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AI Reasoning at Scale Try out DeepSeek-R1âs reasoning capabilities with NVIDIA-hosted APIs or deploy it anywhere with NVIDIA NIM inference microservices. Accelerate Apache Spark ML on NVIDIA GPUs with Zero Code Change How Using a Reranking Microservice Can Improve Accuracy and Costs of Information Retrieval Superchar
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Introducing CUDA Rust: Two Tracks for Writing GPU Kernels
1+ week, 1+ day ago (1308+ words) In September 2026, NVIDIA announced it is leaning into native GPU programming in Rust. CUDA C++ and CUDA Python are mature, enterprise-grade toolchains, and NVIDIA will be growing and maturing CUDA Rust into 2027 and beyond The systems layer of AI spans…...
How to Size GPUs for AI Inference and TCO Without Overspending
1+ week, 5+ day ago (571+ words) Cutting through the noise starts with one deceptively simple question: What problem are you solving? Different use cases map to wildly different infrastructure footprints. At a high level, most inference workloads fall into one of these four buckets: After mapping…...
How to Train a Cross-Embodiment Robot Navigation Policy with AI Agents
2+ week, 3+ day ago (1465+ words) Navigation enables a robot to turn perception and motion into purposeful autonomy. Unlike locomotion, which produces stable movement, navigation must be used to continuously localize the robot, interpret changing surroundings, select a route, and avoid obstacles to reach a goal…...
CUDA Python 1.0: Stable APIs, One Foundation, Full Platform Access
2+ week, 5+ day ago (1398+ words) For years, a Python developer who needed a GPU had two realistic choices: Learn NVIDIA CUDA C++ well enough to write an extension, set up a build toolchain, and maintain bindings back to Python, which most people never did; or…...