Core Insights - The global multimodal large model industry has evolved through distinct phases, from early exploration (1956-2005) to rapid growth (2006-2019), the rise of large models (2020-2022), and now into a phase of widespread application starting in 2023 [1] Market Size and Growth - The global AI hardware market, particularly for servers, is projected to grow from $19.5 billion in 2022 to $34.7 billion by 2026, with a compound annual growth rate (CAGR) of 17.3% [3][4] - The market for servers specifically used for generative AI is expected to increase its share from 11.9% in 2023 to 31.7% by 2026 [4] Computational Demand - The demand for computational power in AI is increasing, with models like ChatGPT requiring significant resources; for instance, the GPT-3 model needs 1,750 billion parameters and consumes 3,640 PF-days of computational power [5] - A tenfold increase in model parameters can lead to more than a tenfold increase in computational requirements, influenced by model architecture and hardware capabilities [5] Large Model Market Dynamics - The global large model market is experiencing rapid growth, with an estimated size of $21 billion in 2023 and a projected increase to $28 billion in 2024, reflecting a year-on-year growth of 33% [7] Competitive Landscape - According to the SuperCLUE benchmark report, GPT-4o leads the global model rankings with a score of 81, while six Chinese models have surpassed GPT-4-Turbo-0409, indicating a strong competitive presence in the market [10]

Core Viewpoint - The article discusses the evolution of artificial intelligence (AI) from its inception to the current era of large models, highlighting key milestones, technological advancements, and the impact on various industries. Group 1: Birth of Artificial Intelligence (Mid-20th Century) - In 1950, Alan Turing proposed the "Turing Test," defining the philosophical goal of AI [3] - The term "Artificial Intelligence" was first used in 1956 at Dartmouth College, marking the transition from philosophical speculation to applied technology [3] - Early AI systems, like the IBM701, had limited computational power, executing only 16,000 operations per second, which is significantly less than modern devices [3] Group 2: Symbolism and Its Failures (1960-1970) - The 1960s saw the rise of "symbolism," where researchers attempted to simulate human reasoning through rule-based expert systems [4] - The MYCIN system developed in 1976 achieved near-expert accuracy in diagnosing blood infections, demonstrating the commercial value of expert systems [4][5] - The "Fifth Generation Computer Systems" project in Japan, launched in 1982 with an investment of $850 million, aimed to create intelligent computers but ultimately failed due to over-reliance on symbolic methods and hardware limitations [8] Group 3: Rise of Machine Learning (1990s-2000s) - The 1990s marked a shift to machine learning, moving from rule-based systems to data-driven approaches, allowing machines to learn from data rather than relying solely on hard-coded rules [10] - IBM's DeepBlue defeated a chess champion in 1997, showcasing the potential of machine learning in closed tasks [12] - The introduction of Google's PageRank algorithm in 1998 demonstrated the commercial value of data correlation, transforming search engines into profitable ventures [12] Group 4: Deep Learning Revolution (2010s-2020) - The 21st century saw the emergence of deep learning, enabling AI to automatically extract features through multi-layer neural networks [13] - AlphaGo's victory over a world champion in 2016 highlighted the capabilities of deep reinforcement learning [13] - The rapid increase in model parameters from 60,000 in LeNet-5 to 600 million in AlexNet illustrated the exponential growth in AI's capacity to handle complex tasks [14] Group 5: Era of Large Models (2021-Present) - The introduction of large pre-trained models like GPT-3 in 2020 has propelled AI towards general intelligence, showcasing advanced language understanding and generation capabilities [15] - Applications of generative AI have expanded across various fields, including content creation, programming assistance, and image generation, significantly enhancing productivity [16] - The competition between open-source and closed-source models has intensified, with companies like HuggingFace promoting open-source development while others like OpenAI focus on proprietary advancements [17] Group 6: Future Directions and Challenges - The future of AI is expected to focus on specialized models for high-value sectors such as healthcare and finance, emphasizing efficiency and cost-effectiveness [38] - The relationship between AI and human employees is anticipated to evolve into deeper integration, enhancing decision-making and innovation within organizations [38] - Ethical challenges and societal risks associated with AI, such as job displacement and privacy concerns, remain critical issues that need addressing [39]

