourselves. but for vehicles, autonomous vehicles, this needs to be done is a much higher percent and so we have sent me to level detailed maps of entire cities and which is actually a remarkable solvable problem but very, very expensive to do an even worse to maintain. there is another limitation with current approaches in terms of the sensors that get used which are very expensive which our way of sending out beams of light, laser light in determining the amount of time that latex to give back and determine how far things are away. that's a wonderful centre and i love that type of information i used it in my previous work and it's hard to integrate into vehicles. in the third one is,

how the intelligence is set up and today, most approaches to autonomous driving is based on autonomous driving is based on a very modular system where you first try and detect all the cars and pedestrians and the traffic lights and whatever else you think you need and then you have some handcrafted rules and say, if this happens then i'm going to do this. if you think about the complexities of urban driving and the number of things that are going on, that this becomes incredibly unwieldy and very quickly in these three areas i think really held back the industry in a way of rethinking this with an alternative approach. so, we decided that we want to go after and although it's a harder problem in the short—term we believe it's much more scalable to avoid the need for maps, we want to avoid the need for very

sensors rely on cameras which are relatively inexpensive and easy to integrate and we drive with these two eyes every day. and finally, we are going to use a more holistic end to end machine learning approach where we teach the machine to drive rather than try to code those rules and by hand. thank you so much, we're going to come to you and made such great strides with your model, your solar car and it is expensive what i really want to know is when am i going to be able to afford one? whenever we went to get the commercially viable affordable family car? we wanted to _ affordable family car? we wanted to provide this for everyone _ wanted to provide this for everyone-— wanted to provide this for eve one. . , , , everyone. and this is selling for 250,000 _ everyone. and this is selling for 250,000 euros - everyone. and this is selling for 250,000 euros and - everyone. and this is selling for 250,000 euros and is i for 250,000 euros and is clearly— for 250,000 euros and is clearly not for everyone. the

way — clearly not for everyone. the way to — clearly not for everyone. the way to view this is the first car is — way to view this is the first car is the _ way to view this is the first car is the technology demonstration. you wouldn't get in the _ demonstration. you wouldn't get in the very— demonstration. you wouldn't get in the very limited series and is the — in the very limited series and is the main reason why this was person— is the main reason why this was person expensive. the key is in scaling — person expensive. the key is in scaling up — person expensive. the key is in scaling up and that is what we planned — scaling up and that is what we planned on the road map for 2025— planned on the road map for 2025 and _ planned on the road map for 2025 and be planned alone here too and — 2025 and be planned alone here too and in — 2025 and be planned alone here too and in terms of efficiency and therefore you can go and solar— and therefore you can go and solar panels. that one is going to have — solar panels. that one is going to have a — solar panels. that one is going to have a starting price of 30,000 _ to have a starting price of 30,000 euros. because of the look— 30,000 euros. because of the look at — 30,000 euros. because of the look at notjust 30,000 euros. because of the look at not just the purchase price — look at not just the purchase price but— look at not just the purchase price but the total cost of ownership of a car like this and — ownership of a car like this and if— ownership of a car like this and if you _ ownership of a car like this and if you start with electrifying a vehicle, the fuel— electrifying a vehicle, the fuel cost of having to charge her car — fuel cost of having to charge her car like this can be done to three _ her car like this can be done to three or— her car like this can be done to three or four. 0n her car like this can be done to three or four. on top of that, _ to three or four. on top of that, mix _ to three or four. on top of that, mix the car, the electric car twice _ that, mix the car, the electric car twice as efficient as most cars— car twice as efficient as most cars on— car twice as efficient as most cars on the road today and we recreate — cars on the road today and we recreate half of the current needs _ recreate half of the current needs for the average person for the — needs for the average person for the solar panels were

