Large Language Model– tag –
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DOE-University Alliance Accelerates Custom Polymer Development via Autonomous AI Inverse Design Workflow and Polybot
Tech Briefs USA Overview Researchers from Argonne National Laboratory (DOE), the University of Chicago, and Purdue University have demonstrated a faster route from target properties to polymer recipes using an autonomous AI inverse desig... -
UChicago’s “ElectrolyteGPT” Unleashes AI-Powered Autonomous Generation of Battery Electrolyte Formulations
UChicago News USA Overview Researchers at the University of Chicago Pritzker School of Molecular Engineering have developed "ElectrolyteGPT," an AI model capable of generating entire battery electrolyte compositions autonomously. This AI... -
Argonne National Laboratory Unveils Roadmap for AI-Driven Autonomous Labs to Revolutionize Battery Research with Large Language Models
Argonne National Laboratory USA Overview Researchers at Argonne National Laboratory have outlined a comprehensive technical roadmap for applying Large Language Models (LLMs) to battery research. Integrated into AI-driven autonomous labs ... -
Finland’s VTT Unveils ‘RADIANT’ Project: AI to Shrink Materials Development from Years to Months
VTT フィンランド Overview Finland's VTT Technical Research Centre and the University of Helsinki have launched the AI-driven "RADIANT" project, aiming to slash new materials development time from years to months. This platform integrates... -
Google Research Introduces “Matter to Mechanism” Benchmark to Accelerate Battery Research with AI Co-Scientists
Google Research USA Overview Google Research has introduced "Matter to Mechanism," a benchmark to evaluate AI co-scientists' ability to derive plausible, mechanism-based solution hypotheses from specific scientific and technical problems... -
“Satisfiable Drift” Problem Emerges in Multi-Turn Reasoning of LLMs, Revealed by Novel DRIFT-Bench Benchmark
AI Accelerator Institute International Overview Researchers developed DRIFT-Bench, a solver-instrumented benchmark with 816 test problems across three constraint domains, to evaluate multi-turn reasoning in open-weight models ranging fro... -
Foundation Models Advance Wireless Communications from PHY Intelligence to Network Autonomy via Multimodal Data Alignment and Agentic RAG Frameworks
arXiv International Overview A preprint explores the application of foundation models in wireless communications, from physical layer intelligence to network autonomy. Contrastive foundation models are discussed for aligning multimodal d... -
Meta Aims for AI Differentiation with Enhanced Health Capabilities, Starting with Muse Spark Integration into Consumer Products
Times of India India Overview Alexandr Wang, Meta's Chief AI Officer, announced that future Meta AI models will differentiate themselves through robust health-related capabilities. The Muse Spark model, released in April, has shown promi... -
2026 LLM Leaderboard Reveals Llama 4 Scout as Fastest at 2600 Tokens/Sec, GPT-5.3 Codex Achieves Lowest Latency at 0.003s
Vellum USA Overview The updated 2026 LLM leaderboard, incorporating data from April 2024 onwards, showcases Llama 4 Scout as the fastest model at 2600 tokens/second, while GPT-5.3 Codex records the lowest latency at 0.003 seconds. Nova M... -
Claude Opus 4.8 Achieves Peak Accuracy of 89.08% in Financial LLM Benchmark, Gemini 3.5 Flash Also Highly Rated
AIMultiple USA Overview In a benchmark evaluating over 40 Large Language Models (LLMs) on complex financial reasoning tasks, Anthropic's Claude Opus 4.8 attained the highest accuracy at 89.08%. Google's Gemini 3.5 Flash also demonstrated...
