…data platforms. DDN said the updates are intended to address bottlenecks throughout the AI data pipeline, including data preparation, model training, inference, retrieval-augmented generation (RAG), reasoning models, and agentic AI workloads…
…for a different platform in both hardware and software. The framing is that DGX Spark is built for Linux and AI developers, while RTX Spark is a Windows-first product that layers…
…As HPE’s first scale-up system based on Intel Xeon 6, the platform delivers higher compute density and is well-positioned to support emerging workloads, including agentic AI, alongside traditional enterprise…
…By maintaining context across inference operations, the platform reduces redundant computation and improves overall system efficiency. In internal benchmarks, MinIO reports improvements in time-to-first-token at production concurrency levels. In…
…Venice is also expected to introduce the new SP7 socket, a physically larger platform than the outgoing SP5 that is designed to accommodate higher power delivery, additional memory channels, and expanded I…
…platform supports GPU-equipped NAS systems and dedicated AI appliances, enabling organizations to run AI inference workloads on-premises while maintaining governance and control over sensitive data. Synology also introduced DSM Agent…
…FERPA, Data Sovereignty, and Why the Cloud Is Not the Answer When Sullivan stepped in to build OSU’s on-premises implementation of the Metrum platform, the first thing he identified was…
…breadth (CUDA, cuDNN, TensorRT-LLM, and the PyTorch-first serving stack land on NVIDIA first; native PyTorch on TPU is still preview). Both platforms have demand. Meta is reportedly in discussions for…
…up well for a self-hosted platform. Claude Code concurrency testing put a finer point on the practical value: eight engineers can run simultaneous agentic coding sessions against a locally hosted 230B…
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