getting _ for the solar panels were getting into the range of median family in europe could afford — median family in europe could afford |— median family in europe could afford. ~' . ., afford. i think the challenge is different _ afford. i think the challenge is different and _ afford. i think the challenge is different and many - afford. i think the challenge is different and many ways, j afford. i think the challenge i is different and many ways, it is different and many ways, it is over promised, really. there's a lot so but autonomous vehicles will be can hope to have and they're not even legal in most countries of the moment. you're the chief scientist, set some realistic expectations are, what can i expectations are, what can i expect to see in the medium—term before we get to where the robots take over the world. �* where the robots take over the world. . ., , , world. are absolutely right. there have _ world. are absolutely right. there have been _ world. are absolutely right. there have been many - there have been many unrealistic— there have been manyl unrealistic expectations there have been many- unrealistic expectations by names— unrealistic expectations by names you _ unrealistic expectations by names you will— unrealistic expectations by names you will have - unrealistic expectations by names you will have all. unrealistic expectations by. names you will have all heard of saying _ names you will have all heard of saying that's _ names you will have all heard of saying that's just _ names you will have all heard of saying that's just round - names you will have all heard j of saying that's just round the corner. — of saying that's just round the corner, since _ of saying that's just round the corner, since from _ of saying that's just round the corner, since from the - of saying that's just round the| corner, since from the corner. that _ corner, since from the corner. that is— corner, since from the corner. that is simply— corner, since from the corner. that is simply not _ corner, since from the corner. that is simply not how - corner, since from the corner. that is simply not how it's - that is simply not how it's going _ that is simply not how it's going to _ that is simply not how it's going to he _ that is simply not how it's going to be. as— that is simply not how it's going to be. as can - that is simply not how it's going to be. as can be - that is simply not how it's going to be. as can be a l going to be. as can be a gradual— going to be. as can be a gradual transition- going to be. as can be a gradual transition it's i going to be. as can be a i gradual transition it's going to take _ gradual transition it's going to take time _ gradual transition it's going to take time and _ gradual transition it's going to take time and i - gradual transition it's going to take time and i would i gradual transition it's going i to take time and i would liken it to _ to take time and i would liken it to the — to take time and i would liken it to the transition _ to take time and i would liken it to the transition between i it to the transition between the card _ it to the transition between the card in— it to the transition between the card in the _ it to the transition between the card in the automobilel it to the transition between - the card in the automobile onto her years— the card in the automobile onto her years ago _ the card in the automobile onto heryears ago it— the card in the automobile onto her years ago. it happened - her years ago. it happened pretty— her years ago. it happened pretty quickly _ her years ago. it happened pretty quickly in _

