NVIDIA Kaggle Grandmasters Win Artificial General Intelligence Competition
NVIDIA researchers on Friday won a key Kaggle competition many in the field treat as a real-time pulse check on humanity’s progress toward artificial general...
Simplify GPU Programming with NVIDIA CUDA Tile in Python
The release of NVIDIA CUDA 13.1 introduces tile-based programming for GPUs, making it one of the most fundamental additions to GPU programming since CUDA was...
Focus on Your Algorithm—NVIDIA CUDA Tile Handles the Hardware
With its largest advancement since the NVIDIA CUDA platform was invented in 2006, CUDA 13.1 is launching NVIDIA CUDA Tile. This exciting innovation introduces a...
Optimize Data Center Efficiency for AI and HPC Workloads with Power Profiles
Exponentially growing computational demand is driving power usage higher and pushing data centers to their limits. With facilities power constrained, extracting...
Train Small Orchestration Agents to Solve Big Problems
Using the right tool and model for a task is a challenging and ever-present engineering problem in agent design. At NVIDIA Research, we're making fast progress...
How to Scale Data Generation for Physical AI with the NVIDIA Cosmos Cookbook
Building powerful physical AI models requires diverse, controllable, and physically-grounded data at scale. Collecting large-scale, diverse real-world datasets...
As generative AI advances, organizations need AI agents that are accurate, reliable, and informed by data specific to their business. The NVIDIA AI-Q Research...
Achieve CUTLASS C++ Performance with Python APIs Using CuTe DSL
CuTe, a core component of CUTLASS 3.x, provides a unified algebra for describing data layouts and thread mappings, and abstracts complex memory access patterns...
Building Scalable and Fault-Tolerant NCCL Applications
The NVIDIA Collective Communications Library (NCCL) provides communication APIs for low-latency and high-bandwidth collectives, enabling AI workloads to scale...
How to Achieve 4x Faster Inference for Math Problem Solving
Large language models can solve challenging math problems. However, making them work efficiently at scale requires more than a strong checkpoint. You need the...
Streamline Complex AI Inference on Kubernetes with NVIDIA Grove
Over the past few years, AI inference has evolved from single-model, single-pod deployments into complex, multicomponent systems. A model deployment may now...
Benchmarking LLMs on AI-Generated CUDA Code with ComputeEval 2025.2
Can AI coding assistants write efficient CUDA code? To help measure and improve their capabilities, we created ComputeEval, a robust, open source benchmark for...
Enhancing GPU-Accelerated Vector Search in Faiss with NVIDIA cuVS
As companies collect more unstructured data and increasingly use large language models (LLMs), they need faster and more scalable systems. Advanced tools for...
How to Predict Biomolecular Structures Using the OpenFold3 NIM
For decades, one of biology’s deepest mysteries was how a string of amino acids folds itself into the intricate architecture of life. Researchers built...
