Group 1 - The Inclusion Bund Conference on September 11, 2025, focused on commercialization as a primary concern for AI entrepreneurs, scholars, and investors [1][3] - Zhu Xiaohu, a partner at Jinsha River Venture Capital, advised entrepreneurs to prioritize stable technologies over cutting-edge ones for commercialization [1][3] - User retention is emphasized as the key metric for evaluating AI applications, rather than annual recurring revenue (ARR) [3][16] Group 2 - Zhu Xiaohu identified that low-code and no-code AI applications are likely to be replaced by AI, leading to a decrease in demand for collaborative tools like Figma [10][15] - The need for smaller, efficient organizations in AI companies was highlighted, with a focus on maintaining high "intelligence density" [5][29] - Wang Xingxing, CEO of Yushu Technology, noted that the AI field is still in its early stages, with significant growth potential yet to be realized [24][29] Group 3 - Wang Jian, founder of Alibaba Cloud, stressed the importance of open resources (data and computing resources) over just open-source code for advancing AI applications [42][50] - The shift from open-source code to open resources is seen as a revolutionary change in the AI landscape, particularly following recent developments in model training and deployment [43][49] - The conference participants agreed that the AI era allows small teams to achieve significant outcomes, challenging traditional notions of team size and efficiency [29][40]

齐鲁晚报·齐鲁壹点 王赟 讲话的结尾，赫拉利说，"在人工智能时代，我们必须留给人类足够的时间来保存记忆，建立彼此之间 的信任与感情，衡量进步，不在于技术的速度，而在于我们之间合作的力度和共情的深度"。 这让笔者想起，开幕式"破局与重构：大模型落地产业进行时"产业圆桌中，金沙江创投主管合伙人朱啸 虎从投资的视角分享了一些关键判断。在朱啸虎看来，衡量AI创业公司是否值得投资，其中一个指标 就是用户的留存情况，"进入AI时代，很多人都愿意尝鲜，但是用户有没有留存决定了公司后续的发展 潜力。" "更容易商业化的项目，它的技术可能不是那么'性感'，看上去还比较无聊。"朱啸虎还提到，真正适合 商业化的AI创业项目往往具有技术稳定的特点，这类产品技术难度不大，但商业化容易，因此备受期 待。 朱啸虎强调，追求商业化时不必盲目跟随最新、最潮的技术，而应选择那些相对稳定、成熟的技 术方向。 2025 Inclusion·外滩大会的开幕式暨主论坛最后一个嘉宾是《人类简史》作者尤瓦尔·赫拉利，他的演讲 是线上的，屏幕里的他穿着粉色衬衫，背景里，书橱、窗户和窗外的绿色以及窗下的暖气片，置身这样 的场景里，他就像坐在你对面和你聊天，"作 ...

Core Viewpoint - The article discusses the latest advancements and discussions in AI technology, highlighting key insights from industry leaders at the Inclusion Bund Conference, emphasizing the transition to an "experience era" in AI development and the importance of open-source strategies in AI competition [6][10][20]. Group 1: AI Development Insights - Richard Sutton, the Turing Award winner, states that the human data dividend is nearing its limit, and AI is entering an "experience era" focused on continuous learning, which will unlock greater potential [9][10][19]. - Sutton emphasizes the need for new data sources generated through direct interaction between intelligent agents and the world, moving beyond static knowledge transfer [12][14]. - The concept of "experience" in AI involves the exchange of observation, action, and reward signals, which is crucial for developing intelligence [16][17]. Group 2: Open Source and AI Competition - Wang Jian, founder of Alibaba Cloud, highlights that the choice between open-source and closed-source models has become a critical variable in AI competition, especially after the U.S. imposed export controls on closed-source models [20][25]. - He discusses the evolution of open-source from code sharing to resource sharing, which now includes data, computing power, and model weights, significantly lowering the barriers to entry in AI development [26][30]. - Wang Jian's recent project involves deploying a complete AI model into space, showcasing the potential of collaborative resource sharing in advancing AI capabilities [31][35]. Group 3: Future of AI Applications - Yuval Noah Harari, a historian and philosopher, warns that the pace of technological change should not overshadow the need for understanding and governance, emphasizing that true progress is measured by cooperation and empathy rather than speed [60][67][70]. - Zhu Xiaohu from Sinovation Ventures predicts a significant explosion in AI applications next year, particularly in low-code and no-code software, and encourages entrepreneurs to seize opportunities in the AI space [54][57]. - Wang Xingxing from Yushutech believes that the integration of AI and robotics is on the verge of a breakthrough, enabling robots to perform tasks autonomously, although challenges remain in data quality and model alignment [46][50].

