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麦肯锡 & Mozilla:2025 人工智能时代下的开源技术研究报告
欧米伽未来研究所2025· 2025-04-24 11:53
Core Viewpoint - Open-source AI is rapidly becoming a core component for enterprises to build AI capabilities, drive innovation, and seek competitive advantages, moving beyond being a supplementary option [3][17]. Group 1: Current State of Open-source AI - Open-source AI technology has penetrated various levels of the AI tech stack, with over half of respondents utilizing open-source in data, models, and tools [4][5]. - The adoption of open-source technology is uneven across different areas, with lower rates in model modification and hosting/inference computing [6]. - The most commonly used models are "partially open," reflecting the current market landscape where many well-known models have limitations on data transparency or usage licenses [7]. Group 2: Value Perception and Trade-offs - Cost-effectiveness is a significant driver for adopting open-source AI, with 60% of respondents believing implementation costs are lower than proprietary solutions [8]. - Performance and ease of use are also critical factors, with a majority of users satisfied with their open-source AI models [8][9]. - However, proprietary tools are perceived to deliver value more quickly, with 48% of respondents favoring them for faster returns [9]. Group 3: Future Outlook and Risk Management - There is a strong expectation for growth in open-source AI usage, with 75% of respondents anticipating increased adoption in the coming years [11]. - A hybrid approach combining open-source and proprietary technologies is likely to emerge, as over 70% of respondents are open to using both [12]. - Key risks associated with open-source AI include cybersecurity, regulatory compliance, and intellectual property issues, with 62% of respondents expressing concerns about cybersecurity [13][14]. Group 4: Community Contribution and Strategic Integration - Only 13% of respondents reported contributing to open-source projects, indicating a need for greater community engagement [16]. - Companies should integrate open-source AI into their core strategies, balancing the benefits of open-source with the need for risk management and community involvement [17][18].