What do you think multi-agent interaction is. I mean, if you take a really really high level view, multi- aent interaction is basically like essential for AGI, right. Um, we're all doing multi- aent interactions now, right. Um, we're all agents, right.So, you so in in in one sense like if you want agents to be close to this level of intelligence, they need to be able to handle multi-agent interactions, right. Um, but to be a go down bit more, you know, concrete, right. I think of it as like the you always h ...

Core Insights - Alibaba's CEO, Wu Yongming, asserts that AI will become the next generation operating system, with a focus on advancing towards Artificial Superintelligence (ASI) [1] - The market reacted positively to these statements, with Alibaba's stock rising over 6%, reaching its highest point since October 2021 [1] Group 1: AI Integration in Automotive Industry - Several automotive companies, including Li Auto, BYD, and NIO, have introduced AI agents into their smart cockpits, enabling features like voice-activated food ordering while driving [2] - The initial applications of these AI agents are relatively simple, focusing on navigation, food ordering, and ride-hailing, but the ultimate goal is to create a seamless "human-vehicle-life" interaction [2][3] - Li Auto's AI agent, "Li Xiang," aims to enhance its capabilities with environmental awareness and comprehensive memory, allowing for more complex interactions [2] Group 2: Technical Frameworks for AI Agents - Li Auto employs two frameworks for its AI agent: CUA (Cockpit Using Agent) and MCP/A2A (Multi-Channel Processing/Agent-to-Agent) [2][3] - CUA involves multi-modal large model understanding tasks and executing them through apps, while MCP/A2A allows the AI agent to delegate tasks to third-party agents for efficiency [3][4] - The accuracy of current AI agents in completing complex tasks is around 30%, indicating a need for improved predictive capabilities [3] Group 3: Future Developments in AI Capabilities - Li Auto's vision for its AI agent includes "full information memory," which encompasses user actions, environmental interactions, and semantic memory regarding relationships [5] - The AI agent is expected to not only remember user behaviors but also proactively assist by mimicking past actions, enhancing user experience [5] - Environmental perception is crucial for the AI agent, enabling it to recognize real-world cues and complete tasks autonomously [5][6] Group 4: Industry Perspectives on AI - Wu Yongming emphasizes that for AI to surpass human capabilities, it must continuously interact with the physical world to gather comprehensive data [6] - The advancement of autonomous driving technology is cited as an example of how AI learns from raw data to improve performance [6]

今天，在京东全球科技探索者大会（JDD）上，京东宣布，未来三年，将持续投入，带动形成万亿规模的人工智能生态。 这次大会，京东首次系统展示了AI全景布局，不仅升级"JoyAI"大模型品牌，还一口气发布三款C端产品、四大场景应用和三大深度平台，意图把供应链 优势延伸至用户端。 受此消息带动，京东集团港股股价盘中涨幅近7%。 9月25日，京东宣布：未来三年，将持续投入，带动形成万亿规模的人工智能生态 三款产品全面押注AI新交互 同时，京东正式推出行业首个"附身智能平台"JoyInside 2.0，强调全龄陪伴、拟人交互和言行一致三大能力，为机器人、AI玩具、智能眼镜等终端"装上大 脑"。目前已有超过30家硬件品牌接入，相关产品已上线京东。 JoyInside2.0已接入超30家品牌 即将上线的京犀App，被定位为"下一代购物与生活服务超级入口"，不只"听懂人话"，更理解商品，意图实现真正意义上的超个性化推荐。据透露，AI购 物、AI试衣等体验后续将从主站迁入这款独立App。 "他她它"App则搭载新版JoyAI大模型，内置一位什么都能聊的"万能博士"智能体，既能查天气、点外卖、聊财经，还可根据用户性格切换对话风格。 ...

