Core Viewpoint - The article outlines the recruitment process and benefits for founders participating in the Founder Show, emphasizing the support and resources available for selected projects in the Gen AI sector. Group 1: Recruitment Requirements - The program is open to 9 new founders, including those who independently develop or own teams, with no restrictions on vertical scenarios and product forms [7] - A product demo is preferred for applicants, enhancing their chances of selection [7] Group 2: Recruitment Process - The application period runs from May 23 to June 10, with final notifications sent by June 13 [7] - The selection process includes initial document submission, online interviews, project review, and notification of acceptance [7][8] Group 3: Event Details - The event will take place on June 20, 2025, in Beijing at the 798·751 Park [7] - Each founder will have 20 minutes to present their product progress and entrepreneurial insights, followed by an interactive Q&A session with guests [7] Group 4: Benefits for Selected Founders - All projects passing the initial screening will receive a standard version of the "Entrepreneur Acceleration Resource Package" provided by Variable Capital [6] - Selected projects will also gain access to advanced support, including free model and computing power usage, product design, and growth guidance [10] - Additional benefits include exposure in the Founder Park community and investment opportunities through the AGI Founders Fund [10]

文章来源于「硅基流动」官方公众号 刚刚，硅基流动官方宣布已完成数亿元人民币 A 轮融资。此轮融资由阿里云领投，老股东创新工场 等机构超额跟投，华兴资本担任独家财务顾问。 硅基流动 创始人袁进辉表示， 「 在本轮融资帮助下，我们将继续加大研发投入，积极拓展海内外 市场，努力早日成为开发者首选的生成式 AI 开发平台。 」 邀请从业者、开发人员和创业者，飞书扫码加群： 硅基流动 成立于 2023 年 8 月， 2024 年底完成亿元 Pre-A 轮融资， Pre-A 轮 投后估值达到 2 亿美元。 进群后，你有机会得到： 以下为 「硅基流动」官方原文： 硅基流动已完成数亿元人民币 A 轮融资。本轮融资由阿里云领投，老股东创新工场等机构超额跟 投，华兴资本担任独家财务顾问。 硅基流动创始人袁进辉表示："作为深耕 AI 基础设施领域多年的专业选手，硅基流动通过持续的技 术突破和产品创新有效解决了国内 AI 行业发展的多个重大问题。今年以来，随着阿里巴巴通义千 问 Qwen、DeepSeek 等开源大模型崛起以及 AI 推理算力需求激增，公司业务迎来了爆发式增 长。感谢多方投资机构的信任与支持，在本轮融资帮助下，我们将 ...

Core Insights - Google has made significant strides in the AI competition, particularly with the launch of Gemini 2.5, positioning itself on par with OpenAI [1][4] - The future of Google Search is envisioned to integrate advanced AI models that will enhance user experience by providing valuable content through multi-path retrieval [4][13] - The company is currently in the AJI (Artificial Jagged Intelligence) phase, indicating notable progress but also existing limitations in AI capabilities [4][42] Group 1: AI Development and Integration - Google aims to deploy the strongest models in search, executing multi-path retrieval for each query to deliver valuable content [4][13] - Approximately 30% of code is generated with the assistance of AI prompts, leading to a 10% increase in overall engineering efficiency [32][34] - The company is focused on creating a seamless integration of AI into its products, with plans to migrate AI Mode to the main search page [4][18] Group 2: Search and Advertising Evolution - The traditional search interface is evolving, with AI becoming an auxiliary layer that provides context and summaries while still directing users to human-created content [14][19] - AI Mode is currently being tested by millions, showing promising early indicators of user engagement and satisfaction [15][18] - Future advertising strategies will be rethought to align with AI capabilities, ensuring that ads are presented in a natural and unobtrusive manner [16][17] Group 3: Challenges and Future Outlook - Scaling laws remain effective, but the company acknowledges limitations in computational power affecting model deployment [29][30] - The integration of AR (Augmented Reality) is seen as the next significant interaction paradigm, with Project Astra being crucial for the Android XR ecosystem [36][38] - The company anticipates that while AGI may not be achieved by 2030, significant advancements will occur across various dimensions of AI [42][44]

