「Jinqiu Spotlight」 追踪锦秋基金与被投企业的每一个光点与动态，为创业者传递一线行业风向。 AI视频产品的叙事革命在屏幕里狂飙。而屏幕外，我们对能与物理世界交互 的载体的想象力，也已经从机械钢甲 机器人延展到生活空间里的"电子搭子"——AI潮玩。比如，这位爱吹牛的"算命先生"和这位额头贴着"关你屁 事"的"小僵尸"。 2月4日，AI 潮玩品牌 奇妙拉比 正 式发布"阴阳双生"系列新品，并官宣完成数千万人民币的天使轮融资， 本轮 融资由 锦秋基金领投 ，首程控股联合投资，沧澜资本担任独家财务顾问。 在消费电子与智能交互的交 汇点上， 锦秋一直在寻找那个能突破"工具属性"的载体。 不同于传统潮玩的"静止 美"，奇妙拉比赋予了 IP "AI生长基因"。 锦秋基金认为，奇妙拉比的核心IP——RAGUS，其独特的生命力在于其天生具备与AI、机器人深度融合的底层基 因，并在同一人格底色下衍生出不同角色灵魂，构造出多元IP宇宙，正是奇妙拉比区别于传统IP的核心优势。团队 对潮玩的深度理解和用户的精准把握创造出了剧情系统、卡牌、面具、积分等系列的创新玩法，短短数月就吸引了 大量的忠实用户，用真诚的产品为用户带 ...

这是AI从"实验室神话"走向"人间烟火"的12年，也是见证他个人从"做生意赚钱"到"求高级"再到"接地气"的逻辑自洽的12年。 第 三次的创业正值2023年AI2.0浪潮来 临之际，但不同于他人的"宏大叙事"，他的初心中有一种特别的"柔软"： 他听到了大众的表达："所有人都在让我努力工作，只有 AI 让我好好生活。" 在科技圈， 沈洽金 是一个很难被"定义"的人。 他读的是园林专业，却在大学时就凭着一股子"极客"钻劲成了校园站长；他是商汤科技早期的合作伙伴，在十多年来打磨出一套与大厂竞合的独门"艺术"；从流 量时代走出来，却把目光投向普罗大众的表达欲。 从2014年的"一登" ， 到后来的"闪剧"，再到如今的"造梦次元"，这位名副其实的连续创业者在AI这条路上走了12年。 他想为 那些在现实生活中没有聚光灯、 在小红书抖音上缺乏素材的"99%的普通人"， 用AI构建一个能表达、能社交、能"造梦"的乐园。 他深知AI的边界，不沉 溺于参数的堆砌，而是要做那个将顶尖模型"翻译"成普罗大众共情瞬间的翻译官。 回到那个锦秋经典问题：如果没有你的创业，世界会错过什么？ 这一次的答案，很 可能是：听不到在主流社交平台中" ...

Core Insights - The article discusses the rapid growth and transformation of the AI comic drama industry, highlighting the success of Jiangyou Culture as a leading player in this space, with significant revenue and user engagement metrics [1][3][4]. Group 1: Industry Growth and Market Dynamics - The AI comic drama market has seen explosive growth, with Douyin's daily consumption reaching 35 million, up from zero a year prior, indicating a significant shift in content consumption patterns [4][10]. - Jiangyou Culture has rapidly expanded its team from 50 to 1200 people and aims to achieve 1 billion in revenue with 200-300 million in profit this year [3][9]. - The overall market for AI comic dramas is projected to reach 33 billion in 2026, driven by a surge in demand for high-visual-impact, fast-paced content [11]. Group 2: Cost Reduction and Production Efficiency - Traditional dynamic animation costs between 3000 to 10,000 yuan per minute, while AI comic dramas have reduced this to approximately 1000 yuan per minute, with aspirations to lower it further to 500 yuan [12][14]. - The production workflow has been streamlined, allowing for rapid content generation with minimal human intervention, significantly reducing collaboration costs and time [21][22]. - A skilled "抽卡师" (card drawing artist) can produce usable frames at a rate significantly faster than traditional animators, enhancing overall production efficiency [20]. Group 3: Technological Advancements - Key technological breakthroughs in video generation models have led to improved quality and reduced costs, enabling the production of high-quality content at a fraction of previous costs [16][18]. - The industry has adopted a batch generation and manual selection approach to address the variability in AI-generated content quality, enhancing the reliability of the output [19]. Group 4: Content Expansion and New Opportunities - AI technology allows for the creation of previously unfeasible genres, such as fantasy and sci-fi, which require extensive special effects that were cost-prohibitive in traditional filmmaking [25][26]. - The ability to produce diverse content types has opened up new market opportunities, allowing for the exploration of a wider range of narratives and themes [24][28]. Group 5: Future Trends and Strategic Directions - The article suggests that the future of content production will involve a combination of technology and intellectual property (IP) strategies, with a focus on both short-term technological advancements and long-term IP development [40][42]. - The potential for AI-generated content to penetrate international markets is highlighted, with the possibility of creating localized versions of stories at significantly lower costs [48][50]. - The overall landscape of the film and content industry is expected to undergo a revolutionary change, with AI enabling personalized content experiences and expanding market size dramatically [51][60].

