Category: Robotics

For robots to see, understand, and physically handle objects in human-centered work environments, they need to learn from real operational settings, not just controlled lab demonstrations. RLWRLD, a Physical AI company founded in 2024, is building RLDX, a robotics foundation model designed to train on real-world industrial data and enable robots to perform dexterous manipulation […]

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 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, […]

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 […]

The open-source Visual Asset Management System (VAMS) now supports GPU-accelerated reinforcement learning (RL) for robotic assets through integration with NVIDIA Isaac Lab. This pipeline enables teams to train and evaluate RL policies directly from their asset management workflow, leveraging AWS Batch for scalable GPU compute. Isaac Lab for Physical AI and Robotics Development Figure 1: […]

Introduction The world is moving towards an Autonomous Economy which represents a transformative economic model where AI, edge computing, robotics, spatial intelligence, and simulation technologies work together to enable systems to operate autonomously with minimal human intervention. Physical AI represents the convergence of these technologies enabling computers to sense, understand, predict, and act with the […]

Note: This blog was updated on May 6, 2026 We have reached a milestone in technical evolution: the ability to use advanced AI models to influence not only the digital world but also the physical one. We are moving from AI that generates text to AI that moves atoms — augmenting our daily lives by […]