NVIDIA AI Blueprints are customizable reference workflows for building generative AI pipelines. Developers can use NVIDIA AI Blueprints to build multimodal RAG pipelines. The RAG Blueprint is built on NVIDIA NeMo Retriever models for continuously indexing multimodal documents for fast and accurate semantic search at enterprise scale. The VSS Blueprint ingests massive volumes of streaming or archival video for search, summarization, interactive Q&A, and event-trigger actions such as alerting.
Make Sense of Video Analytics by Integrating NVIDIA AI Blueprints | NVIDIA Technical Blog…Integration with the NVIDIA GPU Operator and DRA/ComputeDomains allows automated GPU management, topology-aware multinode scheduling, and per-job GPU monitoring, supporting advanced NVIDIA architectures like GB200 NVL72 with dynamic Internode…
…which provides PyTorch-native high-throughput fine-tuning, Slurm and Kubernetes multinode support, and Hugging Face integration for streamlined adaptation and optimization. AI-generated content may summarize information incompletely. Verify important information…
…Built on Linux Kernel 6.8 and Ubuntu 24.04 LTS, and designed with a modular, cloud-native architecture, it integrates the latest NVIDIA AI compute stack and seamlessly integrates with NVIDIA…
…The recommended integration path is direct SDK integration: linking the CloudXR libraries into your application and managing the service lifecycle programmatically on both Windows and Linux servers. This gives your application full…
…A collection of GPU-accelerated simulation building blocks, including geometry optimizers, integrators, and data structures, to enable large-scale, batched simulations with AI ALCHEMI Toolkit-Ops: A repository of GPU-accelerated, batched…
…Faysal Khan , TJ Xu and Arnav Goel Discuss (0) Discuss (0) L T F R E AI-Generated Summary Like Dislike Integrating NVSHMEM with the XLA compiler and JAX enables efficient training…
…NVIDIA collaborates with studios to enhance AI reliability in Unreal environments by integrating syntax-aware code indexing, hybrid search methods (including NVIDIA NeMo Retriever NIM), and GPU-accelerated vector search (NVIDIA cuVS…
…Current integration methods are often fragmented across IHV solutions, forcing operations to execute layer-by-layer and incurring high performance overhead. Furthermore, because AI tasks frequently run out of sync with primary…
…We’re excited to announce the following integrations with leading platforms in the chemistry and materials science community. Orbital Orbital develops advanced AI foundation models used to accelerate the discovery of novel…
…A collection of GPU-accelerated simulation building blocks, including geometry optimizers, integrators, and data structures to enable large-scale, batched simulations leveraging AI. ALCHEMI NIM microservices : A scalable layer of cloud‑ready…