Fall 2016
Hands-free
Sanford Russell ‘82 discusses “Deep Learning” and the near future of driverless cars
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t’s a sunny day in February, NVIDIA’s BB8 represents a giant leap forward from autonomous car (internally called today’s hi-tech cars that automatically stop for BB8) with its NVIDIA DRIVE™ PX 2 pedestrians or parallel park on their own. “[That] supercomputer, is on a test drive. It technology is fairly simple,” said Sanford Russell flattens one cone after another on a private (‘81), Senior Director, Autonomous Driving course then veers off the road on a side Ecosystem, NVIDIA. “[It requires] radar to aid in street, nearly taking out a trash can, and braking when a car or person is in front and... side-swipes the branches of snow-covered camera to see well-marked lane boundaries.” trees. In terms of autonomy, the test is Sanford Russell with UMassD engineering students However, a truly autonomous car requires 360actually just a learning drive, like a child degree awareness, integrating data from radar, learning to walk—the human operator must constantly take the lidar, multiple cameras, ultrasonic sensors, and GPS, and the ability to wheel to help it learn. However, one month later, the car is back, and process all the information in real-time. How, then, have we jumped this time it maneuvers the cones with ease then confidently cruises so quickly from assisted braking to Autonomous research vehicles a busy highway, maintaining its lane. BB8 even masters unpaved with Drive PX2? roads, all while the human operator remains hands-free. The drastic “What has changed,” Sanford said, “is deep learning.” A branch improvement isn’t due to better programming or hardware, it’s the of Artificial Intelligence (AI), deep learning attempts to mimic the result of experience. The previous month, it logged 3,000 training human brain’s ability to learn through training then make informed miles and learned to drive better. decisions. “Deep learning relies on training a computer-based neural continued on page 2
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