3 real-world examples of companies getting results from AI in energy & utilities: the numbers, the companies, and the tools behind each win. Updated daily.
Most-used tools here: Phaidra, NVIDIA DSX, NVIDIA Earth-2, Vaisala Xweather StormScope, NVIDIA DSX MaxLPS, NVIDIA GB300 NVL72
Phaidra applied self-learning AI agents built on NVIDIA DSX Flex, DSX Max-Q and DSX Exchange to tune cooling and power allocation in data centers. The result is roughly 10% more usable compute under the same power budget, plus better grid flexibility…
AXA is using NVIDIA's open Earth-2 weather models to simulate regional cyclone risk across more than 1,000 seasons. Vaisala Xweather is adding lightning data to its StormScope nowcasting tool for short-term warnings, and TotalEnergies is testing subhourly…
European AI cloud provider Nscale tested NVIDIA DSX MaxLPS on GB300 NVL72 systems to match power allocation to workloads. The tests showed 37% more GPUs and nearly 50% higher aggregate inference throughput within the same provisioned power. Nscale plans Vera…