The Cube presents On The Ground. We're welcome to SiliconANGLE The Cube's exclusive coverage of On The Ground here at Ford Silicon Valley headquarters for R&D advanced car technology, all the secret sauce. I'm John Furrier, the host of The Cube. Ken Washington's vice president of research and all the car engineering here in Silicon Valley. First of all, congratulations on a success. CEO Mark Fields is out here. Huge contingent, a lot of big announcements. But first, congratulations for all the work you've done in Silicon Valley. It's been fantastic to watch you guys from the beginning, just amazing growth. Thank you very much. It's really great to be literally part of the Silicon Valley ecosystem. That was our intent when we came out here more than three years ago. And we expanded that presence about a year and a half ago. And now we're working pretty well here as a member of the Silicon Valley community. We see companies come and go in Silicon Valley. It's like laps around the tracks of cycles of innovation. You guys did something different. You dug in here. You dug in here with leadership and from the top down endorsement. Also, you had some real tech shops coming in and developing what was a nascent area now growing very rapidly. The autonomous car, the big announcements today, was huge moonshot-like announcement. Shipping in mass production, autonomous vehicles, driverless cars by 2021. Just for me, personally, that's the year after that. My son's going to be a freshman in college then. Just four more years. It's going to be pretty amazing. That is a huge, bold move. And you got the announcements on technology partnerships, on the sensors, and a machine learning acquisition, and expanding, and really doubling, tripling your footprint here in Silicon Valley. So take us through that. What's going on today? Share with the folks what we just heard. And also, I live streamed on my Facebook page, facebook.com, slash John Furrier, if you want to watch the whole keynote. Tell us what's happening. OK, great. Well, thanks for the acknowledgement. We're really excited about our announcement today and about the time that we're in the history of the automotive industry. We are at a pivotal time in the history of the automotive industry, where it's as big as automation for the vehicles, as big as the introduction of the moving assembly line. More than 100 years ago, if you think about it, 100 years ago, people couldn't afford cars. They were made for the luxury, for the rich. And that opened it up to everybody to have a car. The same thing is going to happen with autonomy. So that's the first element of our announcement is we're going to make mobility and having transportation as a service available to the masses by putting a fully autonomous vehicle into a ride or a ride sharing or a ride service in the year 2021. And the reason that we're excited about that is it's going to make people's lives better and it's going to open up new business opportunities for expanding our business as we continue to move from being an automaker to an automaker and a mobility company. So that was the first thing. And we're so excited about that. It's the right time to do it. And we've got the right capabilities to pull it off. You guys literally have no pun intended. Pole position, if you will, on this race to AI, machine learning, autonomous vehicle, certainly in driver's cars. You're seeing Uber, you're seeing Lyft. A lot of people seeing the success and their relationship with the car is changing. We've certainly had that conversation. But the CEO of Ford and your CEO Mark feels up there. Really talking a different vibe here. He's talking about how the company is totally behind this. They see this with societal benefits. So I want you to help bridge the gap for the folks watching who might say, how does this benefit me? Joe Six back in the middle of America is obviously, and it's going to certainly help people move from point A to point B. But the technology underneath it is complex. I mean, consumers are either using Windows or Macs and they've seen the blue screen of death. They know what the spinning wheel is like. Software isn't perfect. What are you guys doing? What are the engineers doing? How do you resolve that kind of fud or that cognitive fear that someone might have? Well, I mean, you said it well, which is the fact that autonomous vehicles are new to most people. I mean, you talk about autonomous vehicles, it sounds very science fiction-y, right? We've been doing this for over 10 years. And the reason, we haven't been very vocal about talking about our autonomous vehicle strategy and plans because we're not in a race to do it first. We are focused on doing what's right for our customers, which means we wanted to take the time to build a strategy that we can be confident in that's gonna allow our vehicles to be safe, to have the kind of reliability and the kind of capability that will allow us to take the driver fully out of the loop at level four. And having a vehicle that is fully autonomous at level four is really an important distinction here because it means that it's got the capabilities so that you don't have to have a driver re-engage, which we think is really hard to do. So the capability to do this, we're positioned to do it because we've been doing safe transportation for over 100 years. It's often overlooked that an autonomous vehicle is a vehicle, right? So there's sophisticated software to do that path planning, the sensing, but it also has to bring some pretty sophisticated engineering to the vehicle to allow the software to interface with the vehicle. We've been doing, that's table stakes for us. We've been doing that for over 100 years. We know how to build a vehicle that has redundant actuation, that has the right feel, that has the right safety, that has the right reliability, and then to integrate in with the software to make the whole system reliable and safe because trust is huge. And we have the trust of the American and the global public and we plan to retain that trust. And the key is not to do it first for the sake of doing something from an announcement standpoint. Doing it right is key, it's really respectful. I gotta ask you about the digital transformation. It's a buzzword, certainly. We hear all the time, most enterprise companies saw, oh, digital transformation, but really look at what the iPhone did almost 10 years ago. And you see in the evolution with map technology, this is what consumers are living right now. Snapchat, all the social networks, a new fabric, a digital transformation. But in a way, the car is in an analog world. So talk about some of the technologies that you guys are doing because maps and what they see in the real world is not digital, you guys have to convert that to digital. This is an exciting era. Can you just tease us a little bit about how that technology works? Because that's a new field of science that is really being explored. Can you share your thoughts