Introducing AWS Physical AI Toolchain

End-to-End solution for Training and Deploying Physical AI Policies on AWS at Scale Physical AI is artificial intelligence that operates in the real world through robots, autonomous vehicles, and smart factories. According to the Capgemini Research Institute, 79% of organizations are already engaging with Physical AI, and 60% of executives believe that physical AI will […]

3D Gaussian Splatting in practice: Industry use cases

Gaussian Splatting is dramatically lowering the cost and complexity of photorealistic 3D, making once impractical use cases like near real time capture, robotics, and simulation viable across media, construction, manufacturing, and real estate. AWS Physical AI | Blog #2 in the 3D Gaussian Splatting Series From Research Breakthrough to Business Advantage When we introduced 3D […]

Isaac Lab on AWS: From Simulation to Registered Policy

Introduction: The missing layer in Physical AI on AWS Physical AI systems, those that perceive, reason, and act in the physical world, are moving fast from research into production deployments. Training policies in GPU-accelerated simulation compress months of real-world experience into hours of computing, without the cost, time, or safety risks of physical experimentation. A […]

NVIDIA Cosmos 3 on AWS: Omnimodal World Models for Physical AI

Introduction In our previous blog, we demonstrated how NVIDIA Cosmos world foundation models on AWS address the data scarcity problem in physical AI: the challenge of training robust perception, prediction, and control models when real-world robot and sensor data is expensive, unsafe, or impractical to collect at scale. We introduced two production-ready architectures: Cosmos NIM […]

Fine-Tuning π0 (Pi-Zero) for robotic manipulation on Amazon SageMaker HyperPod EKS

Introduction This post demonstrates how to fine-tune π0 (Pi-Zero), a 3-billion parameter flow matching Vision-Language-Action model from Physical Intelligence, on robot manipulation datasets using Amazon SageMaker HyperPod with Amazon Elastic Kubernetes Service (Amazon EKS) orchestration. Two standard robotics benchmarks provide the training data: DROID for real-world manipulation and LIBERO-10 for simulated tabletop tasks, with a […]

How WIRobotics is teaching humanoid robots to use human tools with AWS and NVIDIA

The next frontier of automation is built for human environments Industrial automation has transformed work that is predictable and repeatable. Robots can perform the same motion thousands of times with remarkable consistency, which makes them well suited to structured production environments. But much of the work that keeps industrial operations running is not always orderly. […]

How Physna and AWS use geometric intelligence to bridge engineering design and procurement

Introduction Geometric intelligence visualization showing 3D CAD wireframe parts connected by AI matching arcs Every original equipment manufacturer faces the same invisible cost. An engineer designs a component, unaware that a functionally identical part already sits in a warehouse at another facility, cataloged under a different name in a different system. A procurement team launches […]

Build L1–4 Industrial Digital Twins with OpenUSD and SDMA on AWS

Introduction Digital twins shift manufacturing teams from reactive maintenance to predictive operations. A production-grade twin goes beyond static 3D. It ingests live data, predicts failures, and self-corrects as equipment ages. In this post, you’ll learn how to architect a multi-level digital twin on AWS using Universal Scene Description (OpenUSD) for scene composition and Spatial Data […]