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Muse Wonder 让 Meta 重回人工智能前沿Muse Wonder Puts Meta Back at the AI Frontier

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当马克·扎克伯格去年重启公司的人工智能业务时,这似乎是一项非常昂贵的赌注。Meta最新的人工智能模型Muse Wonder和Muse Wonder Full似乎表明,这项赌注终于开始回报,使公司重新站在人工智能发展的前沿。

When Mark Zuckerberg rebooted his company’s artificial intelligence efforts last year, it seemed to be a very expensive gamble. Meta’s latest AI models, Muse Wonder and Muse Wonder Full, seem to show that the bet is finally paying off by putting the company back at the frontier of AI development.

Meta表示,Muse Wonder Full具备前沿能力,这意味着它是世界上最强大的人工智能模型之一。公司今天在一篇博客文章中表示:“它们共同标志着我们扩展阶梯上的下一步,也是迈向个人超级智能的重大飞跃。”

Muse Wonder Full boasts frontier capabilities, Meta says, meaning that it is among the most capable AI models in the world. “Together, they mark the next step on our scaling ladder and a major leap toward personal superintelligence,” the company said in a blog post today.

Muse Wonder模型将通过API以及通过Muse Code提供服务,Muse Code是一种用于编写人工智能软件的工具。Meta表示,该模型的最佳版本将为其平台上的功能提供支持,包括其Muse个人代理。

The Muse Wonder models will be available though an API and through Muse Code, a tool for writing software with AI. Meta says the best version of the model will power features across its platforms, including its Muse personal agent.

去年,扎克伯格通过向最近成立的Meta超智能实验室投入数十亿美元,并聘请前Scale AI首席执行官亚历山大·王来领导该实验室,彻底改革了公司的人工智能研究。这一过程有时也十分艰难,一些研究人员并未长期留任。

Zuckerberg overhauled his company’s AI research last year by sinking billions into the recently formed Meta Superintelligence Labs, and hiring the former Scale AI CEO Alexandr Wang to lead it. This effort has sometimes been rocky, with some researchers not sticking around for long.

Meta曾一度是人工智能领域的先驱。其Llama系列模型是首个来自大型实验室的前沿开放权重模型。Llama可以下载并在个人硬件上运行,被研究人员和初创公司广泛采用。

Meta was once a trailblazer in AI. Its Llama series of models were the first frontier open-weight offerings from a big lab. Llama, which could be downloaded and run on one’s own hardware, was widely adopted by researchers and startups.

但该公司在推出几个令人失望的模型版本后落后于人,而Anthropic、OpenAI和谷歌则迅速推出了更强大的模型。

But the company fell behind after delivering several disappointing versions of the model, and as Anthropic, OpenAI, and Google rapidly introduced more capable models.

Meta今年4月宣布了其新实验室的首个模型Muse Spark。公司还发布了一个名为Muse Glimmer的小型开放权重模型,并表示计划在未来发布更大的开放权重模型。Meta未透露新Muse Wonder模型的构建或训练细节。

Meta announced the first model from its new lab, Muse Spark, in April of this year. The company has also released a small open weight model called Muse Glimmer, and says it plans to release larger open-weight models in the future. It did not disclose details of how new Muse Wonder models were built or trained.

Muse Wonder 然而是为与最顶尖模型竞争而构建的。Meta 表示,该新模型的最大版本在 Artificial Analysis Intelligence Index(一种广泛使用的模型能力综合评分)上超越了 Anthropic 的第二强模型 Claude Fable 5.1,并仅次于其最强模型 Claude Opus 5.5。

Muse Wonder was built to compete with the very best, however. Meta says the largest version of the new model outperforms Anthropic’s second-best model, Claude Fable 5.1, and ranks just below its best, Claude Opus 5.5, on the Artificial Analysis Intelligence Index, a widely used aggregated score of model capabilities.

Meta 表示,该模型在某些专项基准测试中超越了 OpenAI 的最强模型 GPT-6 Astra,以及 Claude Fable 5.1 和 Claude Opus 5.5,这些测试包括衡量模型处理法律文档和构建软件能力的项目。基准测试并不总是真实世界表现的可靠衡量标准,但这仍然是 Meta 模型的一个重大进步。

Meta says the model outperforms OpenAI’s best model, GPT-6 Astra, and both Claude Fable 5.1 and Claude Opus 5.5 on some specialized benchmarks, including ones that measure a model’s ability to work with legal documents and to build software. Benchmarks are not always a reliable measure of real-world performance, but this is still a significant step forward for Meta’s models.

Muse Wonder 还包含两项新功能,旨在帮助智能体更有效、更不易出现异常行为。这两项名为“主动记忆”(Active Memory)和“主动聚焦”(Active Focus)的新功能,旨在让模型锁定既定目标,防止其陷入混淆。例如,当 AI 执行复杂研究或构建大型软件项目时,这可能是一个挑战,并可能导致昂贵的错误或累积错误。

Muse Wonder also includes two novel features designed to help make agents more effective and less inclined to misbehave. The new features, called Active Memory and Active Focus, are designed to keep the model locked into a stated goal, and prevent it from becoming confused. This can be a challenge when AI performs complex research or builds a large software project, for example, and can lead to expensive mistakes or compounded errors.

Meta 表示,公司投入了大量精力训练 Muse Wonder 拒绝生成危险输出,例如制造生物武器的配方或协助黑客攻击。Meta 称,公司在多项旨在衡量模型对此类提示词抵御能力的基准测试中得分优异。

Meta says it has put significant effort into training Muse Wonder to refuse to generate dangerous outputs, such as recipes for building bioweapons or help with hacking. It says the company scores well on several benchmarks designed to measure how resilient models are to those prompts.

一系列近期涉及 Anthropic、OpenAI 等公司失控 AI 智能体的事件也表明,当被赋予开放式指令时,强大的 AI 模型有多么容易偏离轨道。Meta 未披露其在测试中是否观察到由 Muse Wonder 驱动的智能体出现异常行为,或具体采取了何种措施来缓解这一问题。

A series of recent incidents involving rogue AI agents from Anthropic, OpenAI, and others, also shows how easily powerful AI models can stray when given open-ended commands. Meta did not disclose whether it has seen agents powered by Muse Wonder misbehave in testing or what it has done to mitigate this issue specifically.

扎克伯格上个月在 X 上发帖表示,公司推迟发布其 Muse 模型,以便开展安全工作。Meta 还在本月初的一篇博客文章中公布了一个框架,旨在确保其安全地扩展模型能力。

Zuckerberg said in a post on X last month that the company had delayed the release of its Muse models to work on safety. Meta also revealed a framework designed to ensure that it scales its models’ capabilities safely in a blog post earlier this month.

然而,Muse Wonder 可能会为开发更强大 AI 的白热化竞争火上浇油。这无疑表明,Meta 在赌注日益增高的 AI 竞赛中再次具备了竞争力。

Muse Wonder may add more fuel to an already furious race to develop more capable AI, however. It certainly suggests that Meta is once again competitive in the increasingly high-stakes AI race.