内容来源：https://techcrunch.com/2025/08/29/cracks-are-forming-in-metas-partnership-with-scale-ai/

内容总结：

【Meta巨额投资Scale AI后合作初现裂痕，AI超级实验室陷动荡】
今年6月，Meta宣布向数据供应商Scale AI投资143亿美元，并邀请其CEO亚历山德·王（Alexandr Wang）及多名高管共同运营Meta超级智能实验室（MSL）。然而，双方合作短期内已显露紧张态势。

Scale AI前高级副总裁鲁本·梅耶（Ruben Mayer）加入Meta仅两个月便离职，暴露出管理团队整合难题。据悉，梅耶未被纳入核心研发团队TBD Labs，该团队正与Scale的竞争对手Mercor和Surge合作开发新一代AI模型。多名消息人士透露，尽管Meta对Scale投入巨资，但TBD Labs的研究人员认为其数据质量不足，更倾向使用其他供应商。

Scale AI以众包低成本的简单数据标注起家，但当前AI技术需依赖医学、法律等领域的专家数据。尽管其推出Outlier平台吸引专业人才，但Surge等竞争对手凭借高薪专家模式快速扩张。Meta发言人否认Scale存在数据质量问题，但OpenAI和谷歌已终止与Scale的合作。Scale随后裁员200人，转而聚焦政府业务，近期获美国陆军9900万美元合同。

业内猜测，Meta投资Scale实为招揽CEO王及其团队。然而，MSL内部管理混乱，新引进的OpenAI研究人员与Meta原有团队存在文化冲突，多名核心成员近期离职。Meta四月发布Llama 4表现未达预期，CEO扎克伯格急于追赶OpenAI和谷歌，加速推进人才招募与合作，但实验室领导层人选一度难产，多名顶尖AI学者拒绝加盟。

目前MSL已启动下一代AI模型研发，目标年底发布。然而，团队稳定性与数据战略争议为Meta的AI雄心蒙上阴影。

中文翻译：

直到今年六月，Meta才向数据供应商Scale AI投资了143亿美元，并邀请其首席执行官Alexandr Wang及多位初创公司高管共同运营Meta超级智能实验室（MSL）。但如今两家公司的合作关系已初现裂痕。

据两位知情人士向TechCrunch透露，Wang为协助运营MSL而带来的高管团队中，至少有Scale AI前生成式AI产品与运营高级副总裁Ruben Mayer在入职仅两个月后便离开了Meta。Mayer在Scale AI的两段任职经历累计约五年时间。在Meta短暂任职期间，他负责管理AI数据运营团队并向Wang汇报，但未被选入公司核心部门TBD实验室——该部门致力于构建AI超级智能，并吸纳了来自OpenAI的顶尖AI研究人员。Mayer未回应TechCrunch两次置评请求。

另据五位知情人士透露，TBD实验室正在与Scale AI之外的其他第三方数据供应商合作训练新一代AI模型。这些第三方供应商包括Scale AI两大竞争对手Mercor和Surge。虽然AI实验室通常与多家数据供应商合作（Meta在TBD实验室成立前就与Mercor和Surge有合作），但如此重金押注单一供应商实属罕见。多位消息人士表示，尽管Meta投资了数十亿美元，TBD实验室的研究人员仍认为Scale AI数据质量低下，更倾向于与Surge和Mercor合作。

Scale AI最初通过众包模式建立业务，利用低成本劳动力处理简单数据标注任务。但随着AI模型日益复杂，如今需要医生、律师、科学家等专业领域专家来生成和优化高质量数据。尽管Scale AI通过Outlier平台吸引领域专家，但Surge和Mercor等竞争对手因从一开始就建立在高薪人才基础上而快速成长。

Meta发言人否认Scale AI存在产品质量问题。Surge和Mercor拒绝置评。针对Meta日益依赖竞争数据供应商的质疑，Scale AI发言人仅向TechCrunch转发了Meta投资公告，其中提及双方商业关系的扩展。Meta与第三方数据供应商的合作表明，即便投资数十亿美元，该公司也未将全部希望寄托于Scale AI。但Scale AI则不然——在Meta宣布投资后不久，OpenAI和谷歌便终止了与该公司的合作。

