 Good. All right, well, thank you for having us here. As was mentioned, my name is Carl Dietrich. I'm the co-founder and chief technical officer at Terrafugia. Terrafugia, our mission is to make personal flight more practical for everyone, to truly turn the dream of a flying car into a practical reality. We were founded in 2006 by five graduate students at the Massachusetts Institute of Technology. We're now within two years of delivering our first product, the transition, a prototype of which is out here on the floor, the exhibition floor. We currently employ about 100 people around the world, with offices in the Boston area, Hongzhou, China. And we're opening an R&D center here in the San Francisco Bay Area. And we are here because we're hiring. It's a very exciting time for us. My background, I received my PhD from MIT's Department of Aeronautics and Astronautics. And I've been a pilot since high school. So this has been a personal passion of mine for a long time. And as was mentioned, the big news this week is that Terrafugia is now part of the same family of companies as Volvo and Lotus. We were just acquired by the Zijang Geely Holding Group, which has a tremendous financial depth and access to global markets. So it's a very exciting time for Terrafugia as a company to have access to not only the financial backing of this global automotive company, but to also have the access to the global markets that we've been seeking for a long time to truly disrupt personal mobility. Why are we interested in this? Why is a company like Geely acquiring a small startup like Terrafugia? Well, somewhere between 2% to 4% of the global GDP is lost due to things like traffic congestion. Currently, about half of the world's 7 billion people live in urban areas. And that number is growing by about 60 million people a year. So the growth number is about seven times the population of New York City. It's incredible, and it's not changing. It's just going to continue going in this direction. So you look at traffic congestion. I took this picture actually out of the front window of a taxi cab in Beijing. And this is typical. It's actually worse now in China than it is here. And you look up, and there's a whole lot of room up there. So this is an old story. We've all heard this for more than 100 years, and we've kind of written it off. People have been flying for 100 years, but why don't we fly more today? Little airplanes have been around for a long time, but it really is a niche industry. There are only about 160,000 general aviation airplanes out in the field right now, and only about 600,000 private pilots. Almost everybody has a driver's license, but less than a fraction of a percent of the population in the United States know how to fly. There's lots of training required, certainly a major barrier. Typically, getting a private pilot's license would take about 60 to 70 hours. The minimum requirement was 40 hours. And you have to learn a lot. You have to learn a lot of rules. You have to develop physical skills to land an aircraft. And then once you do become a pilot, there are some major barriers that keep pilots from flying small airplanes today. Little airplanes are fundamentally more weather sensitive than large commercial airliners. So weather is one of the biggest reasons that pilots don't fly more often. There's a high recurring cost of ownership to keep an aircraft. And they don't achieve the true time savings that is possible by flying at 150 miles an hour. On average, a pilot spends about half an hour stopped at an airport, just switching between driving and flying overhead. And then finally, most of the 5,000 public use airports around the United States have no rental car counters. The industry just isn't big enough to justify Hertz or Avis setting up a little counter at most of these little airports. That said, these little airports are our nation's largest underutilized transportation resource. They exist out there and very, very few people use them. These are not the SFOs. These are the small regional airports. This is what we are trying to do at Tarifoodia, is take advantage of the infrastructure that exists, bring some new technology into the equation, and see if we can change the way, start to change the way we get around. Our first product is called the transition. I'll show a brief video of that now. So the transition is really targeted at this existing market today, the general aviation pilot population. It allows them to keep their aircraft at home in their garage, saving hangar expense. You drive it on normal roads, just like driving a normal car. You fill it up at the gas station, just like you fill up your car. It's all about convenience, making it more practical, bringing it home. You drive to one of these little airports, go in the gate, unfold the wings in about 40 seconds, do your pre-flight inspection, and take off, flying to your destination over whatever traffic exists at a speed of about 100 miles an hour direct. And then when you land at the airport, you fold up the wings in another 40 seconds, and you drive right to the door of where you want to be. So the transition was designed to fit inside a new category of aircraft called light sport aircraft. That has a 20-hour training minimum instead of a 40- hour training minimum. Most people get their sport pilot certificate in about 35 hours. So by bringing the product into that category, we really are lowering that initial training barrier. We make it very, very simple to fly. Because you can drive in bad weather, the vehicle