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NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents

21 August 2026 at 13:00
A frontier language model is only one component of an AI agent. The surrounding agent systemβ€”often called a harnessβ€”determines how the model receives...

A frontier language model is only one component of an AI agent. The surrounding agent systemβ€”often called a harnessβ€”determines how the model receives context, uses tools, maintains state, responds to feedback, recovers from failure, and sustains progress over long-running tasks. The challenge is how to build the agent architecture that makes frontier language models work reliably on extended…

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Where Security Fits in an AI Agent Stack

21 August 2026 at 13:00
As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important....

As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important. Drawing on work with NVIDIA OpenShell, agent developers, open-source projects, and partners across the ecosystem, AI safety and security teams at NVIDIA offer their perspective on the emerging agent stackβ€”including the role of each layer…

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Pretrained to Imagine, Fine-Tuned to Act: The Rise of World-Action Models

15 June 2026 at 12:00
Quick glossary for readers new to VLA/WAM terminology VLA Vision-Language-Action model: a robot policy that starts from a pretrained VLM backbone and adapts it...

Quick glossary for readers new to VLA/WAM terminology VLA Vision-Language-Action model: a robot policy that starts from a pretrained VLM backbone and adapts it to generate actions from visual observations and language instructions. Large-scale VLM pretraining is a core part of the recipe. See Pi-0 and GR00T N1. WAM World-Action Model: a policy that starts from a pretrained world-model or video…

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Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron

By: Hao Wu
22 April 2026 at 20:01
Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved...

Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved significant success more recently when applied to leading LLMs. In particular, Muon (MomentUm Orthogonalized by Newton-Schulz) was used to train some of today’s best open source models, including Kimi K2 and GLM-5.

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