Core Insights - OpenAI's Codex App represents a significant shift in software development, enabling both developers and non-technical users to create and manage AI agents, marking the transition from linear to parallel development [2][3] - The introduction of Skills functionality allows non-technical users to generate tools, indicating a new era of software supply explosion and redefined value [3] Group 1: Paradigm Shift in Software Development - The development methodology is changing from serial to parallel, breaking the constraints of "man-days" and potentially increasing efficiency by 30%-50% or more [5] - Software is evolving from a "product" to a "service" or "instant response," where code can be generated on demand based on user needs [6] - The scarcity of software is diminishing, leading to a dilution of individual software value, akin to inflation in currency [7][8] Group 2: New Market Dynamics - The SaaS subscription model for SMBs may be challenged as on-demand generation of software becomes more prevalent [12] - Skills represent a low-cost, customizable alternative to traditional SaaS products, potentially disrupting the lower end of the SaaS market [13][16] - The value of software is shifting from functional capabilities to data, relationships, and network effects, as functionalities can be easily replicated [17] Group 3: Changing Roles and Skills - The role of programmers is evolving from code writing to AI collaboration, requiring new skills in AI utilization and output evaluation [23][24] - The demand for code review may become a bottleneck as AI-generated code proliferates, necessitating new quality control processes [28] - The educational focus for programmers may shift from coding to designing reusable skills and understanding business processes [27] Group 4: New Opportunities and Challenges - The emergence of a "Skill market" could create new platforms for sharing and monetizing skills, similar to an App Store [38] - The competitive landscape is shifting as model providers like OpenAI move into application layers, posing threats to intermediate tool companies [43][44] - The geographic arbitrage logic in software development is changing from labor cost to AI efficiency, impacting outsourcing dynamics [37] Group 5: Future Considerations - The value of data and unique insights will become more critical as code generation costs approach zero, with private, real-time, and relational data becoming increasingly valuable [53][54] - The software industry is at the beginning of a transformative phase, comparable to historical shifts brought by the printing press and the internet [55][56]

「Jinqiu Select」 跨越语言与时差，传递科技圈最值得被听到的声音。 < Overview > Harrison Chase 作为 LangChain 的联合创始人 兼 CEO，是 AI Agent（AI 智能体）基础设施领域最具影响力的工程实践者之一。 自 2022 年开源 LangChain 以来，他 亲历了从早期 GPT-3.5 的简单链式调用，到如今 Claude Code、Deep Research 等长程 Agent 爆发的完整技术周期。 Chatbot 已经不适合 作为新一代 AI 产品的主流形态了。 这不是模型能力的问题，而是产品形态的问题。 Chatbot 的本质是"即时响应"，追求的是低延迟和高流畅度。 但真正有价值的一些日常工作从来不是这样运转的。一份优质的研究报告需要反复检索、交叉验证、结构化整理；一个可靠的代码 PR 需要理解上下文、规划方 案、测试验证、处理边界情况。 这些任务的共同特点是：它们需要时间，需要多步骤的自主决策，需要在过程中不断调整策略。换句话说， 它们需要的不是一个"即时响应者"，而是一个"长程执 行者"。 这正是 Long-horizon Agent 崛 ...