Core Insights - The shift from code open-source to resource open-source is a revolutionary change in the AI era, with open data and computing resources being essential for advancing AI [1] - The choice between open-source and closed-source models has become a critical variable in AI competition, highlighting the importance of resource openness [1] - The concept of open-source has evolved to encompass resource openness, which is a significant characteristic of the AI era [1] Group 1 - The launch of 12 satellites by Zhijiang Laboratory marks the first time an 8 billion parameter model has been sent to space, enabling data processing anywhere in space [2] - The project, named "Trinity Computing Constellation," aims to allow numerous entities to share and utilize the satellites, laying the groundwork for future deep space exploration [2] - AI and computing power are deemed essential for human exploration beyond Earth, particularly in missions to Mars over the next decade or two [2]

Group 1: AI and Innovation - The 2025 Inclusion·Bund Conference in Shanghai focused on "Reshaping Innovation Growth," featuring discussions on AI as a key theme, with over 40 forums and a significant technology exhibition [1] - Richard Sutton, the 2024 Turing Award winner, emphasized that humanity is entering a new "Era of Experience," where AI's replacement is inevitable, and the data era is nearing its end [3][4] - Sutton highlighted that the core of intelligence lies in experience, which involves observation, action, and reward, and pointed out the need for continual learning and meta-learning technologies to unlock AI's full potential [3] Group 2: Industry Perspectives - Wang Jian, founder of Alibaba Cloud, stated that open data and computing resources are essential for advancing AI, marking a shift from code open-sourcing to resource sharing [5][6] - Wang also introduced the concept of "computing satellites," which will leverage AI in space exploration, indicating a new frontier for AI applications beyond traditional devices [6] - Wang Xingxing, CEO of Yushu Technology, expressed optimism about the AI era, noting that small organizations will increasingly have explosive growth potential, despite existing challenges in data quality and model algorithms [7][8] Group 3: Organizational Challenges - McKinsey's China Chairman, Li Yili, identified organizational culture as the biggest bottleneck in AI development, advocating for CEO-led transformations focused on profitability rather than just application scenarios [8][9] - Li outlined three stages of globalization for Chinese enterprises, emphasizing the need for a global perspective and diverse collaboration models to enhance growth opportunities [10] Group 4: Energy and AI - Professor Sun Xuan from the University of Science and Technology of China proposed that nuclear fusion is the key to meeting the energy demands of AI, with 1 gram of fusion fuel equating to the energy of 8 tons of oil [11][12] - Sun highlighted the significant energy gap that AI could create, predicting that AI's energy consumption could exceed 20% of the Earth's total energy supply in the future [11] - The fusion industry is seeing increased investment, with a total of $7.1 billion raised globally, indicating a growing interest in commercializing fusion technology [12]

Core Insights - The 2025 Bund Conference gathered 550 guests from 16 countries to discuss the future of AI, featuring prominent figures like Turing Award winner Richard Sutton and Alibaba Cloud founder Wang Jian [1][2] Group 1: AI Development Perspectives - Richard Sutton emphasized that AI is entering an "experience era," where continuous learning will unlock unprecedented potential, countering fears of AI leading to bias or job loss as exaggerated [1][2] - Wang Jian highlighted the shift from open-source code to open-resource models as a revolutionary change in AI, asserting that the choice between open and closed models is a key variable in AI competition [4] - Zhang Hongjiang noted that AI is driving large-scale infrastructure expansion, with significant capital expenditures expected in the AI sector, projecting over $300 billion in AI-related capital spending by major U.S. tech companies by 2025 [6] Group 2: AI in Healthcare - Han Xinyi from Ant Group stated that AI will not replace doctors but will enhance their capabilities, allowing specialists to focus on complex cases while providing support to general practitioners [9] - He identified three core challenges in AI healthcare implementation: high-quality data, mitigating hallucinations, and addressing medical ethics [9] Group 3: Challenges and Opportunities in AI - Wang Xingxing from Yushutech expressed optimism about the potential for innovation in AI, despite current challenges in embodied intelligence and data quality [10][11] - He noted that the barriers to entry for innovation have significantly lowered, creating a favorable environment for young entrepreneurs to leverage AI tools for new ideas [11]

