AWS Physical AI Blog

A different recipe for training robot world models: compose pre-trained AI modules with classical computer vision to extract scene semantics from ordinary monocular video — no domain data, no synthetic frames. Introduction Today’s recipe for training robot AI looks the same almost everywhere: feed a giant neural network billions of pixels paired with text instructions […]

Introduction Manufacturers need automation that adapts to changing products without costly rework. At Hannover Messe 2026, SoftServe and AWS demonstrated a simulation-first approach to flexible robotic manufacturing, powered by AWS cloud services for AI orchestration, IoT communication, and quality inspection that ran continuously for five days with a near-100 percent pick success rate during live […]

The authors would also like to thank Charlie Chang, Amit Kulkarni, Paul Amadeo, Alla Simoneau, Howie Tan for their contributions in making this initiative possible. Introduction Certis is a leading integrated operations service provider, with over 25,000 employees globally and one of the largest Auxiliary Police Forces in Singapore. As part of its broader autonomous […]

Introduction Physical AI development today faces a critical bottleneck. Engineering teams spend disproportionate hours on infrastructure setup, environment configuration, and dependency management—time that could be spent building intelligent robots. The iterative cycle of environment setup, data collection, policy training, and simulation validation consumes weeks of engineering effort before a single real-world test can occur. Even […]

Introduction A customer walks up to an autonomous barista robot at an airport terminal and orders a flat white coffee. The robot has never been explicitly programmed to make one. It knows how to pull espresso shots, steam milk, and control pour volumes, however “flat white” isn’t in its onboard recipe library. Within 300 milliseconds, […]

Self-Driving Labs® are no longer a vision Developing a new drug takes an average of 10-15 years and costs over $2 billion. For patients waiting on life-saving treatments, every month of R&D delay matters. The bottleneck isn’t a lack of scientific talent, it’s the sheer scale of experimentation required. A single drug optimization campaign might […]

Introduction Physical AI systems – robots that perceive, reason, and act in the real world, are advancing rapidly. The Sim-to-Real pipeline is at the heart of this progress. However, building models that work reliably outside the lab remains one of the hardest problems in the field. The gap between what works in simulation and what […]

Introduction Organizations across urban planning, emergency management, and defense need to model how populations move and behave in spatial environments. Whether simulating an evacuation, modeling resource competition, or analyzing urban migration patterns, understanding human behavior at scale is critical. Traditional agent-based models rely on hardcoded rules that produce predictable, unrealistic behavior. Generative AI changes this […]

A practical guide to spatial data management for inspection workflows on AWS Introduction Across industries, inspection teams are under increasing pressure to document asset conditions accurately, support compliance requirements, and maintain records that remain meaningful months or even years after data is captured. In practice, many inspection programs generate large volumes of imagery and observations […]

From Hospital Walls to the Home — A New Era of Intelligent Care Healthcare has long been defined by a fundamental constraint: the best care requires physical presence — patients travel to hospitals, clinicians are bound to facilities, and monitoring depends on proximity. But what if AWS-powered intelligence could follow the patient — anywhere, anytime? That is […]