云从科技集团股份有限公司监事会 关于公司 2025 年限制性股票激励计划首次授予 激励对象名单的核查意见（截至首次授予日） 云从科技集团股份有限公司（以下简称"公司"）监事会依据《中华人民共 和国公司法》（以下简称"《公司法》"）、《中华人民共和国证券法》（以下 简称"《证券法》"）、《上市公司股权激励管理办法》（以下简称"《管理办 法》"）、《上海证券交易所科创板股票上市规则》（以下简称"《上市规则》"）、 《科创板上市公司自律监管指南第 4 号——股权激励信息披露》等相关法律、法 规、规章和规范性文件以及《云从科技集团股份有限公司章程》（以下简称"《公 司章程》"）的有关规定，对公司 2025 年限制性股票激励计划（以下简称"激 励计划"）首次授予激励对象名单（截至首次授予日）进行了核查，发表核查意 见如下： 1、公司本次激励计划首次授予的激励对象均不存在《管理办法》第八条规 定的不得成为激励对象的情形： （2）最近 12 个月内被中国证监会及其派出机构认定为不适当人选； （3）最近 12 个月内因重大违法违规行为被中国证监会及其派出机构行政 处罚或者采取市场禁入措施； （4）具有《公司法》规定的不得担任 ...

①上述任何一名激励对象通过全部在有效期内的股权激励计划获授的本公司股票均未超过公司总股本的 1%。公司全部有效期内的激励计划所涉及的标的股票总数累计不超过股权激励计划提交股东大会审议时公 司股本总额的 20%。 ②本计划激励对象不包括独立董事、监事、单独或合计持有上市公司 5%以上股份的股东、上市公司实际控 制人及其配偶、父母、子女。 ③上述首次授予激励对象中有 6 人同时作为第一类激励对象和第二类激励对象。 云从科技集团股份有限公司 2025 年限制性股票激励计划首次授予激励对象名单 （截至首次授予日） 一、 限制性股票激励计划的分配情况表 | 序 | | | | 获授的限制性 | 占本激励计划 | 占本次首次授 | | --- | --- | --- | --- | --- | --- | --- | | 号 | 姓名 职务 | 国籍 | | 股票数量 | 首次授予总量 | 予公告时股本 | | | | | | （万股） | 的比例 | 总额的比例 | | | | | | 第一类激励对象 | | | | 1 | 游 | 中国 | 董事 | 14.00 | 3.50% | 0.0135% | | | 宇 | ...

证券代码：688327 证券简称：云从科技 公告编号：2025-016 云从科技集团股份有限公司 关于向激励对象首次授予限制性股票的公告 本公司董事会及全体董事保证公告内容不存在任何虚假记载、误导性陈述或 者重大遗漏，并对其内容的真实性、准确性和完整性依法承担法律责任。 重要内容提示： 限制性股票首次授予日：2025 年 4 月 8 日 限制性股票首次授予数量：400.00 万股，约占目前公司股本总额 103,854.8520 万股的 0.3852% 股权激励方式：第二类限制性股票 《云从科技集团股份有限公司 2025 年限制性股票激励计划（草案）》（以 下简称"《激励计划》"）规定的公司 2025 年限制性股票激励计划（以下简称 "激励计划"）的首次授予条件已经成就，根据云从科技集团股份有限公司（以 下简称"公司"）2025 年第一次临时股东大会的授权，公司于 2025 年 4 月 8 日 召开第二届董事会第二十六次会议、第二届监事会第二十二次会议，审议通过了 《关于向激励对象首次授予限制性股票的议案》，确定公司本次激励计划的首次 授予日为 2025 年 4 月 8 日，以 6.58 元/股的授予价格向 7 ...

