Berkeley Lab: DL4SCI 2026 to Spotlight Discovery Through Agentic AI, Foundation Models
The National Energy Research Scientific Computing Center and Berkeley Lab will host the 2026 Deep Learning for Science (DL4SCI) Summer School from July 20‑24. The five‑day intensive program emphasizes foundation models, reasoning‑centric workflows, and agentic AI for scientific discovery. Researchers and engineers can apply until April 10 to join lectures, hands‑on tutorials, and networking sessions designed to translate cutting‑edge AI techniques into research practice. Since its 2019 launch, DL4SCI has become a key conduit for industry, academia, and lab expertise to reach the broader scientific community.
DOE Announces $320M Investment in Pioneering Scientific Research
The U.S. Department of Energy announced a $320 million investment to support 217 university and industry projects across physical sciences. Funding will be allocated to research in materials science, plasma and fusion, nuclear and particle physics, chemical and molecular sciences, quantum...
LANL Develops Diffusion AI Model for Electroplating Process Optimization
Los Alamos National Laboratory researchers have created a generative diffusion‑based AI model that predicts the micro‑structure of electroplated materials. The system was trained on high‑resolution scanning electron microscope images of 57 rhenium samples, learning to map process parameters to surface...
Alzheimer’s Disease Data Initiative Doubles $1M Prize Competition for Agentic AI Solutions
The Alzheimer’s Disease Data Initiative announced that Biomni-AD and Prima Mente each won the $1 million Alzheimer’s Insights AI Prize, doubling the competition’s total payout to $2 million. The competition, launched in August 2025 and backed by Bill Gates and a broad...
PNNL: Robotics and AI Power Biotechnology Advances
Pacific Northwest National Laboratory has merged AI with high‑throughput robotics to speed microbial biotechnology development. Researchers adapted the open‑source BacterAI platform to model continuous growth‑boundary conditions, then paired it with a Tecan Fluent liquid‑handling system that can execute thousands of...
NERSC Issues 2026 Call for AI for Science Proposals
The National Energy Research Scientific Computing Center (NERSC) has launched its 2026 AI for Science call, offering up to 10,000 GPU node hours on the Perlmutter supercomputer and up to 20,000 CPU node hours for AI‑ready dataset generation. The open...
Researchers Develop AI Framework Combining Expert Knowledge and Data to Accelerate Alloy Discovery
Researchers at Japan Advanced Institute of Science and Technology unveiled an AI‑for‑Science framework that merges experimental alloy data, computational models, and expert knowledge extracted from scientific literature using large language models. The system fuses these evidence streams with Dempster‑Shafer theory,...
WEKA Releases NeuralMesh AI Data Platform Based on NVIDIA AI Data Platform Design
WEKA announced the general availability of its NeuralMesh AI Data Platform (AIDP), an enterprise‑ready, composable storage solution built on NVIDIA’s AI Data Platform reference design. The platform promises to shrink AI project timelines from months to minutes by delivering high‑performance,...
Jeonbuk National University Researchers Develop DDINet for Drug-Drug Interaction Prediction
Researchers at Jeonbuk National University have unveiled DDINet, a lightweight neural network designed to predict drug‑drug interactions (DDIs) for previously unseen compounds. The model employs five fully‑connected layers and molecular fingerprints, with Morgan fingerprints delivering the best results. Using a...
Argonne-Led AI ‘Adviser’ Accelerates Robotic Design of Advanced Electronic Materials
Argonne National Laboratory’s team unveiled an AI “adviser” that monitors and optimizes machine‑learning algorithms during autonomous experiments, dramatically speeding the discovery of mixed ion‑electron conducting polymers. Integrated with the Polybot robotic lab, the adviser reduced the experimental space from over...
LLNL-Led Study Uses Machine Learning, Veterans’ Health Records to Identify ALS Drug-Repurposing Candidate
Lawrence Livermore National Laboratory and partners applied causal‑inference machine learning to electronic health records of more than 11,000 U.S. veterans with amyotrophic lateral sclerosis. The analysis, published in The Lancet Digital Health, identified 27 existing medications that correlate with longer...
A New AI Model Could Help Scientists Design New Forms of Life
Researchers at the Arc Institute unveiled Evo2, an AI model trained on trillions of DNA bases from diverse organisms. By treating DNA as language, Evo2 can generate genome‑scale sequences millions of letters long, demonstrated with Mycoplasma genitalium‑inspired designs. The model...
Siemens to Help Build AI-Ready Scientific Infrastructure as Part of DOE’s Genesis Mission
Siemens announced a memorandum of understanding with the U.S. Department of Energy to support the Genesis Mission, a federal effort to modernize America’s scientific infrastructure with AI‑driven computing and interoperable digital systems. The partnership leverages Siemens’ expertise in industrial AI,...
Unreasonable Labs Emerges From Stealth with AI Platform for Scientific Discovery
Unreasonable Labs announced its launch from stealth and closed a $13.5 million Series A round led by Playground Global, with participation from AIX Ventures, E14 Fund, and MS&AD Ventures. The Cambridge‑based startup, founded by a former Google DeepMind senior scientist and an...
Kempner Institute Announces 2026 Accelerator Awards Request for Proposals
Harvard’s Kempner Institute has opened its 2026 Accelerator Awards request for proposals, offering faculty access to the Kempner AI Cluster. Winners receive up to 64 GPUs for a 30‑day period to conduct advanced intelligence research. The program, now in its...
Lilly Launches LillyPod NVIDIA DGX SuperPOD for Genomics and Drug Discovery AI
Eli Lilly unveiled LillyPod, a DGX SuperPOD built with 1,016 NVIDIA Blackwell Ultra GPUs delivering more than 9,000 petaflops of AI performance. The system powers genomics, protein‑diffusion, small‑molecule graph neural networks and foundation models, allowing billions of in‑silico experiments. Constructed...
UAlbany, UConn Researchers Launch Initiative to Improve Power Outage Predictions and Grid Resilience
Researchers at the University at Albany and the University of Connecticut have launched the North American Forecasting Weather, Outage, Load & Damage Initiative to create an AI‑driven model that predicts storm‑related power outages across the United States and Canada. Backed...
Inside the DOE’s 26 AI Challenges for Genesis Mission
The U.S. Department of Energy unveiled 26 artificial‑intelligence challenges that underpin its Genesis Mission, spanning nuclear systems, grid modernization, materials science, advanced manufacturing, microelectronics and national security. The announcement shifts AI from a purely analytical tool to the connective tissue...