Meta 宣布把用 Muse Wonder 训练的专用模型接入 Muse 和 Meta AI,让用户在工作与日常任务中用上 Muse Wonder 的部分前沿能力。
官方给出 Active Memory 与 Active Focus 两项能力的具体量化变化,可据此判断长任务中记忆与纠偏的改进幅度。
Today we're bringing specialized models trained using Muse Wonder to @Muse and Meta AI, giving users access to some of Muse Wonder's frontier capabilities for complex tasks at work and in everyday life.
These specialized models include Muse Wonder's Active Memory and Active Focus, helping them stay aligned with your goals as tasks unfold:
→ Active Memory helps recognize when earlier information matters and distinguish what's still relevant from what's become stale
→ Active Focus helps recover from setbacks or find alternatives when constraints change
In Muse, the improved models show a 2.4x reduction in forgetting information critical to your goals and a 67% improvement in getting unstuck as constraints evolve. That means less repeating yourself and fewer dead ends when plans change.
In Meta AI, these improvements help it break complex problems into steps, ask sharper follow-up questions and adapt when you change direction.
Read more on our research blog: https://go.meta.me/4kCPcHW
来源:AI at Meta · x.com