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RoboBrain 2.0: The Next-Generation Vision-Language Model Unifying Embodied AI for Advanced Robotics

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…

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NVIDIA AI Team Introduces Jetson Thor: The Ultimate Platform for Physical AI and Next-Gen Robotics

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…

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Genie Envisioner: A Unified Video-Generative Platform for Scalable, Instruction-Driven Robotic Manipulation

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…

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Meet DeepFleet: Amazon’s New AI Models Suite that can Predict Future Traffic Patterns for Fleets of Mobile Robots

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…

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NVIDIA AI Introduces End-to-End AI Stack, Cosmos Physical AI Models and New Omniverse Libraries for Advanced Robotics

Nvidia made major waves at SIGGRAPH 2025 by unveiling a suite of new Cosmos world models, robust simulation libraries, and cutting-edge infrastructure—all designed to accelerate the next era of physical AI for robotics, autonomous vehicles, and industrial applications. Let’s break down the technological details, what this means for developers, and why it matters to the…

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NVIDIA AI Releases GraspGen: A Diffusion-Based Framework for 6-DOF Grasping in Robotics

Robotic grasping is a cornerstone task for automation and manipulation, critical in domains spanning from industrial picking to service and humanoid robotics. Despite decades of research, achieving robust, general-purpose 6-degree-of-freedom (6-DOF) grasping remains a challenging open problem. Recently, NVIDIA unveiled GraspGen, a novel diffusion-based grasp generation framework that promises to bring state-of-the-art (SOTA) performance with unprecedented…

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URBAN-SIM: Advancing Autonomous Micromobility with Scalable Urban Simulation

Micromobility solutions—such as delivery robots, mobility scooters, and electric wheelchairs—are rapidly transforming short-distance urban travel. Despite their growing popularity as flexible, eco-friendly transport alternatives, most micromobility devices still rely heavily on human control. This dependence limits operational efficiency and raises safety concerns, especially in complex, crowded city environments filled with dynamic obstacles like pedestrians and…

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UC San Diego Researchers Introduced Dex1B: A Billion-Scale Dataset for Dexterous Hand Manipulation in Robotics

Challenges in Dexterous Hand Manipulation Data Collection Creating large-scale data for dexterous hand manipulation remains a major challenge in robotics. Although hands offer greater flexibility and richer manipulation potential than simpler tools, such as grippers, their complexity makes them difficult to control effectively. Many in the field have questioned whether dexterous hands are worth the…

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Meta AI Releases V-JEPA 2: Open-Source Self-Supervised World Models for Understanding, Prediction, and Planning

Meta AI has introduced V-JEPA 2, a scalable open-source world model designed to learn from video at internet scale and enable robust visual understanding, future state prediction, and zero-shot planning. Building upon the joint-embedding predictive architecture (JEPA), V-JEPA 2 demonstrates how self-supervised learning from passive internet video, combined with minimal robot interaction data, can yield…

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NVIDIA AI Releases HOVER: A Breakthrough AI for Versatile Humanoid Control in Robotics

The future of robotics has advanced significantly. For many years, there have been expectations of human-like robots that can navigate our environments, perform complex tasks, and work alongside humans. Examples include robots conducting precise surgical procedures, building intricate structures, assisting in disaster response, and cooperating efficiently with humans in various settings such as factories, offices,…

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