How Generative Recommenders Are Redefining RecSys at Scale | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·1d ago
Recommender systems (RecSys) are one of the most ubiquitous machine learning problems in the consumer internet industry yet notoriously difficult to train and serve at scale.
Developing NVIDIA Holoscan Applications with CLI, Skills, and AI Coding Agents | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·1d ago
NVIDIA Holoscan is a platform for building real-time AI applications at the edge, from medical imaging to robotics.
Building Federated Multimodal AI Workflows with NVIDIA FLARE | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·2d ago
Modern vision-language models (VLMs) can support tasks such as visual question answering, captioning, and image-text reasoning.
Evaluating AI Agent Skill Performance with NVIDIA SkillEvaluator | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·2d ago
AI agents are only as effective as the context they receive. Even with capable models and well-documented NVIDIA libraries, agents can spend extra steps finding the right tools, burn tokens on dead...
Post-Train NVIDIA Cosmos 3 Edge for On-Device Robot Control | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·2d ago
Robots need policies that can adapt to their sensors, environments, and tasks while running on onboard computing hardware.
How AI Coding Agents Can Unlock Materials Simulation with NVIDIA ALCHEMI Toolkit | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·3d ago
Atomistic simulation requires three things: knowledge of the science, compute-efficient implementation of simulations, and accessible interfaces to the simulation stack.
Run Massive-Scale UMAP in Minutes Using Multiple GPUs—Without Losing Accuracy | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·3d ago
Uniform Manifold Approximation and Projection (UMAP) is a dimensionality reduction technique widely used for visualization and feature extraction.
Developing Nemotron 3.5 Lightning NVFP4 with QAD Using NVIDIA Model Optimizer | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·4d ago
Teams customize their models to hit their targets for latency, speed, memory, and compute. With the open NVIDIA Nemotron family of models, developers can find the right-sized model for their needs.
Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72 | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·9d ago
Alibaba released the open weights for Qwen3.8-2.4T-A95B (Qwen3.8-Max), its largest open-weight model, bringing near-frontier capabilities to the open ecosystem.
How to Choose Full-Stack Observability for NVIDIA AI Factories | NVIDIA Technical Blog
Nvidia Developer Blogby Jorge Cardoso·9d ago
AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications.
NVIDIA JetPack 7.2.1 Adds Agentic Video Skills and T3000 Emulation | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·10d ago
Video is a core data path across NVIDIA Jetson applications, from robotics and intelligent video analytics to industrial automation, healthcare, media processing, and remote operations.
NVIDIA Nemotron 3.5 Lightning Delivers Fast, Accurate Specialized Task Execution for Long-Running Agents | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·10d ago
Long-running AI agents spend most of their time on high-volume execution: tool calls, result validation, and subagent delegation.
Route AI Agents Across Models with NVIDIA NeMo Switchyard | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·10d ago
Building an AI agent does not end with choosing a single model. Each model has its own strengths, weaknesses, and cost profile, which can shift from one workload to another—or even within the same...
Run Local Agentic AI Workflows with Meta’s Muse Glimmer on NVIDIA | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·11d ago
Meta returns to the open source ecosystem with the release of Muse Glimmer, a 30B open-weight dense model with a 120K+ context window built for local AI agentic work.
Beyond VLAs: How World Action Models Reshape Robot Manipulation | NVIDIA Technical Blog
Nvidia Developer Blogby Michelle Horton·17d ago
A central challenge in robotics is building policies that generalize beyond the demonstrations they’re trained on.
Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 Super | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·17d ago
Autonomous vehicle (AV) development often relies on separate models for trajectory generation, high-level intent prediction, scene understanding, and data labeling.
NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·18d ago
Storage is an active part of every agentic AI workflow. As agents retrieve enterprise knowledge, access persistent memory, reuse key-value (KV) cache data, execute tools, and generate new results...
How to Run Isolated Tenant Kubernetes Clusters on Shared GPU Infrastructure | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·18d ago
Running a dedicated Kubernetes cluster per team often results in more isolation than an organization requires.
Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference | NVIDIA Technical Blog
Nvidia Developer Blogby Tanya Lenz·20d ago
As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1).
NVIDIA Video Codec SDK 13.1: Zero-Copy Transcode, AV1 B-Frames, and Frame-Accurate Seek | NVIDIA Technical Blog
Nvidia Developer Blogby Elizabeth Goodman·21d ago
The demand for high-quality video continues to accelerate across industries, powering everything from immersive streaming experiences to remote collaboration, generative AI media tools, and...
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