Talking Autonomy: Physics-Based Artificial Intelligence скачать в хорошем качестве

Talking Autonomy: Physics-Based Artificial Intelligence

Ghost Autonomy co-founder and CTO Volkmar Uhlig unpacks Ghost's unique approach to physics-based AI. Most AI algorithms for computer vision rely upon image recognition as their first step. They must identify each object on the road and then use that classification of its type and size to help compute distance and motion and make assumptions about its probable behavior. But the challenge of recognizing anything that might be on the road, every time is infinite. Ghost has instead developed a physics-based approach to detect obstacles and understand roads universally that doesn't require explicit object identification. In this video, Volkmar explains the physics-based approach that underlies Ghost's AI algorithms and the benefits it offers for safety, training, and execution efficiency. Thank you for watching Talking Autonomy, a series of short tech talks that explain the key elements of our work at Ghost. Subscribe and stay tuned for new episodes as we continue exploring the core technologies behind the Ghost Autonomy Engine and sharing insights from the founders, engineers, designers, mathematicians, and even the policy-makers who are responsible for bringing Ghost’s self-driving technology to the roads. Connect with Ghost and learn more: Ghost Autonomy Engine on the web: https://www.ghostautonomy.com/platform KineticFlow vision neural network: https://www.ghostautonomy.com/kinetic... Follow Ghost on Twitter:   / ghostautonomy   Follow Ghost on LinkedIn:   / ghostautonomy   #selfdriving #AI #autonomous #GhostAutonomy #computervision