This places additional burdens on the algorithms. “They need something that’s much more specific for the problem they’re trying to solve, such as near real-time vision, while probably mixing that with other sensors like LiDAR and radar,” says Kurt Shuler, vice president of marketing at Arteris IP. “It’s not as general-purpose as something that you’d see from the more academic benchmark. So those guys are having to innovate a lot more than the traditional AI algorithms that you read about.”