June 2026– date –
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ResearchGate Paper: Unconstrained MLIPs Achieve Superior Accuracy and Speed with Large Datasets, Enhancing Static Simulations
ResearchGate (Machine Learning: Science and Technology) Unknown Overview A paper published via ResearchGate demonstrates that unconstrained Machine Learning Interatomic Potentials (MLIPs), when trained on sufficiently large datasets, can... -
AWS and QuEra to Deploy Megaquop-Scale ‘Libra’ on Amazon Braket by 2028, Enabling Fault-Tolerant Quantum Computing
AWS News Blog USA Overview AWS and QuEra have strengthened their strategic collaboration to bring fault-tolerant quantum computing to Amazon Braket. As part of this alliance, QuEra's Megaquop-scale device, 'Libra' (equivalent to approxim... -
SandboxAQ Secures $500M from US Department of Commerce Under CHIPS Act to Resolve Semiconductor Materials Supply Chain Challenges
Semiecosystem USA Overview SandboxAQ, an AI-driven materials discovery platform, has received $500 million in government funding from the U.S. Department of Commerce under the CHIPS and Science Act. This funding will enable the company t... -
Radical AI’s Self-Driving Lab Generates 1,200 Alloys in Six Months, Accelerating Materials Discovery
Latent.Space USA Overview Joseph Krause of Radical AI asserts that 'self-driving labs' are indispensable for materials discovery, surpassing the limitations of 'one-shot' AI. His company's autonomous lab, utilizing a closed-loop system c... -
RSC Paper Proposes ‘Digital Materials Ecosystem’ for Autonomous Discovery, Integrating Databases and AI Agents
RSC Publishing UK Overview A paper from RSC Publishing proposes a 'Digital Materials Ecosystem,' a new materials research paradigm integrating data, theory, and automation. This ecosystem combines reliable material databases, physical fr... -
Hugging Face Showcases LLM Application Preprints in Scientific Discovery, Emphasizing Autonomous Agents in Materials, Biology, and Chemistry
Hugging Face USA Overview Hugging Face's Daily Papers featured several arXiv preprints on the application of Large Language Models (LLMs) in scientific discovery. These papers focus on benchmarking LLMs across biology, chemistry, materia... -
Jeff Bezos Backs AI Materials Science Startup CuspAI with $400M Investment, Valuing Company at $2.6B to Accelerate Carbon Capture and Semiconductor Material Development
TechCrunch UK Overview Jeff Bezos has led a $400 million funding round for UK-based AI materials science startup CuspAI, valuing the company at an estimated $2.6 billion. CuspAI aims to dramatically accelerate materials discovery from ye... -
Unlocking AI’s ‘Why’: Visualizing Prediction Rationale for Rapid Materials Discovery
不明 Japan Overview Researchers from Science Tokyo and Tohoku University have developed a novel interpretable AI (XAI) method that demystifies how AI models predict material properties. This breakthrough technique visualizes the intricat... -
arXiv Paper: Computational Materials Science Evolves to AI & Robotics Integration, Reducing Discovery Risk and Unveiling Mechanisms
arXiv USA Overview An arXiv paper highlights the paradigm shift in computational materials science from mere data reproduction to algorithms guiding exploration and risk reduction. This evolution integrates high-fidelity methods, uncerta... -
University of Washington Leverages AI and Quantum Computing for Scaled Quantum Material Simulations, Uncovering New Phenomena
EurekAlert! USA Overview University of Washington scientists have successfully integrated AI and quantum computing to enable large-scale quantum material simulations previously deemed impossible. This innovative approach has led to the d...