her years ago. it happened pretty quickly in the - her years ago. it happened pretty quickly in the grand | pretty quickly in the grand scale _ pretty quickly in the grand scale of— pretty quickly in the grand scale of things _ pretty quickly in the grand scale of things but, - scale of things but, incrementally, - scale of things but, incrementally, dayl scale of things but, . incrementally, day on scale of things but, - incrementally, day on day, it was — incrementally, day on day, it was a — incrementally, day on day, it was a gradual— incrementally, day on day, it was a gradual process - incrementally, day on day, it was a gradual process but i was a gradual process but accelerated _ was a gradual process but accelerated as— was a gradual process but accelerated as the - was a gradual process but. accelerated as the economics and the — accelerated as the economics and the safety _ accelerated as the economics and the safety and _ accelerated as the economics and the safety and all - accelerated as the economics and the safety and all the - and the safety and all the other— and the safety and all the other things _ and the safety and all the other things that- and the safety and all the other things that came i and the safety and all the l other things that came with such— other things that came with such a _ other things that came with such a transition _ other things that came with such a transition came - other things that came with such a transition came to l other things that came with i such a transition came to bear and _ such a transition came to bear and it— such a transition came to bear and it will— such a transition came to bear and it will certainly— such a transition came to bear and it will certainly be - such a transition came to bear and it will certainly be a - and it will certainly be a muttiyear_ and it will certainly be a multiyearjourney- and it will certainly be a multiyear journey but . and it will certainly be a multiyearjourney but ii and it will certainly be a - multiyearjourney but i very much — multiyearjourney but i very much hope _ multiyearjourney but i very much hope and _ multiyearjourney but i very much hope and expect- multiyearjourney but i very- much hope and expect strongly that by— much hope and expect strongly that by the _ much hope and expect strongly that by the end _ much hope and expect strongly that by the end of— much hope and expect strongly that by the end of this - much hope and expect strongly that by the end of this decade, | that by the end of this decade, we will— that by the end of this decade, we will he _ that by the end of this decade, we will be seeing _ that by the end of this decade, we will be seeing this. - that by the end of this decade, we will be seeing this. git- that by the end of this decade, we will be seeing this.- we will be seeing this. at the end of this — we will be seeing this. at the end of this decade, - we will be seeing this. at the end of this decade, i - we will be seeing this. at the end of this decade, i will - we will be seeing this. at the end of this decade, i will find you and find out. what was your perspective on this? we you and find out. what was your perspective on this?— perspective on this? we talked about the ownership _ perspective on this? we talked about the ownership of- perspective on this? we talked about the ownership of a - perspective on this? we talked about the ownership of a car. about the ownership of a car that— about the ownership of a car that you _ about the ownership of a car that you buy and the biggest factor— that you buy and the biggest factor we have now is the price and that— factor we have now is the price and that is— factor we have now is the price and that is where this driving is going _ and that is where this driving is going to really help because the (hip _ is going to really help because the q—tip cost down and sharing, _ the q—tip cost down and sharing, making sure that we use the — sharing, making sure that we use the car with a lot more people _ use the car with a lot more people because the standing still 90% of the time in the key— still 90% of the time in the key to— still 90% of the time in the key to making sharing

convenient, i think that's where _ convenient, i think that's where autonomous driving comes in and _ where autonomous driving comes in and making sure the car acts like and— in and making sure the car acts like and liberal without a driver _ like and liberal without a driver and within two minutes, it's from — driver and within two minutes, it's from the door and you go there — it's from the door and you go there if— it's from the door and you go there. if you want to bring your— there. if you want to bring your driving panels and f150 putts — your driving panels and f150 pulls up— your driving panels and f150 pulls up and want to take the entire — pulls up and want to take the entire family and all your kids and many— entire family and all your kids and many van pulls up, if two dispose — and many van pulls up, if two dispose of, may be your super smatt. — dispose of, may be your super small, superefficient vehicle putts — small, superefficient vehicle pulls up _ small, superefficient vehicle pulls up. that way, we can drastically reduce the cost for a kilometre of actually doing business right on the striving comes— business right on the striving comes in— business right on the striving comes in but as to progress before _ comes in but as to progress before this happens it is to progress to a point where we praise — progress to a point where we praise autonomous driving based on the _ praise autonomous driving based on the cost and not as potential value because i think the first— potential value because i think the first companies they're going — the first companies they're going to _ the first companies they're going to be able to offer the services _ going to be able to offer the services of autonomous driving the going — services of autonomous driving the going to say we we're replacing taxi drivers in the taxi — replacing taxi drivers in the taxi driver takes percent for kilometre and we can make a lot

of money— kilometre and we can make a lot of money because we need to earn — of money because we need to earn hack— of money because we need to earn back the 100 billion we invested _ earn back the 100 billion we invested in until we get that cost — invested in until we get that cost down really to what it actually _ cost down really to what it actually costs to operate, then ithink— actually costs to operate, then i think we'll start to see this autonomous mobility being a lot cheaper— autonomous mobility being a lot cheaper than owning a car in the big — cheaper than owning a car in the big switch. and if we make those cars— the big switch. and if we make those cars electric or solar,. these — those cars electric or solar,. these help with the missions and especially when the electricity comes through renewable resources and its incredible but the batteries are a problem, are they? they retain a lot of rare earth metals that are at scale and a key component and had to get that out of the desert. is there a plan in place to mitigate those sort of environmental problems that