there? Sure, so our current vehicles you can buy today have a lot of digital technology. There are tens of thousands of lines of software that are on our vehicles today. And so the vehicle, the automotive, the automobile is going through that same digital transformation that our consumer products that are so visible in our lives are going through at the same time. And it's accelerating. So that acceleration has brought lower cost, more capable sensors into vehicles. It's brought more sophisticated software that can be embedded into the vehicle so that you can do some amazing things like have the vehicle drive itself with the kind of reliability and the kind of safety that allows you to remove the steering wheel, take the pedals out of the vehicle, and make it a fully autonomous vehicle. That acceleration is happening and it's only getting faster. So our partnership, for example, that we announced today with Velodyne, it's all about accelerating the advancement of that digital hybrid device that does some amazing sensing using light to determine what objects are within a few hundred meters of the vehicle and how fast they're moving. If you can do that, then you can plan a vehicle and not hit it. You know, I asked you this question before. I'm going to ask it again because it's always a trick question. Is the car a peripheral or a computer? And you said last time a little bit of both, but you know, I looked in the trunk and taking the analog world and converting it into digital, which you guys have in software, is not easy, mapping technology, understanding moving objects, having the sensors. You need the compute. I mean, this is a data center on wheels. There is nothing about developing an autonomous vehicle that's easy. So we have a very capable team of more than a hundred people, more than 20 roboticists, lots of people doing data and analytics, IT team that's building big data centers to help us process information as we do our testing. We've got engineers that are helping us integrate these tech software into our vehicle hardware. We've got people evaluating different compute platforms that can be shrunk and put into the trunk. We're looking at different design architectures for where to put the light or sensors, how to design the interior so that it's got the right safety and look and feel. And so people want to ride in the interior. All of this is very, very complex, but that's what we do it for. We take on hard problems and we make it look easy so that we can provide the kind of service to our customers. Final question for you. As you recruit talent to come in, solve these problems. Obviously my son who's in college asked me a question. He's kind of intrigued by this, a new kind of computer engineer, new data engineers are out there, but you have the old school physics and the blocking and tackling engineers. How do those two worlds come together and what kind of people are you guys hiring here in Silicon Valley? What are some of the profiles? Are there new job titles that are popping out of this? Are there new ways, new job opportunities? Just share with the folks kind of the skills you're looking for, for this next generation innovation cycle. Sure, those two worlds are colliding together in pretty creative ways. And so we're continuing to look for really great engineers of all types, electronic engineers, people that understand physics so they can help us with our LiDAR development and placement, people that understand electrical engineer, we're looking for software engineers. I used the term roboticist earlier, earlier and that's kind of new for us. And those roboticists are helping us understand how do you automate some of the complex tasks that you need to do on an autonomous vehicle? And we're also looking for people that know how to do complex data manipulation, data analytics people and machine learning experts. So it's a pretty wide field of expertise that we're looking for. We're hiring and we're growing and we're having some great success. Cause in our experience, the young professionals that are coming out of our universities today, they want to work on things that matter. They want to change the world. And we're going to change the world with this autonomous vehicle that we announced today. They also want to work on hard things. They want to be challenged. And the autonomous vehicle is a challenge. And so the combination of being challenged and working on something that matters and working with other people that are fun to be around and have what we call one four behaviors makes for a really great combination, which is why we're expanding here in Silicon Valley. Congratulations Ken Washington here. We're, this is exclusive coverage from Silicon Angle theCUBE on the ground here in Palo Alto, the big announcement here, the three big announcements, car shipping and mass production by 2021 in five years, bold move. Congratulations, more coverage after this break. Thank you for watching.


Hi, I'm Emmanuel. In this video, we're going to be using the Tile-Suppler Mnemonic to draw a graph. Let's use an example of an experiment in which we measured the position and time for a car moving in a straight line. Firstly, we want to give our data a caption, which can be, the position as a function of time for a mini electric toy car travelling at a constant velocity. The car was at a position of minus 0.8 at time equals 0, Posted notes were used to mark the position of the car at each time step, a stopwatch was used to measure time, and a ruler was used to measure position. Next, we need to identify the independent and dependent variables, which are in the column headers of the table. The independent variable is time, which can be represented by the symbol of t, and the dependent variable is the position of the car, which can be represented as x. We can then include these symbols at the end of our axes. Then, we need to draw a uniform scale. As position is a vector quantity, it goes into negative values. As you can see, our data will cover at least half of the x-axis going up to 10, and half of the y-axis going up to 4.6. After that, we add units in brackets. Time is measured in seconds, which is symbolized by s, and position in meters symbolized by the letter m. Then, we plot our points. Each row of the table is a set of coordinates which we plot on the graph. Even though the values don't increase evenly in the table, as seen by time jumping from 2 to 4 to 5 to 10, these are spaced out when they are plotted. As you can see in the position column, there is an uncertainty of plus or minus 0.2 meters. We represent this on our graph using error bars, where the line goes 0.2 above and 0.2 below the point we have plotted. Finally, we draw a line of best fits. As you can see, we haven't forced it through any specific points, and it represents the trend of the data. So, hopefully now you have a better idea of how to draw graphs using the mnemonic of tau suplen, which you would use a lot in your studies of science.