据英国《金融时报》报道，由于计算能力的限制，谷歌限制了 Meta 对其 Gemini AI 模型的访问。这一限制对 Meta 产生了重大影响，迫使该公司指导员工更有效地使用 AI 代币。 Meta 还将工作负载从 Gemini 转移到自己的 Muse Spark 模型，以减少对外部人工智能提供商的依赖。
Meta had initially depended on Gemini for tasks such as content moderation and safety processes, owing to its superior performance compared to Meta’s Llama open-source models. With the capped access to Gemini, Meta is accelerating its transition to Muse Spark, which it launched under its Superintelligence Labs division.这些调整表明 Meta 正在努力开发基本工作负载的内部替代方案。
In response to growing demand for Gemini Enterprise, Google has paid SpaceX $920 million per month for access to 110,000 Nvidia GPUs, referred to as “bridge capacity.”这种合作伙伴关系凸显了正在重塑科技行业关系的计算短缺。 Despite owning a significant amount of AI infrastructure and projecting over $180 billion in capital expenditures for 2023, Google still cannot meet all client demands and is rationing access to its models.
Meta previously cut 8,000 jobs to focus on AI initiatives and has since reassigned 7,000 employees to roles concentrating on artificial intelligence. The restrictions on Gemini have pushed Meta to enhance its internal capabilities at a crucial time when demand for AI computing resources outpaces available infrastructure. Other companies, such as Anthropic, are similarly seeking resources from SpaceX to support their operations, highlighting a broader issue of supply constraints in the AI sector.
The current landscape reflects a significant bottleneck in the AI boom, where the growth in demand for computational power is outpacing infrastructure developments. This trend illustrates that the limitations faced by major companies in accessing AI models are not merely a result of algorithmic challenges, but stem from the physical infrastructure needed to support increasing consumption.
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