Core Viewpoint - The initial hype around AI hardware aiming to replace smartphones has diminished, with a shift towards specialized AI hardware that addresses specific needs rather than seeking to disrupt existing devices [2][4][6]. Group 1: Evolution of AI Hardware - The first generation of AI hardware, represented by products like AI Pin, has faced significant challenges, including high return rates and poor user reception, leading to a phase of "failure" in product experience and revenue [4][5]. - In contrast, a new wave of AI hardware is emerging, focusing on niche applications and vertical demands, achieving notable success by solving specific problems rather than attempting broad disruption [5][10]. Group 2: Characteristics of New AI Hardware - The second generation of AI hardware is characterized by a strong sense of "boundaries," focusing on excelling in specific scenarios rather than being all-encompassing [8][9]. - These products prioritize delivering tangible results and addressing real pain points, which necessitates high performance and reliability in specific functionalities [9][10]. Group 3: Interaction and User Experience - The interaction model of AI hardware differs significantly from traditional devices, emphasizing "weak interaction" where users engage through voice rather than touch, allowing AI to operate more like a virtual assistant [11][13]. - This shift in interaction means that users care more about the outcomes (e.g., comfort in their environment) rather than the mechanics of controlling devices [13][14]. Group 4: Emergence of a New Operating System - A new AI-centric operating system is emerging, which transcends specific hardware forms and integrates AI assistants as core components, facilitating seamless interaction across various devices [16][20]. - Major tech companies are actively developing this new layer of AI, which will operate above existing systems like Android and iOS, focusing on task understanding, resource scheduling, and cross-device collaboration [18][21]. Group 5: Future Directions and Opportunities - The AI hardware landscape is transitioning from creating perfect hardware to effectively integrating and utilizing the emerging "invisible OS" [26]. - The ongoing innovation in AI hardware is expected to enhance user experiences and unlock new commercial value across familiar scenarios and products [26].

Founder Park /AGI Playground 2025 动意以 Agenda 6.20 PM lec 特别单元 22822882 Founder Show x se np 新锐与成熟创业者的 28 深度探讨 30 6.21 AM 主题分享: Why Chapter 2 ? 6.21 PM Al 硬件 垂直 Agent 全球化 50 6.22 AM al Al Cloud 100 China x AGI Playground 6.22 PM 创业新范式 | 出海新方法 | After Party 6.21 22 PM 露天 Social Playground 喝点东西, 坐下唠! Founder Park /AGI Playground (2025 Buy Tickets Now 15 16 17 18 19 20 21 23 Founder Park Founder Park 2 % % 2 % % % /AGI Playground /AGI Plavaround /2025 '2025 /早鸟单日票 早的印度 /6月22日 /6月21日 31 32 33 x751 × 751 34 35 36 ...

另外一个重要功能就是 ChatGPT 正式支持 MCP 协议，例如，直接连接 Github 、 SharePoint 、 Gmail 、 Dropbox 、 Box 、 Outlook 等常用工具，实现跨平台数据整合、搜索和推理。 文章转载自「Datawhale」 今天凌晨 1 点， OpenAI开始 技术直播对 ChatGPT 进行了重大更新，包括向 macOS 用户推 出 ChatGPT 会议记录模式，可以转录任何会议、头脑风暴或语音笔记，并快速提取要点然后转 化为新的内容。 简单来说，OpenAI希望把ChatGPT打造成智能协作平台，在一个地方就把所有事情都做了。 超 6000 人的「AI 产品市集」社群！不错过每一款有价值的 AI 应用。 邀请从业者、开发人员和创业者，飞书扫码加群： 进群后，你有机会得到： 最新、最值得关注的 AI 新品资讯； 01 ChatGPT 支持 MCP 在如今数据爆炸时代，我们每天需要处理海量内容，从邮件、ERP、CRM、SharePoint等提取 不同的数据进行分析、总结需要耗费很多时间。 而ChatGPT通过支持MCP协议，可以将这些日常工具直接与大模型相连，帮助我们 ...

Core Viewpoint - In the AI era, taste is becoming a new scarce resource, as production is no longer limited. Companies must focus on creating products that convey a unique philosophy rather than just functionality [2][4]. Group 1: Importance of Taste - Taste is difficult to quantify and process, yet it is essential for creating products that resonate with users [2][3]. - Taste is not merely about aesthetics; it involves thousands of consistent decisions that create a compound effect [4][12]. - Top founders understand that taste is a competitive advantage that permeates design, code, corporate culture, and even equity structure [5][6]. Group 2: Challenges in Defining Taste - Many companies confuse taste with aesthetics, believing that hiring a design firm or choosing a nice font is sufficient [7]. - True taste requires sacrifices, such as rejecting features that could expand market size or spending time optimizing details that users may not notice [8][9]. Group 3: Taste and Rapid Iteration - Taste is not the opposite of speed; rather, it is a prerequisite for sustainable speed in product development [9][10]. - A clear understanding of what to build and why can reduce rework and speed up decision-making processes [11]. Group 4: The Compound Effect of Taste - Taste transforms chaos into clarity, allowing teams to navigate numerous small decisions intuitively [11]. - A product that feels well-considered leads users to trust its infrastructure, security, and future planning [12]. Group 5: Sales with Taste - Early sales hires should view sales as a craft, ensuring they understand the company's vision and can empathize with users [13][14]. - High-quality sales interactions teach potential customers how to understand the product, reinforcing the company's values [15]. Group 6: Scaling Taste - Scaling taste requires systematic approaches, starting with founder oversight on user-facing decisions to ensure consistency [18]. - Hiring talent that bridges vision and execution is crucial for maintaining taste [19]. Group 7: The Nature of Taste - Taste cannot be directly taught; it is developed through practice and experience [21]. - Founders can clarify their taste by explaining their choices and establishing shared quality standards [21]. Group 8: Limitations of Taste - Taste does not dominate all markets; companies can succeed even with less appealing designs if they solve urgent problems [23]. - Understanding the competitive environment is key; taste becomes critical when alternatives are available [23]. Group 9: Long-term Benefits of Taste - Taste resists commoditization as it integrates into a philosophy of decision-making [24]. - The rewards of taste are immediate and accumulate over time, leading to user forgiveness for missing features and attracting top talent [24][25].