失去这些客户后，Scale AI于七月裁撤了数据标注业务的200名员工，新任CEO Jason Droege将原因部分归咎于"市场需求变化"。该公司正加强政府销售等业务部门——刚与美国陆军签下9900万美元合同。有观点认为，Meta投资Scale AI实为招揽Wang（这位自2016年创立Scale AI起就活跃于AI领域的创始人正协助Meta吸引顶尖AI人才）。除Wang之外，Scale对Meta的实际价值仍存疑。

一位现任MSL员工透露，多位来自Scale的高管并未进入核心TBD实验室团队。此外，Meta的数据标注工作也非独家依赖Scale AI。两位前员工和一位现任员工表示，自Wang及大批顶尖研究人员加入后，Meta的AI部门日益混乱：来自OpenAI和Scale AI的新员工对大公司的官僚体系感到沮丧，而Meta原生成式AI团队的工作范围被缩小。

这些矛盾表明Meta迄今最大规模的AI投资可能起步不顺，尽管其本应解决公司AI开发挑战。据一位现任和一位前员工透露，在四月Llama 4发布效果不佳后，CEO扎克伯格对AI团队感到不满。为扭转局面并追赶OpenAI和谷歌，扎克伯格急于达成交易并大举招募AI人才。

除Wang外，他还成功从OpenAI、Google DeepMind和Anthropic挖来顶尖研究人员。Meta还收购了Play AI和WaveForms AI等AI语音初创公司，并与AI图像生成初创公司Midjourney建立合作。为支持AI野心，Meta近期宣布在美国多地建设大型数据中心，其中规模最大的之一是耗资500亿美元、位于路易斯安那州的"Hyperion"数据中心（取名自希腊神话中太阳神之父）。

非AI研究员出身的Wang执掌AI实验室被认为有些非传统。据传扎克伯格曾与OpenAI首席研究官Mark Chen等更传统人选洽谈，并试图收购Ilya Sutskever和Mira Murati的初创公司，但均遭拒绝。《连线》杂志此前报道，部分从OpenAI新招的研究人员已离开Meta，而许多Meta原生生成式AI团队的老成员也因这些变动离职。

MSL AI研究员Rishabh Agarwal最新宣布离职，他在X平台上表示："扎克伯格和Wang关于构建超级智能团队的构想极具吸引力，但我最终选择遵循扎克伯格本人的建议：'在快速变化的世界中，最大的风险是不承担任何风险'。"生成式AI产品管理总监Chaya Nayak和研究工程师Rohan Varma近期也宣布离职。当前问题是Meta能否稳定其AI运营并保留未来成功所需的人才。

