Meta Platforms(US:META) 智通财经网·2025-06-11 03:46Core Insights - Meta's CEO Mark Zuckerberg is personally assembling an elite team to accelerate the development of Artificial General Intelligence (AGI) due to disappointment with the company's performance in the AI sector [1][2][3] - The new team, referred to internally as the "superintelligence group," aims to position Meta as a leader in AGI, integrating its capabilities across all Meta products [1][2] - Meta plans to make a multi-billion dollar investment in Scale AI, which will be the largest external investment in the company's history, potentially raising Scale AI's valuation to $28 billion [2][3] Group 1: Team Formation and Leadership - Zuckerberg is directly involved in recruiting approximately 50 experts for the new team, including a new AI research head, and has adjusted the office layout for closer collaboration [1][2] - He has adopted a "founder mode" management style, reflecting a hands-on approach to address dissatisfaction with Meta's latest AI models, particularly Llama 4 [2][3] - The establishment of a WhatsApp group named "Recruiting Party" among executives indicates a continuous discussion on talent acquisition [3] Group 2: Investment and Market Position - The investment in Scale AI is expected to enhance Meta's AI capabilities, with the founder of Scale AI likely joining the superintelligence group post-transaction [2][3] - Zuckerberg believes that Meta's strong cash flow from its advertising business allows for significant investments in AI, with planned capital expenditures reaching hundreds of billions [3] Group 3: Challenges and Internal Dynamics - Meta has delayed the release of its "Behemoth" model due to concerns about its limited improvements, reflecting internal pressures and performance expectations [3][4] - The company has faced criticism regarding the performance of its Llama models, with internal and external stakeholders questioning their effectiveness [4][5] - There is ongoing internal turmoil, with high-level departures attributed to a lack of focus on AGI's disruptive potential, as well as challenges from competitors in the AI space [5][6]