An analysis of AI assistant infrastructure argues that differences in training and serving infrastructure between OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini matter more to small busines…
A developer trained a 3.8-billion-parameter dense language model to a CORE score of 0.384 for a total budget of $998, according to an account of the Little LM project. The run relied on Grouped Query …
Nvidia is winning the AI war by selling entire ecosystems rather than just chips, leveraging CUDA software gravity, TensorRT, NeMo, and Mellanox-owned InfiniBand networking to lock developers into its…
Nvidia is winning the AI race by focusing on data center interconnect and networking technologies rather than just raw chip performance, according to an analysis. The company's NVLink, Mellanox-based …
NVIDIA Corporation (NASDAQ: NVDA) reported Q1 FY27 Data Center revenue of $75.246 billion, up 92% year over year, and total revenue of $81.61 billion, up 85.23%, as CEO Jensen Huang said 'Agentic AI h…
Nvidia reported fiscal Q1 2027 data center revenue of $75.2 billion, up 92% year-over-year, accounting for 92% of total revenue of $81.6 billion. CEO Jensen Huang cited agentic AI as a key demand driv…
Nvidia is pursuing a $500 billion market valuation target by integrating its InfiniBand networking, CUDA software, and Blackwell architecture into a proprietary full-stack ecosystem, creating high swi…
Cisco is championing an 'Ethernet-first' strategy for AI infrastructure, arguing that Ethernet is becoming the predominant networking technology for AI supercomputing due to its open standards, scalab…
A new arXiv paper (arXiv:2607.28633v1) proposes a topology-aware transfer orchestrator for disaggregated GPU inference, claiming existing systems like DistServe, Splitwise, and Mooncake ignore that ba…
Advanced Micro Devices Inc. used its Advancing AI 2026 event to argue that its Helios rack-scale platform requires radical openness in networking, as monthly token consumption has surged 158 times in …
Cisco's new white paper, 'A Day in the Life of a Prompt,' warns that AI inference is becoming a networking issue as data movement emerges as the primary bottleneck for GPU performance. The paper forec…
NVIDIA's NVLink and NVSwitch technologies form a scale-up fabric that connects GPUs tightly enough to behave as a single machine, contrasting with scale-out fabrics like InfiniBand and RoCE that link …
Google's TPU clusters use 2D or 3D torus topologies with 4 or 6 nearest neighbors per chip, while NVIDIA GPU clusters rely on fat-tree topologies over InfiniBand, according to a July 14, 2026 technica…
AMD has published an analysis of network traffic patterns in AI training clusters, identifying congestion hotspots and harmonic-like oscillations caused by synchronized collective communication operat…
AI clusters often underperform despite powerful GPUs because the GPUs are idle due to bottlenecks in data loading, CPU preprocessing, network communication, or storage contention. A developer explains…
A developer with years of experience in AI and machine learning systems argues that infrastructure—GPU clusters, high-speed storage, memory, networking, and specialized servers—is the hidden backbone …
Enterprise leaders are realizing that AI efficiency depends not only on model optimization but also on co-design of hardware, compilers, runtime, and cloud architecture. Inefficient AI can cost billio…
InfiniBand, a high-performance interconnect technology designed for Remote Direct Memory Access (RDMA), has become critical for AI training and inference workloads that require direct data movement be…
NVIDIA introduced intent-based security profiles in its Unified Fabric Manager for Quantum InfiniBand, enabling network administrators to configure multi-tenant fabric security with a single click. Th…
Canonical published an explainer on RDMA over Converged Ethernet (RoCE), a technology that runs the RDMA programming model over standard Ethernet networks to bypass the kernel and reduce CPU involveme…