TRIAL AND ERROR. Artificial intelligence startup Wayve believes it’s found a better way to train autonomous vehicles (AVs) than the existing methods of sophisticated hardware and detailed 3D maps.

On Monday, the company released a video in which a modified Renault Twizy (a two-seated electric vehicle) learns to autonomously navigate a road. It does so through reinforcement learning, a type of machine learning in which a system earns a “reward” for desirable behavior and a “penalty” for undesirable behavior.

They detail their experiment in a paper published on arXiv. THE PROBLEM WITH MAPS. Most in-development AV systems rely on detailed 3D maps to navigate.

Companies across the globe are currently racing to create these maps, using sophisticated sensors and cameras to detail city streets and highways alike. AVs, in turn, require their own complex systems of cameras and sensors to then navigate these maps.

Unfortunately, 3D maps are labor-intensive and require frequent updates to account for things like construction. Companies that create 3D maps also tend to focus on highly trafficked roads first, leaving rural areas behind. Read more from…

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