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Today we're speaking with Dr. Amarjot Singh, Founder & CEO of Skylark Labs, about physical AI — what changes when a model leaves the server and has to perceive, decide and act inside a machine that moves through the real world.
Today we're speaking with Dr. Amarjot Singh, Founder & CEO of Skylark Labs, about physical AI — what changes when a model leaves the server and has to perceive, decide and act inside a machine that moves through the real world.
Dr. Singh earned his PhD in artificial intelligence and deep learning from the University of Cambridge, and has worked as a research fellow at Stanford University and on DARPA research focused on artificial general intelligence. His work spans computer vision, self-learning AI, drones, humanoid robotics and autonomous systems, with more than 50 international journal and conference publications. At Skylark Labs he is focused on taking that research into real-world systems, including AI-powered drones, robotic platforms and technologies designed for defense and other mission-critical environments.
In this conversation: why a bad prediction from a robot is a different problem than a hallucination from a chatbot, what an on-device AI stack actually looks like from sensors to action, learning from a single exposure at the edge and deliberately forgetting the rest, how one machine shares validated knowledge with the rest of a fleet, why hands and manipulation remain the hardest problem in robotics, what "reliable enough" means when failure has physical consequences, and where this all lands in ten years.
Learn more at https://skylarklabs.ai/
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