Tag
Physical AI
What changes as AI enters robotics, mobility, industry and physical environments.
06essays
01Why Robotics Is Hard: The Real World Has No API ContractRobotics is difficult not simply because models need to improve, but because perception errors, contact physics, latency, mechanical wear and human behaviour accumulate into uncertainty that the system must manage safely.Sep 6, 202612 min read02When Devices Become AI-Powered, Product Management Becomes Lifecycle ManagementAI-powered devices force product teams to manage hardware and model dependencies, capability limits, power budgets, OTA failure paths, data flows, cybersecurity and end-of-life support.Sep 3, 202614 min read03AI Cameras Need to Understand Events, Not Just Detect ObjectsThe next AI camera advantage is not simply detecting more objects. It is turning continuous video into a small number of trustworthy events through tracking, rules, edge filtering, VLM review and interoperable metadata.Aug 28, 202614 min read04Why Edge AI Matters Again: The Real Shift Is Where Inference RunsEdge AI is not replacing cloud AI. As AI moves into devices, cameras, robots and long-running agents, latency, connectivity, privacy, power and cost turn inference placement into a product architecture decision.Aug 22, 202613 min read05When Computer Vision Starts Understanding Events, Not Just ObjectsComputer vision is moving beyond object detection toward streaming video, event understanding and distributed edge inference. The harder question is who defines what counts as an event and what the system is allowed to do next.Aug 19, 202612 min read06What Is Physical AI? Why the Next Wave of AI Will Leave the ScreenGenerative AI transformed how we create and process information. Physical AI goes further: machines begin to perceive, reason and act in the real world, where latency, safety, hardware and failure suddenly matter much more.Aug 15, 202610 min read
← Back to all essays