Meta 发布 Muse Wonder 模型以支持智能体长任务
Meta Muse Wonder 面向智能体长任务
Meta 发布 Muse Wonder 模型，旨在优化智能体在长时程、多步骤工作中的表现。该模型引入 Active Memory 功能以实现跨对话的上下文携带与关联呈现，并配备 Active Focus 机制，确保模型在面对复杂任务时能持续推进目标、尝试替代方案并解决阻碍直至任务完成。
AI at Meta· @AIatMeta · X·2026-10-13 01:02· 49 分钟前AI 评分30
AI 导读
两点让 Muse Wonder 适合智能体每天面对的长时程、多步骤工作： -> Active Memory 跨对话携带你的上下文，并在相关时呈现出来。 -> Active Focus 在任务变得棘手时让模型持续朝你的目标推进，尝试替代方案，攻克阻碍，坚持到底直至完成。
正文
Two things make Muse Wonder suited for long-running, multi-step work an agent faces every day:
-> Active Memory carries your context across conversations and surfaces it when it's relevant.
-> Active Focus keeps the models working toward your goal when a task gets challenging, trying alternative approaches, working through blockers, and following through to completion.
来源：AI at Meta · x.com
来源：AIHot · aihot.news