Core Insights - The collaboration between OpenAI and Oracle to develop an additional 4.5GW of data center capacity reflects a significant shift in the operational logic of the AI industry, moving towards a model where computing power is treated as a flexible service rather than a fixed asset [1][3][6] Group 1: Collaboration Details - OpenAI and Oracle's partnership is not merely a commercial agreement but represents a deep integration of technology and infrastructure services, allowing for enhanced power distribution and disaster recovery capabilities across multiple regions [4][13] - The collaboration enables OpenAI to reduce operational costs by leveraging Oracle's efficient data center infrastructure, which maintains a Power Usage Effectiveness (PUE) of below 1.2, significantly better than the industry average of 1.5 [5][6] Group 2: Computing Power Supply Model - The partnership signifies a paradigm shift in the computing power supply model, moving from reliance on self-built data centers to a more flexible, service-oriented approach, akin to the transition from private generators to public power grids [3][4] - The scale of operations, with the ability to run over 2 million chips, enhances both companies' influence in the semiconductor supply chain, challenging the dominance of Nvidia in the AI chip market [7][9] Group 3: Energy and Computing Synergy - The 4.5GW data center capacity requires substantial energy, equivalent to the annual electricity consumption of 3.15 million households, highlighting the need for efficient energy management in modern data centers [10] - Schneider Electric's report emphasizes the necessity for a dynamic synergy between energy supply and computing power, advocating for a holistic approach to energy management that integrates power supply, computing loads, and cooling systems [10][11] Group 4: Geopolitical Implications - The collaboration aligns with U.S. government initiatives to maintain leadership in advanced computing infrastructure, indicating that the partnership extends beyond commercial interests into national strategic considerations [13][15] - The intertwining of commercial cooperation and national strategy suggests a blurred line between public and private sectors in the context of AI infrastructure, as the U.S. seeks to consolidate computing resources for competitive advantage in the global AI landscape [15][16]

Core Viewpoint - The article highlights the launch of the free "Deep Research" feature by Metaso AI Search, which allows users to conduct comprehensive research without the need for applications or memberships, showcasing a new approach to AI-driven research capabilities [1][12][46]. Group 1: Features of Deep Research - The Deep Research function provides a complete research report by connecting various sub-questions and presenting a clear evidence chain [2][22]. - Users can input complex queries, and the system generates a research path in real-time, displaying the AI's thought process [18][19]. - The final report is structured and can be exported in formats like Word and PDF, with sources clearly cited [28][29]. Group 2: Performance and Evaluation - Metaso AI has shown superior performance in evaluation tests compared to other models, including the WebSailor model [8][10]. - The system can visualize data through charts and graphs, making it suitable for business research and everyday inquiries [39][41]. Group 3: Accessibility and Market Position - The Deep Research feature is available for free, contrasting with many competitors that require payment or limited access [48][50]. - This launch is seen as a significant development in the domestic AI search field, providing users with a low-barrier entry to advanced research tools [52].