Infrinia AI Cloud OS automates Kubernetes and inference services on GPU infrastructure.
With utilities quoting four‑to‑ten‑year wait times — and one offering a 12‑year study period — Google says grid constraints are becoming the defining limit on AI‑era data center growth.
Zhipu’s GLM-Image demonstrates the viability of domestic alternatives amid US export restrictions.
With capacity shifting to high-margin HBM for AI data centers, traditional DRAM supply is collapsing, pushing enterprise IT costs sharply higher and eroding procurement leverage.
Cloud data platform’s backward-incompatible database schema change left customers unable to query data or ingest files
Energy-starved AI workloads are driving companies to space, but analysts say the technology remains years from general enterprise use.
Nvidia’s investment in a UALink board member follows a similar move with Intel, raising concerns about the GPU giant’s influence over alternatives to its proprietary NVLink interconnect.
The company’s restructuring and memory cost warnings signal challenges ahead for enterprise buyers on pricing and service delivery.
Counterpoint warns that DDR5 RDIMM costs may surge 100% amid manufacturers’ pivot to AI chips and Nvidia’s memory-intensive AI server platforms, leaving enterprises with limited procurement leverage.
VMware’s shift to real-world telemetry data reveals a significant gap between recommended and actual resource usage.
