How NVIDIA Uses Kong

Learn how NVIDIA NeMo Switchyard routes AI agent workloads across models using tuning-free and tunable routers that balance model capability, cost, and latency.

Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what’s…

Co-designed hardware, software, and models are key to delivering the highest AI factory throughput and lowest token cost. Measuring this goes far beyond peak…

This article discusses how to rapidly simulate robotic environments using NVIDIA Isaac Sim and World Labs Marble.

The article introduces the Nemotron-H Reasoning Model Family developed by NVIDIA, which addresses the challenges of reasoning-intensive tasks in large language models by significantly improving thr...

The article discusses the advancements of NVIDIA's Blackwell architecture, highlighting its significant performance improvements in MLPerf Inference v5.

Federated learning is transforming the development of autonomous vehicles (AVs) by allowing decentralized training using locally collected data.

The article discusses the NVIDIA Merlin HugeCTR TensorFlow embedding plugin, which significantly enhances the performance of deep learning recommender systems by optimizing embedding layers.

NVIDIA Researchers are set to present 19 accepted papers and posters at the CVPR 2018 conference, showcasing advancements in AI and computer vision technologies.

NVIDIA announced significant updates to its software suite, including the CUDA Toolkit, NV Deep Learning SDK, and TensorRT, aimed at enhancing performance for deep learning and AI applications.

This article discusses a Generative Adversarial Networks (GAN)-based approach developed by researchers from multiple universities to transform facial expressions in still images.

Researchers from The University of Hong Kong have developed a deep learning-based sketching system that enables users to create a 3D face model in minutes.

Researchers from Adobe Research and The Chinese University of Hong Kong developed a deep learning algorithm that effectively separates subjects from backgrounds in images, allowing for easy backgro...

The article discusses how researchers at The Chinese University of Hong Kong utilized GPU-accelerated deep learning to enhance cancer image analysis, potentially saving time for physicians and pati...