I think the most under-hyped area of new technology right now is autonomous vehicles, particularly self-driving cars.
In the 20th century, *non*-autonomous, human-driven cars not only gave people all over the world freedom and independence in a completely new way, but catalyzed massive economic growth and development — leading to the incredible rise of modern cities, suburbs, hotels, restaurants, retail shopping, theme parks, tourism… and a thousand other things that make our lives better and that we all now take for granted.
In the 21st century, I expect self-driving cars to not only lead to another quantum leap in personal freedom and independence for billions of people — and not only create an even bigger wave of economic growth and development due to opening up so much more geography for people to live, work, and travel — but also to reduce, and quite possibly eliminate, the enormous carnage associated with human-driven cars. Cars driven by people kill over a million people a year worldwide, and with modern autonomy technology, we really ought to be able to end that.
However, in order to realize this dream, it is critically important that self-driving cars be able to anticipate and react to every conceivable drive-time scenario imaginable: in every kind of weather, every type of road system, every variable in environmental behavior playing out around them.
And to do that, we must harness technology to train self-driving cars in the virtual world, through millions of hours of simulated driving, so that they are ready to perform as perfectly as possible in the real world.
For that reason, I’m thrilled that we have funded the most impressive team in the world to implement the best possible system for autonomous vehicle simulation, Applied Intuition. Qasar Younis, Peter Ludwig, and their colleagues blend deep experience across both the auto industry and technology — Detroit and Silicon Valley — required to nail this problem. And I’m really excited to personally be on their board and to work with them to fulfill the autonomy dream.
