a16z 今天发布了其第 5 版的 Top 100 GenAI Consumer Apps 榜单，又有一些新面孔加入，其中印象最深的是移动端 Top 50 里接近一半的产品是中国团 队开发的。 移动端新增的 14 个新产品里，像 PixVerse、AirBrush、Wink 以及 Gauth 也都来自中国。 其中 PixVerse 我最早在 2023 年有过介绍，创始团队来自字节，当时他们产品刚上线 2 个多月时间，其 ARR 收入就快 250 万美金了《 不到 1 月 100 万 美金 ARR，国人团队正在用 AI 掘金 Global 市场 》，这篇文章里介绍的另外两个产品，也成为当下中国出海最典型的代表。 | 3 . | | Al Gallery | 25. | PixVerse | 42. | MINI | 49 | AirBrush | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 17. | | Wink | 34. | 0 BeautyCam | 43. | Peachy | 50 . | Pl@ntNet | | 22. | ...

Koji 想把这些 moments 分享给 所有希望在 AI 时代积极行动的人 、 希望借助 AI 创业的人 和 成熟企业 家与管理者 。 他，曾是王兴身边的产品经理 ，和一群有梦想的青年 一起 点燃 了 中国移动互联网的 创业 火种。 他， 是连续创业者， 十多年 来 ，跨越互联网、新媒体、消费品多个周期 。 如今 ， 他 全情 拥抱 AI 。 他就是 新世相 、 街旁网 、 躺岛联合创始人 ， AI Hacker House 发起人 ， 「十字路口」 创始人 ， Koji 杨远骋 。 过去大半年， Koji 做了两件事： 和上百位最前沿的 AI 创业者 进行了 深度对谈 ， 拆解体验每一个刷屏 的 AI 产品 。 以及在上海漕河泾与来自硅谷的Aligns AI 构建了一座 AI Hacker House ，为 AI 时代的创 业者提供一个交流的社区。 上周六， Koji 来混沌分享了他在 「十字路口」 播客中，与 AI 创业者深度对谈中的 15 个 aha moments ，混沌君从中选了 9 个分享给大家。 「 遇到 AI是智障的时候 」 当你遇到 AI像个"人工智障"，无法完成你布置的任务时，你的第一 ...

Core Viewpoint - The article discusses the launch of AutoGLM 2.0 by Zhipu, which elevates the application of Agents to a new level, introducing the world's first mobile Agent that operates without occupying user devices and can run on any hardware [2][3]. Product Overview - AutoGLM 2.0 is powered by domestic models GLM-4.5 and GLM-4.5V, showcasing comprehensive capabilities in reasoning, coding, and multimodal tasks [2][9]. - The product allows users to perform various tasks across multiple high-frequency applications like Meituan, JD.com, and Douyin, effectively transforming AI from a chat tool to a fully functional assistant [6][7]. - It operates independently in the cloud, enabling users to engage with other applications simultaneously, thus enhancing productivity [6][7]. Market Position - AutoGLM is positioned as a leading product in the domestic market, with expectations to drive significant growth for Zhipu [3][4]. - The annual recurring revenue (RRR) for Manus has reached $90 million, indicating a strong market presence and potential for further growth [2]. Technological Advancements - AutoGLM 2.0 represents a qualitative leap, capable of executing tasks autonomously without user intervention, adhering to the 3A principles: Around-the-clock operation, Autonomy without interference, and Affinity across devices [8]. - The product's capabilities can be integrated into various hardware through APIs, allowing for a broader application beyond just mobile and computer devices [8][9]. Performance Metrics - In benchmark tests, AutoGLM outperformed competitors like ChatGPT Agent, UI-TARS-1.5, and Claude Sonnet 4 in device use, showcasing its robustness and versatility [10].

Group 1: Walmart Recall - Walmart has recalled certain Great Value raw frozen shrimp products in 13 U.S. states due to radioactive contamination concerns, specifically cesium-137 [3][4] - The affected states include Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Missouri, Mississippi, Ohio, Oklahoma, Pennsylvania, Texas, and West Virginia [3] - The FDA's investigation is ongoing, and one sample of breaded shrimp tested positive, although it did not enter U.S. commerce [4] Group 2: Manus AI Revenue - Manus, an AI innovator backed by Butterfly Effect, has reached a $90 million annual revenue run rate, indicating strong financial performance [5] - The company is headquartered in Singapore and is being compared to advanced AI models from OpenAI, Google, and Anthropic [6] Group 3: Canva Valuation and Stock Sale - Canva has initiated an employee stock sale that values the company at $42 billion, a 30% increase from its previous valuation of $32 billion in 2024 [6][7] - The graphic design platform reports over 240 million monthly active users and generates an annualized revenue of approximately $3.3 billion [7]