Plaud 在招兵买马，疯狂招人。 他们去年赚了一亿多美金，今年能赚两亿多。 怎么理解这个数字的价值？如果你在国内融资，几乎不可能拿到比这更多的美元。 不过 Plaud 没那么需要融资，它是全世界最成功的 AI 硬件 Startup。约 150 美金的录音卡片，卖给了全球超过 100 万人，引来大厂效仿，甚至还有美国团 队跑来中国找供应商。 你不好奇吗？为什么？ 莫子皓是 Plaud 中国区 CEO，也是负责 AI 产品和研发的合伙人。加入之前，他「看到了真实的数据，一年增长四倍。这就是 PMF。」 硬件的销售带来的用户，稳定、真实、有粘性，还高净值。他们有真实的需求，用 Plaud 记录了密度和价值极高的信息，对他们个人至关重要的信息。所 有这些，用今天流行的话说，就是 context。 过去的东西任由行业 follow 和 copy，对 Plaud 来说，这些竞争来得太慢了，他们无瑕顾及。 我们更好奇的是，在 PMF 的助推下，在这丰沃的用户 context 土壤上，Plaud 可以做什么？他们「误打误撞」发现和解锁的下一个关卡，是什么？ 以下是我们与莫子皓的对话内容，经 Founder Park 编辑整 ...

1. 吴泳铭表示，将在3800亿元AI基础设施的建设上，追加更大的投入。 今年初，阿里巴巴港股的市值还只有1.5万亿港元左右，9个多月后，阿里巴巴不仅实现了市值翻倍，还创下了近4年的股价新高。 在阿里巴巴市值翻倍的这9个月里，每当"吴泳铭""AI""投资"三个关键词同时出现时，阿里的股价通常都会迎来一波大涨。 今年2月，吴泳铭宣布阿里将在未来三年投入至少3800亿元建设云和AI硬件基础设施，随后阿里股价在10个交易日内累计上涨超过35%；在Q2财报电话会 上，吴泳铭再一次重申阿里对AI投入的决心，配合二季度阿里云的超预期表现，阿里巴巴美股一夜上涨13.5%。 最近一次，则是在9月24日举办的2025云栖大会上，吴泳铭宣布未来计划追加更大的投入，阿里港股股价盘中大幅拉升，最终收涨9.16%，总市值来到3.32 万亿港元。 在两股情绪并存的市场上，计划投入3800亿，要做AI时代基础设施的阿里云为什么得到了更多的"支持票"？ 不确定的泡沫和确定的AGI 本月初，美国科技公司甲骨文发布截至8月的2026财年第一财季报告，财报显示，未实现履约义务（尚未确认的已签约收入）已经达到4550亿美元，同比 增长359%，并且 ...

题图来自：视觉中国 从AGI到ASI，阿里果然是造词担当。 阿里集团CEO、阿里云董事长吴泳铭在9月24日的阿里云栖大会上提出观点：实现通用人工智能AGI只 是起点，发展出能自我迭代、全面超越人类的超级人工智能ASI才是终极目标。 维特根斯坦说，语言的边界就是世界的边界。 跳出原有语言体系的表达，确实让人印象深刻，恍如新世界的大门就在眼前。 姚顺雨在今年4月发布的博客《The second Half》提到，AI下半场已经开始，"评估比训练更重要""通过 把智能转化为有用的产品，打造出数十亿甚至万亿美元的公司。" 这些参与"下半场"的创业公司，显然是各大云平台的潜在客户。阿里云需要尽可能多地把它们搞到手。 淘金者可能穷困潦倒，但卖铲子的人总能富得流油。 阿里云已经吃到甜头。根据2025年二季度财报，阿里云收入333.98亿元，同比增长26%，增速创三年新 高，其中AI收入已经占阿里云外部商业化收入超20%。 它的模式已经清晰。 吴泳铭在演讲中重点提到了"两个判断"（两个产品）： 1、大模型是下一代OS。通义千问开源300多款模型，做AI时代的andriod。 别管ASI是否会重蹈"新零售"的覆辙，反正股价已经信 ...