MSL已开始开发下一代AI模型。据《商业内幕》报道，其目标是在今年年底前发布。

英文来源：

It’s only been since June that Meta invested $14.3 billion in the data vendor Scale AI, bringing on CEO Alexandr Wang and several of the startup’s top executives to run Meta Superintelligence Labs (MSL). However, the relationship between the two companies is already showing signs of fraying.
At least one of the executives Wang brought over to help run MSL — Scale AI’s former Senior Vice President of GenAI Product and Operations, Ruben Mayer — has departed Meta after just two months with the company, two people familiar with the matter told TechCrunch.
Mayer spent roughly five years with Scale AI across two stints. In his short time at Meta, Mayer oversaw AI data operations teams and reported to Wang, but wasn’t tapped to join the company’s TBD labs — the core unit tasked with building AI superintelligence, where top AI researchers from OpenAI have landed.
Mayer did not respond to two separate requests for comment from TechCrunch.
Further, TBD Labs is working with third-party data vendors other than Scale AI to train its upcoming AI models, according to five people familiar with the matter. Those third-party vendors include Mercor and Surge, two of Scale AI’s largest competitors, the people said.
While AI labs commonly work with several data vendors – Meta has been working with Mercor and Surge since before TBD Labs was spun up – it’s rare for an AI lab to invest so heavily in one data vendor. That makes this situation especially notable: even with Meta’s multi-billion-dollar investment, several sources said that researchers in TBD Labs see Scale AI’s data as low quality and have expressed a preference to work with Surge and Mercor.
Scale AI initially built its business on a crowdsourcing model that used a large, low-cost workforce to handle simple data annotation tasks. But as AI models have grown more sophisticated, they now require highly-skilled domain experts—such as doctors, lawyers, and scientists—to generate and refine the high-quality data needed to improve their performance.
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Although Scale AI has moved to attract these subject matter experts with its Outlier platform, competitors like Surge and Mercor have been growing quickly because their business models were built on a foundation of high-paid talent from the outset.
A Meta spokesperson disputed the fact that there are quality issues with Scale AI’s product. Surge and Mercor declined to comment. Asked about Meta’s deepening reliance on competing data providers, a Scale AI spokesperson directed TechCrunch to its initial announcement of Meta’s investment in the startup, which cites an expansion of the companies’ commercial relationship.
Meta’s deals with third-party data vendors likely mean the company is not putting all its eggs in Scale AI, even after investing billions in the startup. The same can’t be said for Scale AI, however. Shortly after Meta announced its massive investment with Scale AI, OpenAI and Google said they would stop working with the data provider.
Shortly after losing those customers, Scale AI laid off 200 employees in its data labeling business in July, with the company’s new CEO, Jason Droege, blaming the changes in part on “shifts in market demand.” Droege said Scale AI would staff up in other parts of the business, including government sales — the company just landed a $99 million contract with the U.S. Army.
Some speculated initially that Meta’s investment in Scale AI was really to lure Wang, a founder who has operated in the AI space since Scale AI was founded in 2016 and who appears to be helping Meta to attract top AI talent.
Aside from Wang, there’s an open question around how valuable Scale is to Meta.
One current MSL employee says that several of the Scale executives brought over to Meta are not working on the core TBD Labs team, as with Mayer. Further, Meta isn’t exclusively relying on Scale AI for data labeling work.
Meanwhile, Meta’s AI unit has become increasingly chaotic since bringing on Wang and a wave of top researchers, according to two former employees and one current MSL employee. New talent from OpenAI and Scale AI have expressed frustration with navigating the bureaucracy of a big company, while Meta’s previous GenAI team has seen its scope limited, they said.
The tensions indicate that Meta’s largest AI investment to date may be off to a rocky start, despite that it was supposed to address the company’s AI development challenges. After the lackluster launch of Llama 4 in April, Meta CEO Mark Zuckerberg grew frustrated with the company’s AI team, one current and one former employee told TechCrunch.
In an effort to turn things around and catch up with OpenAI and Google, Zuckerberg rushed to strike deals and launched an aggressive campaign to recruit top AI talent.
Beyond Wang, Zuckerberg has managed to pull in top AI researchers from OpenAI, Google DeepMind, and Anthropic. Meta has also acquired AI voice startups including Play AI and WaveForms AI, and announced a partnership with the AI image generation startup, Midjourney.
To power its AI ambitions, Meta recently announced several massive data center buildouts across the U.S. One of the largest is a $50 billion data center in Louisiana called Hyperion, named after a titan in Greek mythology that fathered the God of Sun.
Wang, who’s not an AI researcher by background, was viewed as a somewhat unconventional choice to lead an AI lab. Zuckerberg reportedly held talks to bring in more traditional candidates to lead the effort, such as OpenAI’s chief research officer, Mark Chen, and tried to acquire the startups of Ilya Sutskever and Mira Murati. All of them declined.
Some of the new AI researchers recently brought in from OpenAI have already left Meta, Wired previously reported. Meanwhile, many longtime members of Meta’s GenAI unit have departed in light of the changes.
MSL AI researcher Rishabh Agarwal is among the latest, posting on X this week that he’d be leaving the company.
“The pitch from Mark and @alexandr_wang to build in the Superintelligence team was incredibly compelling,” said Agarwal. “But I ultimately choose to follow Mark’s own advice: ‘In a world that’s changing so fast, the biggest risk you can take is not taking any risk’.”
Asked afterward about his time at Meta and what drove his decision to leave, Agarwal declined to comment.
Director of product management for generative AI, Chaya Nayak, and research engineer, Rohan Varma, have also announced their departure from Meta in recent weeks. The question now is whether Meta can stabilize its AI operations and retain the talent it needs for its future success.
MSL has already started working on its next generation AI model. According to reports from Business Insider, it’s aiming to launch it by the end of this year.