<![CDATA[NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents]]>This post did not contain any content.
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NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents | NVIDIA Technical Blog

A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives context…

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NVIDIA Technical Blog (developer.nvidia.com)
]]>https://citiverse.it/topic/5e65af8e-4e65-4e90-acca-72876a23f280/nvidia-avo-reaches-100-on-arc-agi-3-demonstrating-a-frontier-level-general-purpose-architecture-for-long-horizon-autonomous-agentsRSS for NodeSun, 23 Aug 2026 16:27:18 GMTFri, 21 Aug 2026 19:30:45 GMT60<![CDATA[Reply to NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents on Fri, 21 Aug 2026 19:30:59 GMT]]>This is further illustration that raw model capability isn’t really the most interesting thing at this point. The model and the harness should be viewed as a single system. I expect that we’ll be moving towards neurosymbolic systems where LLMs act as a heuristic engine within the boundaries of a symbolic logic system.

]]>https://citiverse.it/post/https://lemmy.ml/comment/27376008https://citiverse.it/post/https://lemmy.ml/comment/27376008Fri, 21 Aug 2026 19:30:59 GMT