is less sensitive to the weather variability. The high recurring costs of ownership are reduced by allowing the operator to keep their aircraft at home. And because the aircraft runs on normal automotive gasoline instead of aviation fuel, which is both better for the environment, and about half the price, it's actually quite a bit more economical on an ongoing hourly basis. Because the pilot spends less time stopped on the ground at the airport, they can actually beat much higher performance aircraft on a given door-to-door trip because they spend less time stopped. It's very simple. There's no magic here. And then, of course, because you don't have to worry about renting a car, the fact that most of these little airports don't have any sort of rental car counter or many of them don't have Uber's nearby even, it's not an issue. So this is our first step. And because this is a technical conference, I'm going to go a little bit more into the detail of some of the really cool technologies that we're integrating into this first product. And some of that insight will sort of give you a vision as to where we are headed in the future. First, we'll start with some of the more traditional aviation technologies. The transition has a fairly extraordinary custom wing design, and if you come to our booth, you can see this in person. We developed a custom airfoil for the vehicle due to a number of very interesting constraints. We have a wing that folds up against itself, so we wanted something with a flat bottom to minimize the aerodynamic impact of having a hinge on the bottom of the vehicle. It is not what's called a natural laminar flow airfoil. This is a little bit more draggy, but that gives it ability to resist changes due to the buildup of road debris. So if you're driving around on the road and you get dirt splashed up on the leading edge of your wing, it's not going to dramatically change the performance of this vehicle. It achieves one of the highest maximum lift coefficients of any 2D airfoil section without a flap. And it has a very low moment coefficient, which means that we can keep the tail volume, the tail much shorter, allowing the vehicle to fit inside a garage. Are there any aero engineers anywhere in this building? OK, all right, one of them. All right, so for you. This is some data on that. At a higher level, what is this? One of the things that we're very proud of at TerraFugia is that by bringing the transition to market, we expect to statistically improve the level of safety of personal aviation. And that comes from a variety of things. The visibility out the front of the vehicle is actually quite extraordinary. Most aircraft you're sitting either on top of a wing or right underneath a wing. In the transition, you sit in front of a wing. You can see out to the side, front or down. You don't have to worry about making clearing turns. Any pilots in the room? Maybe one. All right. OK, we have an angle of attack indicator. One of the leading causes of fatal accidents in small general aviation aircraft is simply loss of control. The aircraft on a turn from base leg to final will exceed the maximum angle of attack. And the aircraft will stall and auger into the ground by having knowledge of where you sit relative to your stall angle of attack. You can avoid that sort of situation. In addition, once you do stall the aircraft, the vehicle has very, very benign stall characteristics. This picture actually is a picture of the vehicle in a fully-stalled flight. You'll notice the little black tufts are making all sorts of crazy shapes near the fuselage of the vehicle. Basically, what that means is the flow is very unsteady there. The airflow is separated near the root of the wing. But you'll also notice that if you look out near the edge of the wing over the aileron, out on the outboard section, the airflow is very nice. What this means is that even when the aircraft is fully stalled, the pilot actually still has control over the role of the aircraft. It's still flyable, even in stalled configuration. So that's what we mean by very benign stall characteristics. It's very hard to get into a situation where you would be out of control. We have yet to achieve it in this vehicle. This vehicle has a much lower pilot workload than any normal general aviation aircraft. These things probably don't mean anything to you folks in the room, but let me just put it this way. It makes it much more like driving a car than flying an aircraft. Aircraft today, most of those little GA airplanes, are flown the way cars were driven back in the 30s. There is manual control of the mixture. They have carburetors. They have all sorts of manual control things that, frankly, the automotive industry solved 50 years ago. So we are really bringing general aviation into the 21st century and making it as simple and easy and reliable to fly as possible. Since we don't have any pilots in the room, I won't get into any of these other issues on the bottom, but the real key here is we designed the vehicle from a pilot's perspective to be psychologically help pilots make good choices. Pilots still are key to the equation. And there is a lot of interest right now. We're very interested also in bringing the technology to market that will allow machine learning and AI to make it even more safe in the long run. There are some major, major barriers to achieving the level of reliability of a human being. Statistically speaking, a human being, a human pilot, makes a fatal mistake once every about 10 to the fifth hours, once every 