Desk
NVIDIA hardware, software, and developer news.
Emerald AI, Google, and NVIDIA launched the AI Energy Management Alliance to push data centers that flex electricity use with the grid—not just demand flat megawatts.
Manchester researchers used NVIDIA Earth-2 CorrDiff and StormCast on Isambard-AI to downscale and forecast UK air pollution—after chemistry-heavy models proved too slow to run often.
At Dreamforce, Jensen Huang cast AI safety as an engineering problem solvable by existing law and market discipline—rejecting the “alien mind” framing and new AI-specific regulation.
Huang’s Dreamforce keynote arc—from electricity to internet to AI as infrastructure—landed beside Salesforce’s Koa CRM reasoning model built on NVIDIA Nemotron 3 Super.
NVIDIA’s Sophia Abbassi explains MoE versus dense tradeoffs with Nemotron 3.5 Lightning—30B total, 3B active—where memory stays high but compute per token drops.
Emerald AI’s Conductor took Silicon Valley Power demand signals across thousands of NVIDIA GPUs—200+ events, power dropping on cue—showing AI factories as controllable grid citizens.
At AI Infra Summit, NVIDIA’s Ian Buck highlighted Vera Rubin, DSX, Emerald AI flex load with Silicon Valley Power, Lambda’s 23% perf-per-watt gain, and partner deals from Annapurna to d-Matrix.
NVIDIA details Groq 3 LPX deterministic execution on Vera Rubin—cycle-exact scheduling across 256 LPUs, plus PEP/CPS tricks cutting voltage droop over 60% for interactive inference efficiency.
NVIDIA’s NVLink 6 stack pairs silicon FEC/retry, credit-based flow control, NMX contain-and-drain, and Dynamo Shadow Engine Recovery that restores inference in 7.3s versus 283s cold start on B200.
NVIDIA FLARE 2.9 adds Slurm beside Docker and Kubernetes so federated-learning sites keep local GPUs, secrets, and schedulers without forcing one cluster standard.
At Dreamforce, Salesforce unveiled Koa — a Nemotron-based reasoning model post-trained for sales and support without touching customer data — and aimed it at Claude and ChatGPT token bills.
CHOP turned hours of pediatric heart modeling into seconds with MONAI — and is pushing GPU physics toward same-day device-fit decisions for congenital heart disease.