come from the technology? mining responsibility is very important and that's what more people are attuned to. we drank some of the coalitions that help ensure that we are mining responsibly and i think you're absolutely right that electric vehicles in general are better and more sustainable for the environment and a recent study of the university of michigan just went through some of the data and for north america, ev from a lifecycle perspective, critical to the grave, including all the manufacturing and the batteries still result in a 64% less harm to the planet and eyes of traditional gas vehicle would. there is definitely improvements their and we as companies and we as individuals and to make sure we

do it responsibly and is beginning to cleaner energy too down the road, that 64% of improvement will obviously increase and that is to increase and that is to increase very quickly. thank ou so increase very quickly. thank you so much. _ increase very quickly. thank you so much. who - increase very quickly. thank you so much. who in - increase very quickly. thank you so much. who in the . you so much. who in the audience would like to ask us a question of any of our amazing panelists today? i question of any of our amazing panelists today?— panelists today? i have a question _ panelists today? i have a question for _ panelists today? i have a question for linda. - panelists today? i have a question for linda. first | panelists today? i have a i question for linda. first of an. — question for linda. first of all. you _ question for linda. first of all, you said about the fuel cells, — all, you said about the fuel cetis, i_ all, you said about the fuel cells, i have a quick question because _ cells, i have a quick question because i_ cells, i have a quick question because i know f150, how much of the _ because i know f150, how much of the big — because i know f150, how much of the big vehicle it is. how are you _ of the big vehicle it is. how are you able to get people to really — are you able to get people to really adopt the use of electric and places like rural pennsylvania, upstate new york where _ pennsylvania, upstate new york where we — pennsylvania, upstate new york where we are very much a hunting _ where we are very much a hunting environment where we have _ hunting environment where we have due — hunting environment where we have due years push everything into the — have due years push everything into the back of the vehicle. how— into the back of the vehicle. how are _ into the back of the vehicle. how are you you able to get that— how are you you able to get that uptake? | how are you you able to get that uptake?— that uptake? i think a lot of it is really _ that uptake? i think a lot of it is really about _ that uptake? i think a lot of it is really about making - that uptake? i think a lot of.

it is really about making sure that the truck does exactly needs to do. f150 lightning can tell, whole and do all the things that a gas f150 can and in addition to it, we offer a lot more and we are leveraging a battery to provide electricity for customers and particularly in electrical outage situations we can actually use it for home and multiple things at a time. and with an engine, were able to take advantage of that space up front and basically turn it into a front trunk and the performance in the vehicle is just outstanding and you get that instant work that we told about earlier which gives you zero to 60 mph and mid four seconds. it is fast. i zero to 60 mph and mid four seconds. it is fast.— seconds. it is fast. i have a question — seconds. it is fast. i have a question from _ seconds. it is fast. i have a question from gilbert - seconds. it is fast. i have a l question from gilbert coming through on the video link. gilbert, if you can unmute your