Group 1 - Manus has reported a revenue run rate (RRR) of $90 million since its launch in March, equivalent to approximately 646 million RMB [2] - The revenue run rate is a financial metric used by startups to forecast annual revenue, calculated by multiplying monthly revenue by 12 [2] - Manus co-founder Xiao Hong clarified that revenue does not equal cash income, as many AI products offer annual payment options that are considered as deposits rather than revenue [2] Group 2 - Manus is backed by the company Butterfly Effect, with its core product being Monica.im, and the domestic entity is Beijing Butterfly Effect Technology Co., Ltd., established in April 2022 [5] - The company completed Series A financing in 2024, with investors including Tencent and ZhenFund [5] - Manus launched its general AI agent product in March 2025, claiming to be the world's first general-purpose AI agent capable of handling complex tasks and achieving state-of-the-art results in GAIA benchmark tests [5] Group 3 - Manus initially adopted an invitation-only registration system, leading to high demand for access codes, which were reportedly sold for up to 100,000 RMB on second-hand trading platforms [5] - The company has relocated its headquarters to Singapore, with a partner stating that Manus represents the next "ChatGPT moment" in AI development [5]

资本闻风而至。仅一个月后，Manus背后的母公司"蝴蝶效应"就完成了由硅谷顶级风投Benchmark领投 的 7500万美元B轮融资，估值飙升至5亿美元。媒体用上了"天选之子""中国AI之光""下一个deepseek"这 样的字眼。 但几个月后，剧情急转直下。6月，蝴蝶效应宣布将总部迁往新加坡；7月，国内120名员工，仅有40多 人跟随核心团队去新加坡，其余全被裁掉。微博、小红书账号清空，官网对中国地区不可见，和阿里云 合作开发中文版的计划也宣告搁浅...... 更讽刺的是，带它走向"全球化"的美国投资方Benchmark，如今自己也被美国政府盯上——这笔对 Manus的投资，随时可能被逼撤资。 短短半年，Manus完成了从高光到幻灭的全套。它的命运，是创业、资本、地缘政治交织下的一出荒诞 剧。 01 从天选之子到跑路 要理解Manus，就得从它的创始人说起。 文 | 新质动能，作者｜沐风，编辑｜时楠 2025年春天，一个叫 Manus 的AI应用，曾让科技圈彻夜不眠。 这款"通用型AI智能体"，凭借一段4分多钟的演示视频炸场：它能分析股票、整理发票、做简历筛选， 甚至能独立完成财务报表。 一时间，全网为之疯 ...

Core Viewpoint - Manus, a new AI agent developed by the startup "Butterfly Effect," has gained significant attention for its capabilities in various tasks such as resume screening and stock analysis, but has recently withdrawn from the Chinese market, sparking controversy and discussion within the industry [1][2]. Strategic Focus of Manus - The co-founder, Ji Yichao, emphasized that Manus's decision to not develop its own underlying model was a strategic choice aimed at achieving Product-Market Fit (PMF), which is crucial for startup success [4][5]. - Initially, Ji Yichao considered self-developing a foundational model but realized that it would hinder the ability to meet market demands and validate PMF efficiently [5]. - The team recognized the risks associated with technological lock-in when relying on proprietary models, leading to the decision to build Manus based on cutting-edge models instead [5][6]. Investment in Context Engineering - Manus focuses on "Context Engineering," a critical concept in the application of large language models (LLMs), which involves optimizing input text to guide the model in generating desired outputs [8][9]. - Context Engineering aims to transition LLMs from general assistants to specialized experts that can integrate into various industry workflows, addressing the challenge of AI implementation in real-world scenarios [9]. Core Optimization Principles - Ji Yichao outlined six core optimization principles for Manus, including maintaining stable prompt prefixes, externalizing memory through a virtual file system, and dynamically updating task lists to enhance model performance [11][14]. - These principles are essential for the stability, efficiency, and scalability of the AI agent, which are critical for its commercial viability [12][14]. Market Withdrawal Reasons - The withdrawal from the Chinese market may be attributed to strategic considerations, including the inability to sustain product development across two markets and the pressure for commercial growth [15][16]. - Domestic users perceived Manus's pricing as high without clear differentiation from local competitors, impacting its conversion rates [16]. - The decision to focus on more commercially viable markets reflects the challenges faced by small to medium enterprises in the competitive AI landscape [16][17]. Industry Implications - Manus's experience signals to the industry that the core competitive advantage in AI agent commercialization may not lie solely in the underlying model but in how effectively a system is built around it to provide timely and relevant information [18][19]. - The ongoing trend of vertical AI agent startups and the emergence of new generation agents highlight the necessity for companies to create systems that integrate LLMs into professional workflows effectively [19].

