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 in just four months, LillyPod accesses 700 TB of data and 290 TB of high‑bandwidth GPU memory while targeting 100 % renewable electricity by 2030. Select models will be offered through the TuneLab platform, giving biotech partners federated‑learning access to Lilly’s proprietary AI assets.
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...
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...