microphone. gilbert, if you can unmute your microphone-— microphone. why was the light here zero release _ microphone. why was the light here zero release so _ microphone. why was the light here zero release so late - microphone. why was the light here zero release so late when j here zero release so late when we expected _ here zero release so late when we expected so— here zero release so late when we expected so much- here zero release so late when we expected so much earlier? | here zero release so late when i we expected so much earlier? —— lightyear — we expected so much earlier? —— lightyear bar— we expected so much earlier? -- lightyear-— lightyear. by was the lightyear so late? we — lightyear. by was the lightyear so late? we set _ lightyear. by was the lightyear so late? we set out _ lightyear. by was the lightyear so late? we set out to - lightyear. by was the lightyear so late? we set out to build . so late? we set out to build the score — so late? we set out to build the score was _ so late? we set out to build the score was six _ so late? we set out to build the score was six years - so late? we set out to build the score was six years ago | the score was six years ago we found — the score was six years ago we found that _ the score was six years ago we found that the company but we are a _ found that the company but we are a go— found that the company but we are a go straight out of college, we had no money or experience and besides having to engineer a experience and besides having to engineera car, experience and besides having to engineer a car, we also had to engineer a car, we also had to build — to engineer a car, we also had to build a _ to engineer a car, we also had to build a company and we've been — to build a company and we've been trying to do the engineering of the vehicle and hooting — engineering of the vehicle and booting the company at the same time and — booting the company at the same time and whether we set up for success in— time and whether we set up for success in the future. we were notjust— success in the future. we were notjust engineering a car, are also _ notjust engineering a car, are also engineering all the processes and systems behind it and i_ processes and systems behind it and i do — processes and systems behind it and i do keep track of this, how— and i do keep track of this, how do— and i do keep track of this, how do you actually make a car so the — how do you actually make a car so the next time we do it, you have _ so the next time we do it, you have a — so the next time we do it, you have a clear process flow and we know _ have a clear process flow and we know how to get there. and along _ we know how to get there. and along the — we know how to get there. and along the way, the challenges, we talked about one on the

solar— we talked about one on the solar panel, we develop motors that are — solar panel, we develop motors that are directly there and we haven't— that are directly there and we haven't seen this in production vehicles — haven't seen this in production vehicles yet and a lot of testing _ vehicles yet and a lot of testing and vehicles to get those _ testing and vehicles to get those reliable and working, overall. _ those reliable and working, overall. i_ those reliable and working, overall, i think the fear question is when we first started _ question is when we first started the company but were five and — started the company but were five and experience guys, we usually — five and experience guys, we usually underestimate the challenge of getting a car into production. maybe that's a good thing _ production. maybe that's a good thing because if we had known, i thing because if we had known, idon't — thing because if we had known, i don't know if we would've started _ i don't know if we would've started it. it's really hard to start — started it. it's really hard to start a — started it. it's really hard to start a car— started it. it's really hard to start a car company. that's the best— start a car company. that's the best answer to your question. one _ best answer to your question. one last — best answer to your question. one last question in the room here. look around, the lady of the left ear. here. look around, the lady of the left ear-— the left ear. i'm from the r0 al the left ear. i'm from the royal academy _ the left ear. i'm from the royal academy and - the left ear. i'm from the royal academy and have | the left ear. i'm from the | royal academy and have a question— royal academy and have a question for— royal academy and have a question forjamie - royal academy and have a question forjamie and - royal academy and have a question forjamie and bel royal academy and have a - question forjamie and be heard in the _ question forjamie and be heard in the news, _ question forjamie and be heard in the news, self—aware - question forjamie and be heard in the news, self—aware ai - question forjamie and be heard in the news, self—aware ai andl in the news, self—aware aland concerns— in the news, self—aware aland concerns about _ in the news, self—aware aland concerns about that. _ in the news, self—aware aland concerns about that. do - in the news, self—aware aland concerns about that. do you i concerns about that. do you think— concerns about that. do you think as _ concerns about that. do you think as capability— concerns about that. do you think as capability of- concerns about that. do you think as capability of ai - think as capability of ai increases, _ think as capability of ai increases, you - think as capability of ai increases, you might . think as capability of ai - increases, you might actually iet increases, you might actually get bored _ increases, you might actually get hored of— increases, you might actually

