More importantly Pittsburgh boasts the robotics department at Carnegie-Mellon University, recognized as the leading academic institution in the field.
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The transportation firm has about 500 employees in the city’s tech Strip district and plans to start testing as many as 100 Volvo sport utility vehicles on the city’s streets. Many of Uber’s employees were hired directly from Carnegie-Mellon’s computer labs and the state’s approach to the technology – called greenlight governing – effectively encouraged investment in the field. Uber estimates its investment will reach $1bn over the next few years.
“It’s not just about self-driving cars,” says Law. “It’s about the future of urban mobility. How do you create smarter and more efficient cities.” Pittsburgh is ideal, he says, “because if you are going to design a car that needs to navigate some of the most complex road networks and systems, you’re not going to get a bigger challenge than here. It’s old, it was planned poorly, it’s built around hills and valleys, and the roads are windy and steep. If it works in Pittsburgh, it can work anywhere.”
The firm is not alone: General Motors, Google – which has centered its engineering facilities here and employs 600 – and Intel have also come to Pittsburgh. While Apple, which employs 500 here, has not stated the reason for its interest, it is known to have already developed a prototype vehicle. But the city’s easy-going regulatory approach and an intelligent workforce is not the only reason Pittsburgh is becoming ground zero for auto-automation, widely regarded as one of the largest untapped economies.
Google’s Mike Capsambelis explains the company’s explicit interest in Pittsburgh is machine learning, a sub-field of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In other words, learning without needing to be explicitly programmed.
