Stream High-Fidelity Spatial Computing Content to Any Device with NVIDIA CloudXR 6.0 | NVIDIA Technical Blog
… By using WebRTC and WebXR, it removes the need for native application installs on devices like Meta Quest 3 and PICO 4 Ultra. …
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Accelerating Long-Context Model Training in JAX and XLA | NVIDIA Technical Blog
… Unlike data parallelism, which splits the batch, or tensor parallelism, which splits the model, context parallelism splits the sequence dimension across multiple devices. …
Accelerating AI-Powered Chemistry and Materials Science Simulations with NVIDIA ALCHEMI Toolkit-Ops | NVIDIA Technical Blog
… We are excited to announce in-progress integrations with leading open source tools in the chemistry and materials science community: TorchSim, MatGL, and AIMNet Central. …
NVIDIA In-Game Inferencing SDK
…integrates with ACE to enable seamless AI inference in game development. It covers NVIGI’s architecture, key features, and how to get started creating autonomous characters with NVIDIA ACE on-device models…
Building Custom Atomistic Simulation Workflows for Chemistry and Materials Science with NVIDIA ALCHEMI Toolkit | NVIDIA Technical Blog
… We’re excited to announce the following integrations with leading platforms in the chemistry and materials science community. …
NVIDIA ACE for Games
…Get Started with NVIDIA ACE On-Device The NVIDIA In-Game Inferencing (NVIGI) SDK offers a streamlined and high-performance path to integrate locally run AI models into games and applications via…
Build and Stream Browser-Based XR Experiences with NVIDIA CloudXR.js | NVIDIA Technical Blog
…Developers can integrate CloudXR.js with various web frameworks and utilize provided WebGL and React sample clients for rapid prototyping, while production deployments are supported with Docker, WebSocket proxy configurations, and compatibility…
NVIDIA RTX Innovations Are Powering the Next Era of Game Development | NVIDIA Technical Blog
… By leveraging AST-aware chunking, MCP integrations, and fine-tuned models for large codebases, the guide aims to boost developer velocity while ensuring compatibility with complex studio pipelines. …
Federated Learning Without the Refactoring Overhead Using NVIDIA FLARE | NVIDIA Technical Blog
… The typical flow is: import, patch, optional validate, train as usual. lightning client.py import pytorch lightning as pl from pytorch lightning import Trainer import nvflare.client.lightning as flare Lightning Client API from model import LitNet from data import CIFAR10DataModule def main : model … …
Bringing AI Closer to the Edge and On-Device with Gemma 4 | NVIDIA Technical Blog
Agentic AI / Generative AI Bringing AI Closer to the Edge and On-Device with Gemma 4 Apr 02, 2026 By Anu Srivastava Discuss 0 Discuss 0 L T F R E AI-Generated Summary Like Dislike The Gemma 4 multimodal and multilingual model family was launched to support a wide range of AI tasks, offering improve… …