NVIDIA Megatron Core
…It provides GPU-optimized building blocks for training and post-training workflows, so teams can build custom systems with the performance, flexibility, and scale required for modern LLM, MoE, and multimodal development…
Search
People also ask
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 BlogScale Synthetic Data and Physical AI Reasoning with NVIDIA Cosmos World Foundation Models | NVIDIA Technical Blog
…This post explores the latest Cosmos WFMs, their key capabilities that advance physical AI , and how to use them. Cosmos world foundation model updates: NVIDIA Cosmos world foundation models have continued to…
Make Sense of Video Analytics by Integrating NVIDIA AI Blueprints | NVIDIA Technical Blog
…Returned context is inserted into the enrichment prompt set in the tunable VECTOR_RAG_ENRICHMENT_PROMPT before LLM generation. The tunable enrichment prompt used in the nutritional example is pictured below. Here…
Speed Up Unreal Engine NNE Inference with NVIDIA TensorRT for RTX Runtime | NVIDIA Technical Blog
…TensorRT for RTX is only compatible with NVIDIA RTX GPUs, from the Turing generation (compute capability 7.5) up to the NVIDIA Blackwell generation (compute capability 10.0). Unreal Engine neural network…
NVIDIA NVbandwidth: Your Essential Tool for Measuring GPU Interconnect and Memory Performance | NVIDIA Technical Blog
…While modern GPUs boast impressive compute capabilities, their performance is frequently limited by how quickly data can be moved between different devices: CPU memory to GPU memory GPU memory to CPU memory…
Add a Specialized Deep Research Skill to Agent Harnesses | NVIDIA Technical Blog
…Once installed, the agent harness sees a single deep research capability. Phrases like “research the regulatory landscape for X across our internal policy docs and produce a memo” route through the skill…
Transform Video Into Instantly Searchable, Actionable Intelligence with AI Agents and Skills | NVIDIA Technical Blog
…It uses accelerated vision-based microservices, vision-language models (VLMs) , large language models (LLMs) , and retrievers for real-time video intelligence, agentic search, and automated reporting. VSS helps enterprises monitor operations, detect…
MiniMax M2.7 Advances Scalable Agentic Workflows on NVIDIA Platforms for Complex AI Applications | NVIDIA Technical Blog
…The MiniMax M2 series is a sparse mixture-of-experts (MoE) model family designed for efficiency and capability. The MoE design keeps inference costs low while preserving the full capacity of a…
How Justt Scaled Chargeback Extraction with Nemotron Parse
…Architecture overview and data flow Extraction pipeline Nemotron Parse is integrated into the extraction pipeline, replacing previous OCR-based solutions and extending visual extraction capabilities to handle complex document structures such as…
Practical Security Guidance for Sandboxing Agentic Workflows and Managing Execution Risk | NVIDIA Technical Blog
…Such malicious instructions to the LLM can result in it taking attacker-influenced actions with adverse consequences. Manual approval of actions performed by the agent is the most common way to manage…