A new top-level effort unifies data center and network oversight as the company targets multi-gigawatt AI scale.
Lenovo’s “AI cloud gigafactory” model promises speed and scalability for enterprises, but experts caution that utility, cooling, and fiber bottlenecks could slow adoption.
Announcements included the MI440X GPU for on-prem enterprise deployments and a longer-term roadmap that includes rack-scale AI systems and next-generation accelerators.
The unpatched flaw affects AsyncOS-based Secure Email appliances, with Cisco investigating scope and urging rebuilds in confirmed compromise cases.
By acquiring the developer of Slurm, Nvidia is strengthening its influence over how AI workloads are scheduled across GPUs and data center networks.
The open-source tool tracks power, temperature, airflow and interconnect health across thousands of GPUs, helping operators spot issues early and prevent throttling.
The move introduces fresh uncertainty into an already constrained GPU market, forcing buyers to rethink both their timelines and their broader procurement plans for upcoming data-center upgrades.
Their exits may strain Microsoft’s push to expand AI capacity as energy constraints and infrastructure bottlenecks increasingly dictate the pace of cloud growth.
Microsoft says the attack, sourced from more than 500,000 compromised IPs, exposes deep weaknesses in home IoT and raises questions about enterprise DDoS readiness.
Expanded DRAM and HBM output is expected to relieve infrastructure bottlenecks for hyperscalers and data centers amid rising AI demand.
