AI Briefing#robotics
The latest AI and developer news about #robotics, with the original source and a short summary.
The latest AI and developer news about #robotics, with the original source and a short summary.
NVIDIA, Pollen Robotics, and Hugging Face introduce a workflow to train walking policies for the Microduck robot in Isaac Lab 3.0 and deploy them via ONNX.
The library provides pre-configured OpenUSD models with physics and thermal metadata to accelerate digital twin construction and robotics training.
The portfolio includes Nemotron 3.5, Kumo for structured data, Cosmos 3.5 for robotics, and Ising for quantum computing, enabling customization with local data.
The program launches in Minneapolis, Chicago, and Miami to record technicians performing plumbing, electrical, and HVAC work.
Held at COEX on November 9-10, the event offers RTX Spark experiences and free opportunities to take technical certification exams.
The new Pi API allows developers to upload data and fine-tune π0 and π0.5 models on managed infrastructure, enabling hosted inference for diverse robotic applications.
Architecture and performance data released for serving 79 model rows, from text to robot actions, within a single runtime
Developers used GPT-6 Astra to generate code for humanoid robot simulators, autonomous driving tests, and digital twins using NVIDIA Omniverse libraries.
The dataset features over 1 million unique tasks collected in 8 weeks, significantly outperforming existing public UMI benchmarks in diversity and scale.
Runway has announced Praxis-1, an open-weight world action model for robotics that leverages large-scale video pretraining to improve policy generalization, with a public release planned for the coming months.
A new study by Anthropic researchers finds that while robots can technically perform 74% of physical work, high costs mean only 0.3% of tasks are currently economically viable for automation.
Presents an infrastructure strategy connecting simulation to edge deployment using SageMaker and IoT Greengrass
Stanford researchers propose EXPO-FT, an algorithm for universal post-training in robotics that achieves 100% success rates on physical tasks by using a lightweight editing policy to stabilize reinforcement learning.
It presents migration procedures and performance tuning tips for scaling the SO-101 robot arm to up to 2,048 parallel GPU environments.
MS unveiled Physical AI Toolchain features that offload robotics inference to the edge or cloud, extending battery life by up to 160% and improving performance.
NVIDIA has released Isaac ROS 5.0, featuring enhanced AI agent workflows and GPU acceleration capabilities.
NVIDIA has unveiled 'Halos', a full-stack safety system spanning hardware to verification for the large-scale deployment of autonomous vehicles and robots.
Figure released Helix 2.5, which can autonomously perform whole-body tasks in 30 homes it has never seen before.
Apple released REVERSAL-BENCH to measure irreversibility issues in reset-free reinforcement learning, identifying a phenomenon where learning halts as irreversibility increases.
Odyssey has released Odyssey-3, a general-purpose physical intelligence model designed to control robots, autonomous vehicles, and games.
Researchers from the National University of Singapore and others released OpenWAM, a modular stack for comparing design variables of robot World-Action Models.
Skild AI has released 'S1', a foundation model that leverages NVIDIA infrastructure to enable robots to perform new long-horizon tasks using only a single video.
Arm unveiled the Total Design initiative and a robot capability standardization framework to accelerate physical AI development with over 80 companies.
Robotics has not yet reached a true intelligence stage due to data scarcity and generalization failures, making data collection in narrow domains essential.