Google DeepMind has released SIMA 2 to test how far generalist embodied agents can go inside complex 3D game worlds. SIMA’s (Scalable Instructable Multiworld Agent) new version upgrades the original instruction follower into a Gemini driven system that reasons about goals, explains its plans, and improves from self play in many different environments. From…

How do you build a single model that can learn physical skills from chaotic real world robot data without relying on simulation? Generalist AI has unveiled GEN-θ, a family of embodied foundation models trained directly on high fidelity raw physical interaction data instead of internet video or simulation. The system is built to establish scaling…

Can a single AI stack plan like a researcher, reason over scenes, and transfer motions across different robots—without retraining from scratch? Google DeepMind’s Gemini Robotics 1.5 says yes, by splitting embodied intelligence into two models: Gemini Robotics-ER 1.5 for high-level embodied reasoning (spatial understanding, planning, progress/success estimation, tool-use) and Gemini Robotics 1.5 for low-level visuomotor…

What Do We Mean by “Physical AI”? Artificial intelligence in robotics is not just a matter of clever algorithms. Robots operate in the physical world, and their intelligence emerges from the co-design of body and brain. Physical AI describes this integration, where materials, actuation, sensing, and computation shape how learning policies function. The term was…

In this tutorial, we walk step by step through using Hugging Face’s LeRobot library to train and evaluate a behavior-cloning policy on the PushT dataset. We begin by setting up the environment in Google Colab, installing the required dependencies, and loading the dataset through LeRobot’s unified API. We then design a compact visuomotor policy that…

Robotics and artificial intelligence are converging at an unprecedented pace, driving breakthroughs in automation, perception, and human-machine collaboration. Staying current with these advancements requires following specialized sources that deliver technical depth, research updates, and industry insights. The following list highlights 12 of the most authoritative robotics and AI-focused blogs and websites to track in 2025.…

Last week, the NVIDIA robotics team released Jetson Thor that includes Jetson AGX Thor Developer Kit and the Jetson T5000 module, marking a significant milestone for real‑world AI robotics development. Engineered as a supercomputer for physical AI, Jetson Thor brings generative reasoning and multimodal sensor processing to power inference and decision-making at the edge. Architectural…

Advancements in artificial intelligence are rapidly closing the gap between digital reasoning and real-world interaction. At the forefront of this progress is embodied AI—the field focused on enabling robots to perceive, reason, and act effectively in physical environments. As industries look to automate complex spatial and temporal tasks—from household assistance to logistics—having AI systems that…

Embodied AI agents that can perceive, think, and act in the real world mark a key step toward the future of robotics. A central challenge is building scalable, reliable robotic manipulation, the skill of deliberately interacting with and controlling objects through selective contact. While progress spans analytic methods, model-based approaches, and large-scale data-driven learning, most…

Amazon has reached a remarkable milestone by deploying its one-millionth robot across global fulfillment and sortation centers, solidifying its position as the world’s largest operator of industrial mobile robotics. This achievement coincides with the launch of DeepFleet, a groundbreaking suite of foundation models designed to enhance coordination among vast fleets of mobile robots. Trained on…