100,000 hours. Given the variable circumstances that the pilot has to deal with, that's actually rather extraordinary. And while, in theory, we can contemplate AI and machine learning algorithms that might someday get to that level, it's extremely difficult to compensate for all the failures, all the sensor failures, and maintain the perspective of your situation that a human being can do intuitively. And we're not there right now. So in the meantime, we're making it easier for the pilot with the idea that if we make it easier for the pilot, that will actually make it easier for the machine learning algorithms in the long run. One other very cool technology that we bring in the transition is a full vehicle parachute. So if all else were to fail, you can pull a handle and bring the entire aircraft down under a parachute. The vehicle incorporates automotive crash safety features. So we have a safety cage, crumple zones, integral fuel cell. These are things you don't see in general aviation today. We really are setting the highest bar for safety in the GA industry. We've done extensive simulated crash testing of the vehicle, all sorts of different scenarios. And you really do push the state of the art of simulation as you do this type of analysis. Any composite material experts in the room? Not so much, maybe. Yeah, over there. OK. So you know that the failure of composite materials is extremely difficult to predict. How much energy will that failure incur? You can predict about when it will fail, but not necessarily how it will fail and how much energy will be absorbed in the process of failing. So we use isotropic materials, aluminum, to absorb energy in a collision. And we rely on carbon fiber and composite materials for our rigid structures that we want to keep intact to protect the occupants. So we take these simulated crash pulses and we feed them into simulated crash test dummies. So we can actually do a full range of crash testing and have expectations for what sensors in an actual physical crash test dummy would output before we actually do any sort of physical crash testing. And that helps us reduce the cost of our development program. Some of the other very cool technologies. So right now there's a lot of buzz in the aviation industry about electric and hybrid electric propulsion systems. And there's good reason for that. The specific power of electric motors is on the order of five kilowatts per kilogram. The specific power of a certified gas turbine engine, a jet engine that would be on an aircraft today, is about half of that. So we're almost doubling the specific power. So what's the big problem with electric propulsion for aircraft? It's the energy. It's the battery. The battery technology to do pure electric flight is just on the edge of being viable today with mandatory legal reserve minimums. The FAA requires for a flight in what's called visual flight rules, you have to have at least a half hour reserve. So whatever amount of energy you need to get to your destination, you need to be able to fly for at least a half hour more. That's very difficult to achieve with today's battery technologies unless you go to vehicles that are more like sail planes that are extremely efficient and less practical for what we would call normal flying missions. That said, electric can have a big impact on aviation, particularly if we go to hybrid configurations where we're still relying on fuel for the storage of energy. And we use the electric motor to provide additional power in certain situations, like in takeoff, high rates of climb situations. So this is an example of one of the system architecture that we have in the transition, where you have a traditional certified aircraft engine driving power back through to a propeller, and you have a motor generator on that prop shaft that powers a bus. And that allows us to, gives us the flexibility of using electric ground drive when we're driving on the road. But it also gives us a very cool capability, which no other aircraft has out there right now, which is the ability to have effectively an electric power boost or what we would call an electric afterburn, which is going to be a very nice feature if you're a pilot of these things. Imagine you're in a situation where you're at a high density altitude and you need to climb out a little bit faster. You can kick in an extra 20% power. You notice that. That all goes into climb rate. So it's a fantastic safety feature that you're giving the pilot. You can't do that for more than a couple minutes, because of the limit on the battery capacity. But just being able to do it for 30 seconds can change, can save somebody's life. And that's really what you're talking about. When it comes down to it, aviation is all about safety, right? Making these things work reliably, consistently. And not only will this be a fantastic safety feature, it's actually going to be a whole lot of fun for a pilot. Some of the other new technology that we're integrating into the transition is a data network that's fully deployed now, satellite and ground-based data stations, part of this ADS-B network, where all aircraft in key parts of the national airspace will be required to broadcast GPS position and heading to this data network, and it's freely available. So effectively, when we deploy a transition, you'll have an image of all the other air traffic around you that is something that today you would not have in a normal general aviation aircraft unless you had radar on board. This way, we get the effect of long-distance