Core Insights - The 2025 Inclusion Bund Conference highlighted a revolutionary shift in AI from code open-sourcing to resource open-sourcing, emphasizing that open data and computing resources are essential for AI advancement [1][4] - Wang Jian, founder of Alibaba Cloud, noted that the choice between open-source and closed-source models has become a critical variable in AI competition [3][4] Group 1: Open Source vs Closed Source - The concept of open-source, which originated in the software era, is now pivotal in AI competition, with significant models previously concentrated in a few leading U.S. companies [3] - Wang Jian compared the current AI landscape to the 1998 emergence of the open-source browser Netscape, marking a watershed moment in the internet era [4] Group 2: Importance of Resources - The scale of data, models, and computing power has dramatically increased, leading to profound changes in AI capabilities [4] - The essence of model weight openness is fundamentally about the openness of data resources and computing resources, reducing the need for extensive computational resources for tasks already completed by others [4] Group 3: Space and AI - Wang Jian proposed the concept of "computing satellites" as a fourth type of satellite, emphasizing that AI should extend beyond traditional applications to include space exploration [4] - The launch of 12 satellites by Zhijiang Laboratory, equipped with an 8 billion parameter model, represents a significant advancement in processing data in space [5] Group 4: Future of AI and Space Exploration - The "Three-Body Computing Constellation" project aims to share satellite resources globally, laying the groundwork for future deep space exploration [5] - Wang Jian emphasized that AI and computing will be crucial companions for humanity's journey to Mars over the next decade or two [5]

来源：环球网 人工智能正在经历从数据驱动向体验驱动的范式转变。2024年图灵奖得主理查德·萨顿提出了"经验时 代"的概念，标志着AI发展进入新阶段。他认为，人类数据红利正逼近极限，人工智能需要从与世界的 直接交互中生成新的知识源，这正是人类和其他动物的学习方式。 图：理查德·萨顿在2025外滩大会开幕式主论坛发表主旨演讲 规模定律仍然主导着AI发展轨迹。美国国家工程院外籍院士张宏江指出，大模型的"规模定律"仍然有 效，而推理模型的出现塑造了大规模发展的新曲线——"推理规模定律"。上下文、记忆等层面对计算的 需求持续推升着算力扩张。 基础设施扩张支撑AI产业化进程。张宏江列举了OpenAI的Stargate和Musk的Colossus等项目，2025年美 国主要科技公司的AI相关资本开支预计超3000亿美元，整个AI数据中心产业链正经历大规模建设热 潮。 智能体经济正在形成。人类正在进入"智能体群"时代，数量庞大的智能体之间彼此交互、执行任务、交 换数据和信息，甚至交换任务。人类与这些智能体群的交互，将构成全新的"智能体经济"。 【环球网科技报道 记者 李文瑶】9月11日，以"重塑创新增长"为主题的2025 I ...

Core Viewpoint - The article emphasizes the transformative shift from "code open source" to "resource open source" in the AI industry, highlighting that by 2025, open sourcing will be a critical variable in AI competition [2][5][11]. Group 1: Open Source Evolution - The transition from code open source to resource open source is described as a revolutionary change, with the importance of resource sharing becoming more pronounced in the AI era [4][11]. - The open sourcing of models like Tongyi Qianwen and DeepSeek has caused significant industry disruption, with notable figures like Sam Altman acknowledging the historical implications of this shift [5][11]. - The concept of "open resource" is positioned as essential for advancing the AI industry, as it allows individuals to leverage existing models without incurring the costs of retraining [11][12]. Group 2: AI and Space Exploration - The launch of the "Three-Body Computing Constellation" satellites marks a significant milestone in integrating AI with space exploration, enabling data processing directly in space [3][13]. - The long-term vision includes making each satellite accessible globally, facilitating collaborative efforts in space exploration and addressing sustainable development challenges [15][16]. - The article posits that AI and computational resources must be sent into space for humanity to truly explore beyond Earth, particularly in missions to Mars and beyond [16][15].

公众号记得加星标⭐️，第一时间看推送不会错过。 Jim Keller 表示，Tenstorrent 正在建造一座特殊的电脑工厂，目标是生产所有现代高阶AI 电脑和高 性能处理器所需的零组件。一直以来，Tenstorrent 一直致力于打造高阶AI 电脑和具备大量IP 与技 术的高速CPU，如今产品已经开始出货，包括可扩展的Galaxy box 伺服器，以及为了回应客户抱怨 噪音而设计的水冷quiet box 等。此外，我们还推出了PCI Express卡，并刚开始向客户提供Eson TPU 作为IP。令人兴奋的是，还已经将AI 处理器出货给多家客户，其中包含LG，他们将AI 处理器 整合到电视芯片中。 于这些Tenstorrent 的成果，Jim Keller 强调自己是个任务导向的人，虽然长远来看也希望公司能够 赚 钱 。 但 更 重 要 的 是 要 有 一 个 使 命 ， 就 是 当 今 AI 世 界 正 在 彻 底 改 变 一 切 ， 随 处 都 可 见 对 「 千 兆 瓦」、「兆位元组」 产品的需求。但这一切都变得越来越大、越来越昂贵，而且很多技术是专有 的。尽管有些模型是开源的，但大部分仍然是封闭的 ...