Free Machines of Loving Grace by John Markoff Page B

start-ups. Now the AI world was rebounding. Progress in AI, which had been relatively stagnant for its first three decades, finally took off during the 1990s because statistical techniques made classification and decision-making practical. AI experiments hadn’t yet seen great results because the computers of the era were still relatively underpowered for the data at hand. The new ideas, however, were in the air.
    As a graduate student Shashua would focus on a promising approach to visually recognizing objects based on imaging them from multiple views to capture their geometry. The approach was derived from the world of computer graphics, where Martin Newell had pioneered a new modeling approach as a graduate student at the University of Utah—which was where much of computer graphics was invented during the 1970s. A real Melitta teapot found in his kitchen inspired Newell’s approach. One day, as he was discussing the challenges of modeling objects with his wife over tea, she suggested that he model that teapot, which thereafter became an iconic image in the early days of computer graphics research.
    At MIT, Shashua studied under computer vision scientists Tommy Poggio and Eric Grimson. Poggio was a scientist who stood between the worlds of computing and neuroscience and Grimson was a computer scientist who would later become MIT’s chancellor. At the time there seemed to be a straight path from capturing shapes to recognizing them, but programming the recognition software would actually prove daunting. Even today the holy grail of “scene understanding”—for example, not only identifying a figure as a woman but also identifying what she might be doing—is still largely beyond reach, and significant progress has been made only in niche industries. For example, many cars can now identify pedestrians or bicyclists in time to automatically slow before a collision.
    Shashua would become one of the masters in pragmatically carving out those niches. In an academic world where brain scientists debated computational scientists, he would ally himself with a group who took the position that “just because airplanes don’t flap their wings, it doesn’t mean they can’t fly.” After graduate school he moved back to Israel. He had already founded a successful company, Cognitens, using vision modeling to create incredibly accurate three-dimensional models of parts for industrial applications. The images, accurate to hair-thin tolerances, gave manufacturers ranging from automotive to aerospace the ability to create digital models of existing parts, enabling checking their fit and finish. The company was quickly sold.
    Looking around for another project, Shashua heard from a former automotive industry customer about an automaker searching for stereovision technology for computer-assisted driving. They knew about Shashua’s work in multiple-view geometry and asked if he had ideas for stereovision. He responded, “Well, that’s fine but you don’t need a stereo system, you can do it with a single camera.” Humans can tell distances with one eye shut under some circumstances, he pointed out.
    The entrepreneurial Shashua persuaded General Motors to invest $200,000 to develop demonstration software. He immediately called a businessman friend, Ziv Aviram, and proposed that they start a new company. “There is an opportunity,” he told his friend. “This is going to be a huge field and everybody is thinking about it in the wrong way and we already have a customer, somebody who is willing to pay money.” They called the new company Mobileye and Shashua wrote software for the demonstration on a desktop computer, soon showing one-camera machine vision that seemed like science fiction to the automakers at that time.
    Six months after starting the project, Shashua heard from a large auto industry supplier that General Motors was about to offer a competitive bid for a way to warn drivers that the vehicle was straying out of its