AI Infrastructure

ABI Research forecasted AI inference workloads to surpass training by 2033 and reach more than 46 GW by 2035.

NeoCloud providers need faster GPU onboarding, multi-tenant orchestration, vendor-neutral networking, deep observability, packet-level compliance monitoring, and AI support.

SEALSQ outlined a plan for post-quantum semiconductor and PKI technologies for orbital computing and space-based data centers.

Weekly roundup covering Linux local privilege escalations, AI networking and security updates, and governed cloud and compliance certifications.

AI networking may top $200B by decade’s end, with software estimated at $40–50B, driven by Ethernet fabrics, observability, automation, and open networking.

NVIDIA and IREN plan DSX AI factory deployments, including up to 5 gigawatts across IREN’s pipeline and a Sweetwater focus.

Rackspace Technology and AMD signed an MOU outlining a multiyear partnership to build a governed Enterprise AI Cloud for regulated and sovereign workloads. The proposal integrates AMD Instinct GPUs and EPYC CPUs into a fully managed stack, covering private/hybrid deployment, inference runtime, and managed inference services with defined SLAs.

Aviz Networks podcast says AI changes networking via AI-ready infrastructure and AI-driven network operations, with KPIs shifting to efficiency.

Supermicro said its new Silicon Valley DCBBS campus near San Jose covers 32.8 acres and will add domestic capacity.

AI-era infrastructure needs change before failure, the post argues, citing cost, operating model, and networking execution differences.

AI traffic is increasing demand on switching fabrics and shortening network refresh cycles from 5–7 years to about 3.

Aviz Networks webinar says simulation-first AI factory design validates configurations, security, and failures before hardware arrives.