证券代码：688327 证券简称：云从科技 公告编号：2025-019 云从科技集团股份有限公司 关于调整 2025 年限制性股票激励计划 首次授予相关事项的公告 本公司董事会及全体董事保证公告内容不存在任何虚假记载、误导性陈述或 者重大遗漏，并对其内容的真实性、准确性和完整性依法承担法律责任。 云从科技集团股份有限公司（以下简称"公司"）于 2025 年 4 月 8 日召开 第二届董事会第二十六次会议、第二届监事会第二十二次会议，审议通过了《关 于调整 2025 年限制性股票激励计划首次授予相关事项的议案》，根据《上市公 司股权激励管理办法》（以下简称"《管理办法》"）等法律法规、规范性文件 和公司《2025 年限制性股票激励计划（草案）》（以下简称"《激励计划》" 或"激励计划"）的规定及公司 2025 年第一次临时股东大会的授权，公司董事 会对本次激励计划首次授予相关事项进行调整。现对有关事项公告如下： 一、本次激励计划授予已履行的决策程序和信息披露情况 1、2025 年 1 月 9 日，公司召开第二届董事会第二十五次会议，审议通过了 《关于公司<2025 年限制性股票激励计划（草案）>及其摘要的议案》 ...

北京国枫律师事务所 关于云从科技集团股份有限公司 2025 年限制性股票激励计划调整暨首次授予事项的 法律意见书 国枫律证字[2025]AN005-2号 GRANDWAY 北京国枫律师事务所 Grandway Law Offices 电话(Tel): 010－88004488/66090088 传真(Fax): 010—66090016 北京国枫律师事务所 关于云从科技集团股份有限公司 2025 年限制性股票激励计划调整暨首次授予事项的 法律意见书 国枫律证字[2025]AN005-2号 致: 云从科技集团股份有限公司 根据北京国枫律师事务所(以下简称"本所")与云从科技集团股份有限公司 (以下简称"云从科技"或"公司"）签署的《律师服务协议书》，本所作为云从 科技集团股份有限公司 2025 年限制性股票激励计划(以下简称"本次激励计划") 的特聘专项法律顾问,已出具了《北京国枫律师事务所关于云从科技集团股份有限 公司 2025 年限制性股票激励计划(草案)的法律意见书》（以下简称"《法律意见 书》"）。 根据《公司法》《证券法》《管理办法》《自律监管指南》等有关法律、法规、 规章及规范性文件以及《公司章程》 ...

证券代码：688327 证券简称：云从科技 公告编号：2025-018 云从科技集团股份有限公司 第二届监事会第二十二次会议决议公告 本公司监事会及全体监事保证公告内容不存在任何虚假记载、误导性陈述或 者重大遗漏，并对其内容的真实性、准确性和完整性依法承担法律责任。 一、监事会会议召开情况 云从科技集团股份有限公司（以下简称"公司"）第二届监事会第二十二次 会议于 2025 年 4 月 8 日在上海市浦东新区川和路 55 弄张江人工智能岛 11 号楼 4 楼会议室以现场会议与通讯表决相结合的方式召开，本次会议通知及相关材料 已于 2025 年 4 月 3 日以电子邮件方式送达公司全体监事。 本次会议由监事会主席刘君先生主持，会议应出席监事 3 人，实际出席监事 3 人（其中监事周哲斯先生以通讯表决方式出席）。本次会议的召集、召开和表 决程序符合《中华人民共和国公司法》（简称"《公司法》"）等法律、法规以 及《云从科技集团股份有限公司章程》（简称"《公司章程》"）的有关规定。 二、监事会会议审议情况 经与会监事表决，审议通过以下议案： 1、《关于调整 2025 年限制性股票激励计划首次授予相关事项的议案》 公司 ...

Group 1 - The A-share market opened lower on March 28, with the Sci-Tech Innovation Board Artificial Intelligence ETF (588930) showing a fluctuating trend, up 0.41% with a premium rate of 0.02% [1] - The ETF tracks the Shanghai Stock Exchange Sci-Tech Innovation Board Artificial Intelligence Index (950180.CSI), which selects 30 large-cap stocks involved in providing foundational resources, technology, and application support for artificial intelligence [1] - Recent measures from the Ministry of Commerce aim to promote the application of technologies like artificial intelligence in the consumer sector, indicating a government push towards "AI + consumption" scenarios [1] Group 2 - According to Industrial Securities, the domestic AI industry chain has seen significant catalysts since the 2025 Spring Festival, leading to a vibrant market narrative and potential new highs [2] - The narrative around the AI industry is becoming clearer, with benefits observed across the entire industry chain, from upstream to downstream, and accelerating towards various application scenarios [2]