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| | Run Google DeepMind’s Gemma 3n on NVIDIA Jetson and RTX | | | As of today, NVIDIA now supports the general availability of Gemma 3n on NVIDIA RTX and Jetson. Gemma, previewed by Google DeepMind at Google I/O last month,... | | | | | |
| | Check Out Sovereign AI in Practice Through an NVIDIA Webinar | | | Join NVIDIA experts and leading European model builders on July 8 for a webinar on building and deploying multilingual large language models. | | | | | |
| | How to Streamline Complex LLM Workflows Using NVIDIA NeMo-Skills | | | A typical recipe for improving LLMs involves multiple stages: synthetic data generation (SDG), model training through supervised fine-tuning (SFT) or... | | | | | |
| | Join Us at We Are Developers World Congress 2025 | | | Join us at We Are Developers World Congress from July 9 to 11 to attend our workshops and connect with experts. | | | | | |
| | Powering the Next Frontier of Networking for AI Platforms with NVIDIA DOCA 3.0 | | | The NVIDIA DOCA framework has evolved to become a vital component of next-generation AI infrastructure. From its initial release to the highly anticipated... | | | | | |
| | NVIDIA Run:ai and Amazon SageMaker HyperPod: Working Together to Manage Complex AI Training | | | NVIDIA Run:ai and Amazon Web Services have introduced an integration that lets developers seamlessly scale and manage complex AI training workloads. Combining... | | | | | |
| | Introducing NVFP4 for Efficient and Accurate Low-Precision Inference | | | To get the most out of AI, optimizations are critical. When developers think about optimizing AI models for inference, model compression techniques—such as... | | | | | |
| | Upcoming Livestream: Beyond the Algorithm With NVIDIA | | | Join us on June 26 to learn how to distill cost-efficient models with the NVIDIA Data Flywheel Blueprint. | | | | | |
| | Making Industrial Robots More Nimble With NVIDIA Isaac Manipulator and Vention MachineMotion AI | | | As industrial automation accelerates, factories are increasingly relying on advanced robotics to boost productivity and operational resilience. The successful... | | | | | |
| | Real-Time IT Incident Detection and Intelligence with NVIDIA NIM Inference Microservices and ITMonitron | | | In today’s fast-paced IT environment, not all incidents begin with obvious alarms. They may start as subtle, scattered signals, a missed alert, a quiet SLO... | | | | | |
| | Finding the Best Chunking Strategy for Accurate AI Responses | | | A chunking strategy is the method of breaking down large documents into smaller, manageable pieces for AI retrieval. Poor chunking leads to irrelevant results,... | | | | | |
| | Improved Performance and Monitoring Capabilities with NVIDIA Collective Communications Library 2.26 | | | The NVIDIA Collective Communications Library (NCCL) implements multi-GPU and multinode communication primitives optimized for NVIDIA GPUs and networking. NCCL... | | | | | |
| | Compiler Explorer: An Essential Kernel Playground for CUDA Developers | | | Have you ever wondered exactly what the CUDA compiler generates when you write GPU kernels? Ever wanted to share a minimal CUDA example with a colleague... | | | | | |
| | How Early Access to NVIDIA GB200 Systems Helped LMArena Build a Model to Evaluate LLMs | | | LMArena at the University of California, Berkeley is making it easier to see which large language models excel at specific tasks, thanks to help from NVIDIA and... | | | | | |
| | AI in Manufacturing and Operations at NVIDIA: Accelerating ML Models with NVIDIA CUDA-X Data Science | | | NVIDIA leverages data science and machine learning to optimize chip manufacturing and operations workflows—from wafer fabrication and circuit probing to... | | | | | |
| | Benchmarking LLM Inference Costs for Smarter Scaling and Deployment | | | This is the third post in the large language model latency-throughput benchmarking series, which aims to instruct developers on how to determine the cost of LLM... | | | | | |
| | Fine-Tuning LLMOps for Rapid Model Evaluation and Ongoing Optimization | | | Large language models (LLMs) have created unprecedented opportunities across various industries. However, moving LLMs from research and development into... | | | | | |
| | R²D²: Building AI-based 3D Robot Perception and Mapping with NVIDIA Research | | | Robots must perceive and interpret their 3D environments to act safely and effectively. This is especially critical for tasks such as autonomous navigation,... | | | | | |
| | Power Real-Time AI Media Effects with New AI Reference Apps on NVIDIA Holoscan for Media | | | Live media workflows are increasingly using AI microservices to augment production capabilities. However, advanced AI models are mostly hosted in the cloud,... | | | | | |
| | Isaac Sim and Isaac Lab Are Now Available for Early Developer Preview | | | NVIDIA today released developer previews of NVIDIA Isaac Sim and NVIDIA Isaac Lab — reference robotics simulation and learning frameworks. Now available on... | | | | | |
| | Enhance Robot Learning with Synthetic Trajectory Data Generated by World Foundation Models | | | Generalist robotics have arrived, powered by advances in mechatronics and robot AI foundation models. But a key bottleneck remains: robots need vast training... | | | | | |
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