get bored of driving? - increases, you might actually get bored of driving?- get bored of driving? well, i think that's _ get bored of driving? well, i think that's a _ get bored of driving? well, i think that's a fascinating - think that's a fascinating question, rather philosophical one and — question, rather philosophical one and perhaps, the way that al systems today work and will ai systems today work and will work _ ai systems today work and will work for — ai systems today work and will work for the foreseeable future _ work for the foreseeable future, they are essentially, with — future, they are essentially, with a — future, they are essentially, with a neural network, an artificial— with a neural network, an artificial network is essentially a lot of multiplications and additions and that's all it is, literally all it— and that's all it is, literally all it is— and that's all it is, literally all it is and, the gp, the graphics— all it is and, the gp, the graphics processing units that evaluate _ graphics processing units that evaluate these artificial neural _ evaluate these artificial neural networks, theyjust sit there — neural networks, theyjust sit there, chart all day and do very— there, chart all day and do very basic mathematical calculations and outcomes the answer — calculations and outcomes the answer. and unless there are fundamental changes in how these — fundamental changes in how these systems operate, which is entirely— these systems operate, which is entirely possible in terms of research _ entirely possible in terms of research and breakthroughs, there's— research and breakthroughs, there's no chance in my mind that—

there's no chance in my mind that these _ there's no chance in my mind that these things will get bored _ that these things will get bored in that sense because they're _ bored in that sense because they're just doing the job that they— they're just doing the job that they are — they're just doing the job that they are executing again and again— they are executing again and again through these multiplications. love that question- _ multiplications. love that question. it _ multiplications. love that question. it brings - multiplications. love that question. it brings us - question. it brings us perfectly to the end of this programme. we've heard about everything from the future of solar and electric vehicles and ai and even touching on the first ai strike i think on behalf of the bbc world service, whether you're joining us via the internet or around the world are here with us in this fabulous information age gallery, please give a warm round of applause to our brilliant pioneering engineers.

hello there. it's turning even hotter with temperatures 35, maybe 36 degrees. dry, sunny, hot for most this weekend but in northern and western areas you could start to see a few showers developing, particularly through the day on sunday. southern parts of britain that really could do with rainfall, for example 0dium in hampshire hasn't seen any measurable rain for 42 days the ground is parched here, we really do need some rain. the met office amber extreme heat warning remains in force for large parts of england and well up until around sunday. those temperatures reaching 35, maybe 36 degrees

in the hottest spots on saturday afternoon. widespread sunshine through saturday any low cloud and mist and will burn back to the coast, maybe a slight chance of a shower across the scottish hills, may be snowdonia, high 20s in the north, 35 to 36 degrees across england and wales. saturday night it will stay dry for most, a bit of low cloud, mist and work across eastern scotland, northeast england. temperature wise, again the low to mid teens in the north on 17 to 20 degrees for the south, really could be quite warm and comfortable across the south coast of england. sunday we do it all again. a sunny start, mist and low cloud burning back but a chance of showers and thunderstorms developing across northern ireland, scotland into the afternoon, maybe one two across western england and wales later in the day. the vast majority will stay dry and sunny and very hot again, 30 to 36 england and wales for the a touch cooler,

scotland and northern ireland around the mid 20s. we start to see changes into next week of the things sort of a cooler and we will start to see more in the way of showers and thunderstorms low pressure pushing up from the south as we move out of sunday. that will introduce more humid air it could be quite uncomfortable for a well sunday into monday but you will see the shower and thunderstorm activity such increase. initially northern and western areas and migrating towards the east. you will see temperatures very warm to start the week across the southeast and then showers, thunderstorms rattle their way through, things will be turning cooler, closer to the seasonal average by the time we reach the end of the new week.

this is bbc news — i'm rich preston. our top stories: the acclaimed author sir salman rushdie suffers serious injuries, after being stabbed on stage in the state of new york. his agent says he's on a ventilator and can't speak and is likely to lose an eye. in other news, it's been revealed the search warrant for donald trump's florida home was partly based on suspicion of violations of the us espionage act. ukraine and russia have again accused each other of risking catastrophe by shelling europe's largest nuclear power plant. and the eurovision host contest — the shortlist is announced for the cities who may stage the famous celebration of song.