Uploaded August 2026 | Updated September 2026, 3 weeks ago
-What goes into building an open model for long-running agents? In this Ask the Experts session, you'll get direct access to the NVIDIA AI researchers building and training the latest Nemotron open models. Join us to hear what's driving their design decisions: how these models are trained to handle specialized, high-volume agentic tasks, why Nemotron open models are built to run locally — on hardware like DGX Spark — without sacrificing accuracy or speed, and what it means to build an open model that fits into a system where different tasks call for different models.
We'll cover how the research team approaches training open models purpose-built for agentic work: fast, efficient, and designed to be customized for your domain. The conversation will dig into the architecture choices, training techniques, and design principles behind models built to run anywhere — from DGX Spark to the data center — and to slot cleanly alongside other models in a multi-model agent system.
What you'll learn:
- How NVIDIA AI researchers train open models for long-running, autonomous agents
What makes the Nemotron family customizable for domain- and task-specific workflows
- How Nemotron open models are optimized to run locally, from DGX Spark to your own infrastructure
- How Nemotron open models are built to work in systems where different steps call for different models
Have questions about open model training, agentic design choices, or running Nemotron locally? Drop them live — our researchers will answer them directly.
-What goes into building an open model for long-running agents? In this Ask the Experts session, you'll get direct access to the NVIDIA AI researchers building and training the latest Nemotron open models. Join us to hear what's driving their design decisions: how these models are trained to handle specialized, high-volume agentic tasks, why Nemotron open models are built to run locally — on hardware like DGX Spark — without sacrificing accuracy or speed, and what it means to build an open model that fits into a system where different tasks call for different models.
We'll cover how the research team approaches training open models purpose-built for agentic work: fast, efficient, and designed to be customized for your domain. The conversation will dig into the architecture choices, training techniques, and design principles behind models built to run anywhere — from DGX Spark to the data center — and to slot cleanly alongside other models in a multi-model agent system.
What you'll learn:
- How NVIDIA AI researchers train open models for long-running, autonomous agents
What makes the Nemotron family customizable for domain- and task-specific workflows
- How Nemotron open models are optimized to run locally, from DGX Spark to your own infrastructure
- How Nemotron open models are built to work in systems where different steps call for different models
Have questions about open model training, agentic design choices, or running Nemotron locally? Drop them live — our researchers will answer them directly.