Core Insights - The article emphasizes that speed in solving real problems is a crucial competitive advantage in the AI industry, rather than striving for perfection or broad functionality [3][6][11] Group 1: Speed and Focus - The story of Tao Zhang and his team at Monica illustrates that focusing on specific user pain points can lead to rapid product development, as seen with their tool Manus, which was developed in just two months [4][5] - The combination of speed and focus is prevalent in the U.S. AI landscape, where companies can invest and develop products without facing stringent regulations, leading to unprecedented revenue growth [5][6] Group 2: Market Dynamics - The article highlights a clear market judgment: companies must act quickly to address real problems or risk being surpassed by competitors [6][12] - Manus's product roadmap aims to extend AI's independent working duration from two hours to 24 hours, showcasing a commitment to enhancing user capabilities [6][7] Group 3: Founder Expertise - The definition of "technical founders" is evolving, with successful teams now needing to balance technical skills with a deep understanding of user needs, as demonstrated by the founders of Manus and Alix [9][10] - Founders with backgrounds in various fields, such as finance and law, are leveraging their expertise to create effective AI solutions, indicating a shift in the necessary skill set for success in the AI sector [10][11] Group 4: Global AI Landscape - The article notes that while the European AI scene is still developing, it is beginning to show promise with companies like Mistral adapting to local conditions [12][13] - The dominance of English in AI development is highlighted as a significant advantage for U.S. companies, although this may change as other regions, like China, develop their own models [11]

Core Insights - The article discusses the transformative impact of AI on society, emphasizing the urgency for individuals and companies to take proactive steps in navigating this rapidly changing landscape [1][7]. Group 1: About Koji - Koji is recognized for his diverse roles, including founder of "Crossroads" and initiator of AI Hacker House, showcasing his influence in the tech and media sectors [3]. - His background includes significant contributions to the mobile internet space in China, having worked alongside notable figures in the industry [4][5]. - Koji's approach to AI reflects a willingness to embrace challenges and seize opportunities during chaotic times [6]. Group 2: Key Learnings from AI - Koji identifies three critical skills needed in the AI era: - Taste: The ability to discern what is genuinely valuable versus what is merely trendy [16]. - Agency: The capacity to create and drive change proactively [17]. - Distribution: The skill to amplify and share valuable ideas widely [18]. Group 3: Team Dynamics - The emphasis is placed on execution speed over secrecy, highlighting the importance of understanding user needs and rapid product iteration in a fast-paced technological environment [21]. Group 4: Emotional and Human Aspects - The article suggests that as efficiency increases, the focus should shift towards creating meaningful human experiences, indicating a broader potential for AI beyond mere productivity [24]. - Koji's interactions with entrepreneurs reveal a deeper mission centered around emotional connections, suggesting that the future of AI will intertwine technology with human values [23]. Group 5: Additional Insights - The article hints at various topics to be explored, such as the challenges faced by AI when it underperforms and the underestimated role of designers in the AI landscape [25]. - It concludes with a call for individuals and companies to maintain curiosity and compassion in their endeavors, positioning themselves at the intersection of technology and humanity [30].

Core Insights - GPT-5 was launched after multiple delays, showcasing improvements in intelligence, programming, and task reasoning, but did not significantly surpass its predecessor GPT-4 in performance [1][2] - The pricing strategy for GPT-5 is a major highlight, with API call costs being significantly lower than competitors, indicating strong cost-effectiveness in the current large model market [1][6] - The release of GPT-5 reflects a shift in focus from technical breakthroughs to practical applications of AI in daily life, as the excitement around large model parameters diminishes [2][3] Group 1: Evolution of GPT Models - The GPT series has evolved from GPT-1 in 2018 to GPT-5, with significant milestones including the jump from 1.5 billion parameters in GPT-1 to 175 billion in GPT-3, and the introduction of multimodal capabilities in GPT-4 [3][4] - The narrative around large model parameters is shifting towards a focus on multimodal capabilities and practical applications in sectors like healthcare and education [3][4] Group 2: Market Dynamics and Competition - The launch of GPT-5 coincides with a wave of new model releases from competitors, indicating a competitive landscape where companies are racing to capture user attention [7][8] - The slowdown in significant upgrades for large models suggests a maturation of the market, with recent models showing limited improvements compared to earlier iterations [7][8] Group 3: AI Agent Emergence - The rise of AI Agents, which are specialized applications built on large models, is shifting the commercialization focus from general-purpose models to tailored solutions for specific industries [11][12] - OpenAI anticipates that revenue from AI Agents will surpass that from ChatGPT by the end of 2025, reflecting a significant shift in business strategy [11][12] Group 4: OpenAI's Strategic Moves - OpenAI has introduced multiple versions of GPT-5, including a mini and a pro version, indicating a move towards a more customizable and tiered pricing model [6][13] - The company has also resumed releasing open-source models, suggesting a response to industry demands for transparency and collaboration [13]