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ASPIRE Arrives on Hugging Face: Autonomous Skill Discovery System Streamlines Robot Programming
Hugging Face (arXiv paper page) USA Overview A preprint on Hugging Face introduces ASPIRE (Agentic Skill Programming through Iterative Robot Exploration), a continuous learning system that autonomously develops and refines robot control ... -
Labimus: First Benchmark for Dexterous Humanoid Robot Manipulation in Chemical Laboratories Debuts on arXiv
arXiv USA Overview A new preprint on arXiv introduces 'Labimus,' the first benchmark designed to evaluate dexterous manipulation by humanoid robots in chemical laboratories. Labimus aims to bridge the critical gap between current automat... -
U.S. DOE Propels AI Innovation Ecosystem, Empowering Research with Autonomous Laboratories
Department of Energy USA Overview The U.S. Department of Energy (DOE) is fostering a world-leading AI innovation ecosystem by integrating AI across high-performance computing, environmental modeling, and materials research. This includes... -
AI Workflow Unites Foundation Models and Bayesian Optimization for Cost-Efficient Materials Discovery
arXiv USA Overview A new preprint introduces a novel Bayesian materials design workflow that integrates surrogate-gated generation with foundation model embeddings. This approach, leveraging pre-trained ORB embeddings and Gaussian proces... -
DOE Unleashes AI-Powered Autonomous Labs to Revolutionize Energy and Biotech Discovery
Department of Energy USA Overview The U.S. Department of Energy (DOE) is spearheading a transformative initiative to accelerate scientific discovery in critical sectors like energy, computing, and biotechnology through advanced AI-driven... -
Tohoku University Launches AI-Driven ‘DigCat 4.0’ Platform to Revolutionize Catalyst Discovery
東北大学 Japan Overview Tohoku University researchers have unveiled 'DigCat 4.0,' an AI-powered digital catalysis platform designed to significantly accelerate catalyst discovery and development. By integrating experimental data, theoret... -
Accelerating Innovation: Lawrence Berkeley’s A-Lab Leverages AI for Self-Driving Materials Discovery
TheSequence USA Overview Self-driving labs are fundamentally transforming materials science by autonomously executing experiments and learning from both successes and failures. Lawrence Berkeley National Laboratory's A-Lab exemplifies th... -
AI-Driven Design Transforms Metal-Organic Materials to Dynamic Networks, Powering Self-Driving Labs for Accelerated Discovery
MDPI International Overview This paper proposes extending AI-driven design of metal-organic materials (MOMs) beyond traditional crystalline MOFs to dynamic coordination networks, such as metal-polyphenol networks (MPNs). It integrates pr... -
Lisa Pedrosa Explains the Rise of ‘Self-Driving Labs’ Integrating AI & Robotics, Transforming Scientific Discovery
Lisa Pedrosa USA Overview Lisa Pedrosa's article details how 'self-driving labs,' integrating AI, robotics, and human expertise, are fundamentally transforming scientific discovery. These labs autonomously design, execute, and analyze ex... -
CVC Analyzes 8 Leading AI Material Development Companies: Investment Strategies and Public Market Proxies Explored
note Japan Overview From a Corporate Venture Capital (CVC) perspective, eight key AI material development companies—Cusp AI, DeepMind, Microsoft, Orbital, Matlantis, Citrine Informatics, Aionics, and Kebotix—have been analyzed. This arti...
