The Paradigm Shift in Model Training The conventional wisdom in deep learning has been simple: bigger models require bigger infrastructure. Training a 100-billion parameter language model tradition...

Every team that operates GPU clusters for AI has seen this pattern. The cluster boots, GPUs are visible, and scheduling works at a basic level. Then the first distributed training run stalls in NCCL ...

By Valerie Cutts and Jithin Jose   Last fall we introduced Fairwater, the world’s most powerful AI datacenter. Delivering a system of this scale required rethinking how Azure designs supercompute...

Training large AI models on hundreds or thousands of nodes introduces a critical operational challenge: when a distributed job fails, quickly identifying the root cause across scattered logs can beco...

NCv6 Virtual Machines are Azure's flexible, next generation platform enabling both leading-edge graphics and generative AI compute workloads. Featuring NVIDIA RTX PRO 6000 Blackwell Server Edition ...

If you had to point out the top trends of IT these days, two strong candidates would be Generative AI and Cybersecurity. Especially around the latter, sophistication, reach and volume of cyberattacks...

Microsoft returns to NVIDIA GTC 2026 in San Jose with a strong presence across conference sessions, in‑booth theater talks, live demos, and executive‑level ancillary events. Together with NVIDIA an...

As AI models continue to scale in size and complexity, cloud infrastructure must deliver more than theoretical peak performance. What matters in practice is reliable, end-to-end, workload-level AI pe...