Machine Learning– tag –
-
PMC Advocates AI-Driven Labs for Optimizing Next-Gen Battery Materials in Humanoid Robotics
PMC International Overview A PMC article highlights the critical early-stage role of machine learning and AI-driven labs in advancing next-generation batteries for humanoid robotics. It emphasizes the necessity of Bayesian optimization a... -
Aisot Technologies Raises €2.13 Million Seed Extension for AI-Powered Portfolio Intelligence Platform Targeting Institutional Investors
Startupticker.ch Switzerland Overview Zurich-based Aisot Technologies has raised €2.13 million in a Seed extension round for its AI-powered portfolio intelligence platform for institutional investors. Spun off from ETH Zurich, the compan... -
AI & Machine Learning Weekly Report August 9, 2026
▼ ▼ ▼ If the infographic makes you want to read the full report, please click the download button below. ▼ ▼ ▼ 📄 Weekly Report August 09, 2026 (PDF) — Download Weekly Report August 09, 2026 (PDF) — DownloadDownload 🎙 Podcast August 09, ... -
AI Drives Strategic Advancement in Biopharmaceutical Development: From Antibody Design to Quality Control, Backed by Indian Government Initiatives
Press Information Bureau, Government of India India Overview AI is strategically transforming biopharmaceutical development, from target identification and multispecific antibody design to automated quality control. India is significantl... -
MIT Accelerates Sodium Metal Battery Electrolyte Design with Machine Learning: Key Role of Solvent Size and Molecular Similarity
MIT News USA Overview MIT researchers introduced a new approach to electrolyte design by developing a machine learning-driven pipeline enabling the generation, selection, and experimental validation of solvent candidates. This approach d... -
Scilight Press Publishes Review on AI-Driven Rational Design of Solid-State Electrolytes: Paving the Way for Next-Gen Batteries
Scilight Press Unknown Overview Scilight Press published a review paper on AI's role in advancing the rational design of solid-state electrolytes (SSEs) for high energy density and safety in next-generation rechargeable batteries. The pa... -
IIT KANPUR Elucidates Material Structure-Property Relationships with Computational Materials Science: Leveraging DFT, MD/MC, and PFM
MSE | IIT KANPUR India Overview IIT KANPUR emphasizes computational materials science as a powerful toolkit for solving material-related problems, citing Density Functional Theory (DFT) at the electronic level, Molecular Dynamics (MD) an... -
DOE Basic Energy Sciences Supports Software Development for New Materials and Chemical Processes Towards Next-Gen Exascale Computing
Department of Energy (DOE) USA Overview The U.S. Department of Energy's (DOE) Basic Energy Sciences (BES) division is supporting research teams developing software and databases to accelerate the design of new materials and chemical proc... -
UW Research Accelerates Multifunctional Materials Discovery with AI Inverse Design Framework: Achieving 60% Thermal Conductivity Improvement and 10% Cost Reduction
Mechanical Engineering | University of Washington USA Overview Researchers at the University of Washington (UW) developed a novel 'inverse design framework' combining physics-based modeling and machine learning, accelerating the discover... -
Berkeley Lab Accelerates Advanced Materials Development with New AI-Thermodynamics Modeling Approach: Enhancing Solid-Phase Reaction Prediction
Berkeley Lab USA Overview A new modeling framework, leveraging accurate thermodynamics and machine learning, precisely and rapidly predicts a sequence of events in solid-phase reactions, including intermediate compounds, final products, ...
