Core Viewpoint - Sequoia China has launched a new AI benchmark tool called xbench, marking the first benchmark released by an investment institution since the rise of AGI following ChatGPT's introduction in 2022, adding a new topic to the AI discourse [1][2][8]. Group 1: Background and Development - Over the past two years, AI benchmarks have become common tools for evaluating foundational models and AI agents, with numerous testing systems developed by universities, research institutions, and AI companies [2]. - Sequoia China's xbench originated from internal evaluations of AGI progress and mainstream models, revealing that mainstream models were quickly exhausting test questions, leading to a rapid decrease in the effectiveness of benchmark tests [3][4]. Group 2: xbench Features - xbench employs a dual-track evaluation system, constructing a multidimensional assessment dataset while tracking the theoretical limits of models and the practical value of agents [5]. - The system innovatively divides assessment tasks into two complementary main lines: evaluating the capability limits and technical boundaries of AI systems, and quantifying their utility value in real-world scenarios [5][6]. - The evergreen evaluation mechanism ensures continuous maintenance and dynamic updates of test content, allowing for timely and relevant assessments [5][6]. Group 3: Significance and Impact - The introduction of xbench is significant not just as a benchmark tool but also due to its unique characteristics and Sequoia China's industry position, potentially surpassing the impact of ordinary benchmarks [8]. - The emergence of xbench is likened to the iPhone moment for AI, suggesting that it could serve as a foundational element for the AGI era, similar to how smartphones laid the groundwork for the mobile internet [10][12]. Group 4: Market Fit and Development Stages - The report outlines three stages of technology-market fit (TMF) in the agent field, from initial non-viability to collaborative work with humans, and finally to specialized agents guided by domain experts [12]. - The transition from stage one to stage two is driven by breakthroughs in AI technology and the expansion of computational power and data, while the move from stage two to stage three relies on familiar vertical demands and expert knowledge [12]. Group 5: Community Engagement and Future Directions - Sequoia China calls for community collaboration, inviting foundational model and agent developers to utilize the latest xbench evaluation set for product validation [14][15]. - The initiative aims to establish a high-density talent community that seeks to explore and push the limits of AI technology while identifying commercialization opportunities [15].