以下文章来源于叶小钗 ，作者叶小钗 叶小钗 . 原为鹅厂、ctrip、baidu、一线开发，B站技术专家，某独角兽技术负责人，AI产品项目负责人，CEO数字分身负责人，产品数字CTO负责人 本文作者叶小钗是一位 「 AI + 管理 」 领域的创业者，在成为创业者之前，他曾在腾讯、百度等大厂任职开发工作，也曾是B站的技术专家。 与多数创业者相似， 叶小钗 因为对管理的热爱以及在实际工作中积累的管理经验，萌生了「 AI + 管理 」创业的想法。 不过，与以往的文章不同的是，这不是一篇创业成功的经验分享， 而是一份坦诚地创业失败实录。 从想要创业的涌动，到 创业实践中的自我审视与复盘，到最后理性退场， 叶小钗在这篇文章中完整且细腻地分享了他的心路变化。 超 6000 人的「AI 产品市集」社群！不错过每一款有价值的 AI 应用。 邀请从业者、开发人员和创业者，飞书扫码加群： 进群后，你有机会得到： 01 创业的小火苗 关于为什么要做管理领域的创业，简单来说可能是： 第一，我内心深处可能喜欢这个东西 。 因为我从小比较喜欢看历史纪录片，对于各种变法强国是发自内心的喜欢，比如 商鞅、王安石、张居正 ... 当时在我内心 ...

Core Viewpoint - The AI programming tool Windsurf is facing significant challenges due to a sudden reduction in service quotas for its Claude models by Anthropic, which has forced Windsurf to seek third-party inference services to maintain user experience [1][8][11]. Group 1: Windsurf's Response and Challenges - Windsurf expressed strong dissatisfaction with Anthropic's abrupt decision to cut off service resources, which they claim could negatively impact not only their company but the industry as a whole [5][11]. - The company is actively seeking additional resources from other model providers while emphasizing their commitment to maintaining access to Anthropic's models and their willingness to pay for service resources [9][10]. - Users may experience temporary resource shortages while Windsurf works to increase capacity, but the overall impact is deemed manageable [12]. Group 2: Competitive Landscape - The AI-assisted coding sector is becoming increasingly competitive, with Windsurf's annual recurring revenue (ARR) reaching $100 million in April, indicating rapid growth as it attempts to catch up with competitors like Cursor and GitHub Copilot [28]. - Windsurf's inability to access Anthropic's new models could hinder its growth momentum, especially as competitors like Cursor have already gained access to the latest Claude 4 model [29][13]. - Anthropic is prioritizing service resources for partners that ensure ongoing collaboration, which may further disadvantage Windsurf in the competitive landscape [26]. Group 3: Product Developments - Windsurf has launched its own large model series, SWE-1, in mid-August, which may provide an alternative for users during this transitional period [30]. - The introduction of Claude 4 has led some users, such as those focused on Apple's Swift programming language, to switch to Cursor for better collaboration capabilities [17].

Core Viewpoint - The article discusses the transformation of software development through the advent of large language models (LLMs), suggesting that the marginal cost of software creation will approach zero, similar to the impact of the internet on content production [3][6]. Group 1: Evolution of Software Development - The introduction of LLMs is predicted to lead to the dissolution of traditional software as a "container," shifting the focus from writing code to describing needs [10][15]. - The historical context is provided by comparing the launch of YouTube in 2005, which democratized content creation, to the current state where a simple prompt can generate software solutions [8][10]. - The article emphasizes that the process of software creation will become as accessible as content creation, allowing anyone to turn ideas into products with minimal effort [8][10]. Group 2: Cost and Trust Dynamics - As the cost of software generation decreases, trust will become a critical factor in determining which systems can effectively represent user needs [11][14]. - The article notes that traditional software companies may struggle as free distribution models gain dominance, similar to how print media faced challenges from digital platforms [11][12]. Group 3: The Future of Software - The ultimate conclusion is that the traditional notion of software will fade away, with functionality becoming ubiquitous and easily accessible, marking the "end of software" as a distinct entity [15][16]. - The article posits that as logic can be invoked and combined freely, the concept of software containers will become obsolete, leaving only the functions themselves [15][16].