François Chollet · @fchollet · X·2026-08-22 00:26·4天前
AI 导读

François Chollet 称赞 NVIDIA 的 AVO 系统在 ARC-AGI-3 上表现优异,认为其采用深度学习引导的符号世界模型实时合成路径。但他明确指出,在公开演示集上拿 100% 不等于在 ARC-AGI-3 基准上拿 100%,如同通关教程不等于通关游戏。AVO 通过记忆、工具与执行反馈实现长时程任务持续进展。

François Chollet@fchollet
39AI 编辑部评分,满分 100
2026-08-22 00:26· 4天前
AI 导读

François Chollet 称赞 NVIDIA 的 AVO 系统在 ARC-AGI-3 上表现优异,认为其采用深度学习引导的符号世界模型实时合成路径。但他明确指出,在公开演示集上拿 100% 不等于在 ARC-AGI-3 基准上拿 100%,如同通关教程不等于通关游戏。AVO 通过记忆、工具与执行反馈实现长时程任务持续进展。

This is very nice work from NVIDIA. Like all high-performing approaches on ARC-AGI-3, it uses deep learning-guided on-the-fly synthesis of symbolic world models, i.e. navigating the world by generating programs to represent what you know.

To be clear, like with several other recent claims, scoring 100% on the public demonstration set is not the same as "scoring 100% on the ARC-AGI-3 benchmark". It would be like saying you beat a videogame because you cleared the tutorial level.

NVIDIA AINVIDIA AVO continuously inspects, plans, implements, and evaluates, using memory, tools, and execution feedback to build on what it learns along the way. This a...

来源:François Chollet· x.com