Meta Platforms(US:META) Hua Er Jie Jian Wen·2025-07-15 02:53Core Insights - Meta is undergoing an unprecedented strategic transformation to catch up in the foundational model race, with CEO Mark Zuckerberg announcing a multi-billion dollar investment in large data centers, starting with the Prometheus center expected to be operational next year [1] - The company is adopting a new "tent-style" data center design for faster construction and is secretly building two "gigawatt" (GW) supercomputing clusters in Ohio and Louisiana, named Prometheus and Hyperion, respectively [1][2] - The aggressive shift is a response to the failure of Meta's Llama 4 model, which damaged its reputation after the success of Llama 3 [3] Infrastructure Development - Meta has abandoned its previous decade-long data center construction blueprint to prioritize rapid deployment of massive computing power [2] - The new "tent-style" structure utilizes prefabricated power and cooling modules, sacrificing some redundancy to expedite GPU cluster deployment [2] - The Prometheus cluster in Ohio aims to integrate various power sources and is building two 200-megawatt onsite natural gas power plants to address local grid limitations [3][4] Technical Challenges - The Llama 4 model faced technical issues, including a flawed "chunked attention" mechanism that impaired long-range reasoning capabilities [4] - The team struggled with data quality, transitioning from public datasets to an internal web crawler without adequate preparation, limiting its multimodal capabilities [4][5] - The Llama 4 team encountered difficulties in scaling research experiments and lacked strong leadership to unify the technical direction [5] Talent Acquisition and Strategic Investments - To bridge the talent gap with top AI labs, Meta is focusing on recruiting for a new "superintelligence" team, offering compensation packages up to $200 million over four years [6] - Strategic acquisitions, such as the investment in Scale AI, are aimed at addressing the shortcomings exposed by Llama 4, particularly in data and evaluation capabilities [6]