Meta 推出用 Muse Wonder 训练的专项模型,接入 Muse 和 Meta AI,包含 Active Memory 和 Active Focus 两项能力。在 Muse 中,关键信息遗忘减少 2.4x,约束变化时摆脱卡壳的改善为 67%;Meta AI 则能更好地拆解复杂问题、提出更精准的追问并适应用户改变方向。
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