“Autonomous Driving AI Workloads: Technology Trends and Optimization Strategies,” a Presentation from Qualcomm

Ahmed Sadek, Senior Director of Engineering at Qualcomm, presents the “Autonomous Driving AI Workloads: Technology Trends and Optimization Strategies” tutorial at the May 2022 Embedded Vision Summit.

Enabling safe, comfortable and affordable autonomous driving requires solving some of the most demanding and challenging technological problems. From centimeter-level localization to multimodal sensor perception, sensor fusion, behavior prediction, maneuver planning and trajectory planning and control, each one of these functions introduces its own unique challenges that must be solved, verified, tested and deployed on the road.

In this talk, Sadek reviews recent trends in AI workloads for autonomous driving as well as promising future directions. He covers AI workloads in camera, radar and lidar perception, AI workloads in environmental modeling, behavior prediction and drive policy. To enable optimized network performance at the edge, quantization and neural architecture optimization are typically performed either during training or post-training. Sadek also covers the importance of hardware-aware quantization and network architecture optimization, and introduces the innovation done by Qualcomm in these areas.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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