NVIDIA Technical Blog
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NVIDIA Technical BlogSiliconAccelerating Mamba-2 with High-Performance Forward Pass Kernels in NVIDIA CUDA Tile NVIDIA CUDA Tile (cuTile) is a Python-based DSL and parallel programming model for NVIDIA GPUs that automatically leverages advanced hardware capabilities to...
NVIDIA Technical BlogSiliconCode, Test, and Deploy on One Machine with NVIDIA RTX Spark AI agents are changing how software gets built. Developers have gone from writing every line of code by hand to directing agents that write most of the code. As...
NVIDIA Technical BlogSiliconNVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning Always-on agents are taking on longer, more complex enterprise workflows. A single request can involve reading a document, checking information across sources,...
NVIDIA Technical BlogSiliconScale Agentic Coding Workflows with Meta’s Muse Spark Open on NVIDIA GB300 NVL72 Meta launches Muse Spark Open, a coding-optimized 816B mixture-of-experts (MoE) model with 42B active parameters and a 1M token context window. Trained on...
NVIDIA Technical BlogSiliconOptimizing Agent Reliability and Tool Calling Efficiency for Chip Design Using NVIDIA NeMo Gym AI agents offer remarkable productivity gains in complex chip design workflows, but their tendency to generate plausible yet incorrect artifacts makes...
NVIDIA Technical BlogSiliconHow to Rewrite Apache Spark UDFs for GPU Acceleration with AI Agents Enterprise applications have become increasingly demanding. Agentic AI has compounded the need for vast amounts of enterprise data with frequent, complex...
NVIDIA Technical BlogSiliconNVIDIA Run:ai Is Now Open Source as Part of NVIDIA DSX AI Factory Platform NVIDIA is making the full NVIDIA Run:ai platform available as open source software, giving customers, developers, and ecosystem partners access to...
NVIDIA Technical BlogSiliconReplaySSM: Rethinking State Storage for Faster Hybrid-Model Decoding Hybrid models interleave state-space model (SSM) layers with a few attention layers. NVIDIA Nemotron 3, Qwen3.5 through Qwen3.8, Kimi-K3, and GLM-5.3-Flash are...
NVIDIA Technical BlogSilicon5 Steps to Create SimReady Assets for Robotics with Frontier AI Models Preparing CAD assets for robotics simulation requires more than converting geometry to OpenUSD: developers must configure and validate materials, collision...
NVIDIA Technical BlogSiliconBuilding Reliable Data Analytics Agents: Lessons from the KDD Cup The NVIDIA KGMON team placed second in the KDD Cup 2026 Data Agents competition with a system built around a simple idea of making an agent's harness smaller,...
NVIDIA Technical BlogSiliconThe Machines that Make the Machines How we taught robots to assemble GB300 tester trays and what it taught us about robot learning, mechanical intelligence, and good old-fashioned engineering The...
NVIDIA Technical BlogSiliconValidate AI Factory Changes with Digital Twins and AI Agents AI factories are some of the most complex operations in the world, combining GPUs, CPUs, switches, DPUs, and SuperNICs alongside schedulers, orchestration...
NVIDIA Technical BlogSiliconScaling Decision Optimization to 100 Million Variables and Beyond with mPDLP in NVIDIA cuOpt Supply chain problems are expanding across more SKUs, lanes, and constraints than ever before, while energy grids are balancing more distributed sources in real...
NVIDIA Technical BlogSiliconFaster Scientific Image Analysis with NVIDIA cuPhoton Observatories and telescopes, lasers and X-ray light sources, and other high-throughput instruments generate image data faster than CPU-bound pipelines can...
NVIDIA Technical BlogSiliconScale Bitwise-Deterministic Pretraining with NVIDIA Megatron Core Bitwise determinism makes large-scale pretraining easier to debug, validate, and resume reproducibly. These benefits become especially valuable when training...
NVIDIA Technical BlogSiliconHow DOCA GPUNetIO Unifies GPU-Initiated Networking Across the NVIDIA Software Stack GPU applications increasingly need networking and data movement to behave like first-class GPU-controlled operations rather than host-driven services. When the...
NVIDIA Technical BlogSiliconAICR v1.0: Open, stable, and verifiable GPU cluster configuration GPU-accelerated Kubernetes clusters depend on compatible versions across dozens of components, each on its own release cycle: host kernels, GPU drivers,...
NVIDIA Technical BlogSiliconControl How Your GPU Shares Work with Green Contexts GPU applications increasingly consist of multiple independent components running at the same time within a single process: a latency-sensitive operator...
NVIDIA Technical BlogSiliconBuild Applications on NVIDIA BlueField Faster with NVIDIA DOCA Agent Skills AI agents are becoming a standard part of development workflows, but general-purpose agents weren't built with specialized infrastructure software such as...
NVIDIA Technical BlogSiliconBuild Local AI Apps with C++ and NVIDIA TensorRT RTX Samples Adding AI models to local applications requires a portable model format, a reliable runtime, and acceleration that works across target systems. Do Inference Now...
NVIDIA Technical BlogSiliconFine-Tuning NVIDIA Nemotron for Saudi Arabic Dialects, with a Path to Other Languages Automatic speech recognition must handle how people actually speak, not only the languages and styles that dominate pretraining data. Regional dialects and...
NVIDIA Technical BlogSiliconDeploying an HSTU Generative Recommender with NVIDIA Dynamo-Triton Generative recommender (GR) systems are emerging as a powerful new approach for large-scale personalization. Instead of treating recommendation as a set of...
NVIDIA Technical BlogSiliconExpanding AI Storage Access with NVIDIA cuObject and the NVIDIA SCADA Server SDK AI infrastructure engineers, storage developers, and cloud service providers need fast and secure access to high-capacity file and object storage to support AI...
NVIDIA Technical BlogSiliconTracing Agent Harness Behavior with NVIDIA NeMo Relay An agent can finish a task and still take an inefficient path. A failed search can trigger another search. A truncated file read can lead to a command fetching...
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