How to Build a Voice Agent with RAG and Safety Guardrails | NVIDIA Technical Blog
Agentic AI / Generative AI How to Build a Voice Agent with RAG and Safety Guardrails Jan 05, 2026 By Chris Alexiuk and Isabel Hulseman Discuss (0) Discuss (0) L T F R…
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Why are SLMs beneficial to agentic AI tasks?
SLMs are well-positioned for the agentic era because they use a narrow slice of LLM functionality for any single language model errand. LLMs are built to be powerful generalists, but most agents use only a very narrow subset of their capabilities. They typically parse commands, generate structured outputs such as JSON for tool calls, or produce summaries and answer contextualized questions. These tasks are repetitive (up to the differences in prompt payloads), predictable, and highly specialized—well within the scope of specialized SLMs. An LLM trained to handle open-domain conversations is o
How Small Language Models Are Key to Scalable Agentic AI | NVIDIA Technical BlogTop stories
Build a Retrieval-Augmented Generation (RAG) Agent with NVIDIA Nemotron | NVIDIA Technical Blog
…Learn more Unlike traditional LLM-based systems that are limited by their training data, retrieval-augmented generation (RAG) improves text generation by incorporating relevant external information. Agentic RAG goes a step further…
How to Integrate Computer Vision Pipelines with Generative AI and Reasoning | NVIDIA Technical Blog
…New knowledge graph features and cross-camera support include multi-stream Q&A, improved knowledge graph generation, agentic-based graph traversal, Neo4J and ArangoDB with cuGraph acceleration. Unlock generative AI at the…
Building for the Rising Complexity of Agentic Systems with Extreme Co-Design | NVIDIA Technical Blog
…The faster these agents produce insights, the more exponentially valuable they become. This speed shortens R&D cycles, improves harness control, and enables complex multi-agent loops. Because the tokens enabling these…
NVIDIA Vera CPU Delivers High Performance, Bandwidth, and Efficiency for AI Factories | NVIDIA Technical Blog
…models to capture the best gradient tokens and accelerating training cycles. In agentic inference, it reduces users’ wait time, improving accelerator utilization and easing pressure on KV cache offloading. For frontier training…
Streaming Tokens and Tools: Multi-Turn Agentic Harness Support in NVIDIA Dynamo | NVIDIA Technical Blog
…Streaming tool calls as typed dispatch events rather than buffering until turn completion enables immediate tool execution and improved harness compatibility, enhancing responsiveness in agent workflows. AI-generated content may summarize information…
Optimize Supply Chain Decision Systems Using NVIDIA cuOpt Agent Skills | NVIDIA Technical Blog
…Skills serve as a packaging mechanism, dynamically loading the correct procedural context and improving agent performance on specific tasks. This post outlines core NVIDIA cuOpt agent skills , their significance, and how they…
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…
Mastering Agentic Techniques: AI Agent Evaluation | NVIDIA Technical Blog
…that improvements or vulnerabilities can be caught early. Get started evaluating AI agents Reliable agentic systems shift evaluation from static model benchmarks to dynamic, trajectory-aware metrics that reflect how agents behave…
Building Telco Reasoning Models for Autonomous Networks with NVIDIA NeMo | NVIDIA Technical Blog
…Multiturn tokenization simulates realistic interactions where the agent alternates between reasoning, calling tools, and interpreting tool responses, which is essential for deploying a ReAct-style NOC agent. The result is a curriculum…