2025云栖大会首日，阿里巴巴集团CEO、阿里云智能集团董事长兼CEO吴泳铭发表主旨演讲。 商报讯（记者 吕文鹃）"AGI并非AI发展的终点，而是全新的起点。AI不会止步于AGI，它将迈向超越 人类智能、能够自我迭代进化的超级人工智能（ASI）。"在2025云栖大会开幕首日，阿里巴巴集团 CEO、阿里云智能集团董事长兼CEO吴泳铭发表主旨演讲，首次系统阐述了通往ASI的三阶段演进路 线。 AI行业发展的速度远超预期，行业对AI基础设施的需求同样也远超预期，当AI继续向前演进，一个全 新的ASI时代会是怎样的？那时的人类和AI又会是怎样的协作关系？在广大开发者的推动下，中国乃至 全球的云计算、AI和科技行业迎来了前所未有的发展浪潮，而一场由人工智能驱动的智能化革命才刚 刚开始。 "AGI并非终点" 吴泳铭阐述通往ASI的三阶段 从"学习人"到"辅助人"，最后再到"超越人"，吴泳铭将通往ASI的路分为三个阶段。在第一阶段，AI通 过学习海量人类知识具备泛化智能。过去几十年的互联网发展，为智能涌现提供了基础。在这些已构成 的基础之上，大模型首先通过理解全世界的知识集合，具备了泛化的智能能力，涌现出通用对话能力， 可 ...

[Music] I honestly believe that the AI revolution is underhyped. Now, why is this all important? >> Eric Schmidt is here. He's the former Google executive chairman and CEO. >> These agents are going to be really powerful, and they'll start to work together. We're soon going to be able to have computers running on their own, deciding what they want to do. Now we have the arrival of a new nonhuman intelligence which is likely to have better reasoning skills than humans can have. >> So if you were emperor of t ...

Core Viewpoint - The article discusses the recent talent shifts within Meta and the implications for its organizational structure and strategy in the AI sector, highlighting the challenges and opportunities faced by the company in the competitive landscape of AI development [4][6][21]. Group 1: Meta's Talent Acquisition and Loss - In June 2025, Meta acquired a 49% stake in Scale AI for $14.3 billion and recruited Alexander Wang, the 28-year-old founder of Scale AI, to lead the newly formed Meta Superintelligence Labs [4]. - Following the acquisition, Meta experienced a wave of talent departures, including long-term employees and new recruits returning to OpenAI, indicating dissatisfaction with the company's environment [4][8]. - The rapid turnover of talent is attributed to an increasingly bureaucratic structure and internal political struggles, which have made the work environment less appealing for top-tier AI talent [8][9]. Group 2: Organizational Structure and Culture - Meta's organizational structure has become more cumbersome, with an increase in VP levels leading to slower decision-making processes, which contrasts with the company's previously agile culture [8][9]. - The lack of clear ownership in model training and the presence of overlapping responsibilities among teams have created inefficiencies and internal competition, hindering productivity [10][11]. - The article suggests that a smaller, more focused team of 150 to 250 individuals would be more effective for achieving breakthroughs in AI models compared to a larger team of 5,000 [9][10]. Group 3: Comparison with Other AI Companies - Other AI companies like OpenAI and Anthropic have a more mission-driven approach, which helps align their teams towards common goals, reducing internal conflicts and enhancing productivity [12][21]. - Google employs a top-down approach with clear authority figures guiding research, which contrasts with Meta's bottom-up culture that can lead to disorganization [10][12]. - The article highlights that while Meta has a strong social network, its organizational inefficiencies may hinder its ability to compete effectively with companies like OpenAI and Anthropic, which are currently attracting top talent [23][24]. Group 4: Future of AI Organizations - The article discusses the potential for new organizational structures in AI startups, emphasizing the importance of decentralization and trust within teams to enhance efficiency [26][27]. - It suggests that AI can significantly improve organizational productivity, allowing for a shift away from traditional hierarchical structures towards more agile, networked teams [26][27]. - The future of talent competition in Silicon Valley is expected to cool down as market expectations are reassessed, impacting the recruitment of top AI talent [34][35].

Group 1 - Alibaba announces collaboration with Nvidia for Physical AI [1] - Alibaba officially launches its largest and most powerful model Qwen3-Max to date [2] - Alibaba's Wu Yongming states that AGI is just the starting point, with the ultimate goal being super artificial intelligence [3] Group 2 - The "Stargate" project will establish five AI data centers in the United States [4] - AMD announces expansion of global AI collaboration with AI startup Cohere [5] - SAP and OpenAI announce partnership to launch a "German version of OpenAI" [6] - Applied Materials collaborates with GlobalFoundries to advance AI and AR photonic technologies [7]