In the coming years, mobility solutions--or how we get from point A to point B--will bridge the gap between ground and air transportation--yes, that means flying cars. Technological advancements are transforming mobility for people and, leading to unprecedented change. Nand Kochhar, vice president of automotive and transportation for Siemens Software says this transformation extends beyond transportation to society in general. "The future of mobility is going to be multimodal to meet consumer demands, to offer a holistic experience in a frictionless way, which offers comfort, convenience, and safety to the end consumer." Thinking about transportation differently is part of a bigger trend, Kochhar notes: "Look at few other trends like sustainability and emissions, which are not just a challenge for the automotive industry but to society as a whole." The advances in technology will have benefits beyond shipping and commute improvements--these technological advancements, Kochhar argues, are poised to drive an infrastructure paradigm shift that will bring newfound autonomy to those who, today, aren't able to get around by themselves. Kochhar explains, "Just imagine people in our own families who are in that stage where they're not able to drive today. Now, you're able to provide them freedom." Laurel Ruma: From Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic today is the future of mobility. In 2011, Marc Andreessen famously said, "Software is eating the world."
Austin Russell is the 25-year-old founder and CEO of Luminar, a startup in Silicon Valley that makes LIDAR sensors for self-driving cars. LIDAR technology had been used for short-distance mapping, but Luminar claims to have a functioning LIDAR that works at 250 meters, which is a breakthrough. Luminar recently went public, making Austin today's youngest self-made billionaire. And when it comes to self-driving cars, youth is definitely an advantage -- Austin told me we're still years if not decades away from fully self-driving cars, and there's a lot of work to be done to make them safe, effective, and ubiquitous. That work is racing ahead -- Luminar has deals with Volvo, Audi, Toyota, and others -- but building a complete self-driving car is still a long-term project. This transcript has been lightly edited for clarity. I'm very excited to talk to you. You are, as far as the last thing I read, the youngest self-made billionaire in America, your company just went public in a SPAC [special purpose acquisitions company]. And come Pi Day, 26. You were born on Pi Day? So, Luminar, it's a company that makes LIDAR sensors. You have a number of deals to supply LIDAR sensors to major automakers. I want to talk about all of that. One thing that I always get frustrated by in origin stories is no one ever really talks about act two. In 2012 you were at Stanford, you had this idea to do LIDAR sensors. I want to talk about act two for a little bit. Just that middle part of going from "I've got a great idea," to "This company is actually up and running and functional." So give me a sense of, at the beginning you were a student at Stanford, you got a Thiel Fellowship from Peter Thiel. What was the next step? Did you sit down and build a LIDAR sensor?
I want to make one point, that this is on the record. But we're going to have a great time discussing "Robots and the Future of Jobs: The Economic Impact of Artificial Intelligence." So I'll start with simple introductions, and then we'll lay out some definitions about the kinds of terms that will be involved in this conversation. So my name is John Paul Farmer. Very happy to be here with three experts on the topic. Next to me is Dr. James Manyika, who is a recovering roboticist. And his day job is at McKinsey, at the McKinsey Global Institute, where he's been focusing on the future of jobs and the future of work in this new era. In the middle, we have Dr. Daniela Rus. Dr. Rus is a professor and roboticist at MIT, and she is also the director of the Computer Science and Artificial Intelligence Lab there. And at the end, we have Edwin van Bommel. Edwin is formerly of McKinsey, but now he's the chief cognitive officer at IPsoft. So, with that, let me lay out some definitions that are going to be important, I think, to following this conversation. You may have read in Foreign Affairs and elsewhere about this fourth industrial revolution, the changes that are happening in our society today and many more that will be coming down the pike. So as we--as we talk about these things, one, we should all be on the same page in terms of what artificial intelligence is. What do we mean when we say AI? And the definition that many accept is it's the development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and even translation between languages. AI is sometimes humorously referred to as whatever computers can't do today. Machine learning is another term you're going to hear a lot, sometimes thought of as a rebranding of AI, of artificial intelligence. But there's one key difference, which is that it takes a much more probabilistic approach as opposed to deterministic. So it looks at not just yes or no; it looks at a 30 percent chance of X, a 10 percent chance of Y, and so on. Big data, a term that I think we've all heard. Data is the raw material. Some people call it the new oil for this new era.