radar capability allowing you to steer clear of other traffic. I alluded a little bit earlier to machine learning and AI. One of the big problems with incorporating machine learning and AI into aircraft is that the FAA, the way they certify products, is they need to know if your system gets this input, what's the output going to be? And how can you prove to me that it's going to be that output with this level of reliability? That's what certification is all about. By its very nature, machine learning and artificial intelligence, you can't do that by the definition of machine learning. This is a huge problem for the certification of the future of flying cars. We would like to implement nondeterministic algorithms that give us new capabilities that we don't have today. I mean, the pilot at its heart is a nondeterministic algorithm. The FAA is comfortable with giving a person a pilot's license, but they're not yet comfortable with giving an algorithm a pilot's license. So how are we going to get around that? This is the current proposal, and it's evolving into an industry standard right now. We're very heavily involved in the committees that are creating these standards. Basically, you have a monitor system, a safety monitor system that is certified. So while normally you may be operating with this complex or nondeterministic algorithm, you have a safety monitor system that can switch it off and implement a certified recovery maneuver. So this type of concept is not very sophisticated, but it already has been employed and fielded. And this is just a very cool video that I want to share of one of these systems. This is what's called automatic ground collision avoidance. So if the system has a model of the performance of the vehicle, and it has a terrain model of the land around you, and if the safety monitor on board predicts that you're getting too close to the terrain, it will execute an automatic recovery maneuver. This system has been fielded on F16s and is already credited with saving four lives. This is not our work. This is actually work that's been pioneered by a team at NASA Armstrong. But it's an example of the type of technology that we're hoping to bring to market. So what you see here is a cockpit view on F16. This pilot is pulling a 9G turn. And they black out in the middle of a 9G turn with full afterburner on. And they wind up rolling into the ground. So you can see the altitude display on the right. So he's up at 17,000 feet right now. And now he's basically nosed over because he's blacked out, heading towards the ground. Two, recover. Two, recover. Two, recover. That's the automatic system kicking in and recovering. The pilot had blacked out. He would be dead without that system on board, without that safety monitoring system. And he recovers consciousness and can fly away. So that's the kind of thing that we're talking about implementing with that sort of algorithm. So let's create a vision now for what we could do if we had machine learning capability on board. We could do things like planning smart routes. If you had a deterministic route planner today, and you looked at the weather, particularly in the San Francisco Bay Area, oftentimes in the morning, you have fog come in. But oftentimes it burns off by a little bit later in the afternoon. Pilots know that. So a pilot could plan a route that takes into account some of that experience, some of that knowledge that they've gained through the years. And they could achieve more missions, which in the end could achieve those missions safely. Whereas if you had a hard-coded algorithm that if the visibility wasn't good when you wanted to depart, you wouldn't be able to go. At the same time, pilots may know that, hey, you know, about three o'clock in the afternoon, the winds pick up at this particular airport. And therefore, I'm actually not going to fly into that airport because that's going to be crosswinds, and I'm probably going to be uncomfortable. I'll be outside my personal limits. So I'll fly to this other airport where I'll have better winds. Again, those sorts of things, those are decisions that pilots make today that are very, very difficult for a computer to code in because they have to do not only with the performance of the system, but weather and things like that that are very, very hard to predict. But if you have some experience with the local environment, you can make better decisions, safer decisions, and decisions that allow you to also be more productive. So that's why we want, in the long run, to enable things like machine learning in personal aviation. So the long-term vision for flying cars. Many of you will see lots of media about flying cars, not only from TeraFugia this week, but there are a number of different companies all around, particularly in the Bay Area. Airbus is doing the A-Cube Vahana program here. Boeing just acquired Aurora Flight Sciences. They're doing an urban electric vertical takeoff and landing vehicle. TeraFugia is also entering the vertical takeoff and landing space with electric vertical takeoff and landing capability. Our plans are not public yet, but they're very exciting. And I'm very excited about the future that we've got in front of us. So if you are interested in this space, I hope you'll come by our booth. We are right now hiring controls engineers, aero engineers, systems engineers, electrical engineers, embedded software folks. And I'd like to talk to some machine learning folks who want to be in on the next generation of transportation. That's it. Thank you very much.