「Jinqiu Spotlight」 追踪锦秋基金与被投企业的每一个光点与动态，为创业者传递一线行业风向。 今日， 锦秋基金被投企业- 生数科技 宣布完成超过6亿元人民币A+轮融资。 锦秋基金是生数科技天使+轮独家投资方，于2023年年中投资了生数科技，是生数科技的早期机构投资人。 2月5日， 生数科技宣布完成超过6亿元人民币A+轮融资。 本轮融资由中关村科学城公司和星连资本领 投，上市公司万兴科技、视觉中国、拓尔思进行战 略投资，原有股东启明创投、北京市人工智能产业投资基金、卓源亚洲、建发新兴投资、淮海投资等投资人加码跟投。 坚持模型技术原创、创新与突破，模型能力全球领先 生数科技是全球最早研究多模态生成算法的团队，2022年9月提出U-ViT架构（比OpenAI的DiT架构早三个月），2023年3月生数科技成立，2024年4月在中关 村论坛上发布中国首个全面对标Sora的文生视频大模型Vidu，随后于2024年7月全球上线Vidu，在文生视频和图生视频的模型能力外，Vidu全球首创"参考生视 频"技术，率先解决了商业级视频需求中的多主体连续一致性难题，此后连续发布Vidu Q1、Vidu Q2和Vidu ...

2月3日， 锦秋基金创始合伙人杨洁 参加 亚马逊云科技 re:Invent 中国行 活动，并作题为《AI赛道一级市场投资 趋势观察和思考——AI创业者应该高效利用杠杆》的内部分享。 锦秋基金是一家 AI-native 投资机构。 我们常为首轮投资人，投资额度通常为 100 万至 2500 万美元。 我们快速决策，支持 SAFE 与多轮投资，同时引入人才、产业资源以及全球投资网络。我们亲身参与并活跃在AI 前线，做最早理解变化、长期陪伴的投资伙伴。 锦秋的目标是寻找敏锐热情、有深刻认知和超强执行力的创始人，尊重他们的独特路径，助力他们发挥最大潜力。 这背后，也是锦秋对于当下AI创业的思考： AI技术飞速迭代的时代里，锦秋基金应该如何与创始人一起，利用好 杠杆，来实现高速增长？ 在算法重构生产力的当下，锦秋不仅是出资人，也希望成为技术变革的深度参与者，尊重技术背后每家企业的独特 成长路径。 以下为锦秋基金创始合伙人杨洁的分享，经整理。 第一，我们低估了 AI 的真实需求量和天花板； 第二，我们低估了技术迭代的速率和AI产品增长的斜率； 第三，我们低估了社交媒体的杠杆效率。 下午好，我是锦秋基金创始合伙人杨洁。 我 ...

Group 1 - The core viewpoint of the article discusses the emergence of 1.8 million "animation super individuals" enabled by technology, suggesting that animation can become a form of "super expression" for everyone [1] - The discussion features OiiOii's founder, who emphasizes that OiiOii is not just a generative tool but an intelligent collaborative agent system composed of AI scriptwriting, storyboarding, and sound effects [1] - The conversation aims to dissect the technological experiment surrounding "identity reversal" and the reconstruction of AI productivity [1] Group 2 - The first episode focuses on the dynamics of AI entrepreneurship in China and the U.S. in 2026, highlighting how Chinese entrepreneurs can position themselves on a global stage [2] - The guests include a dual-capacity investor with a background in AI research and early-stage VC, providing insights into the underlying logic of the Sino-U.S. AI investment ecosystem [2] - Key topics include the due diligence truths of Silicon Valley VCs, funding strategies for non-native entrepreneurs, and overlooked market gaps by OpenAI [2] Group 3 - The CES discussion involved around 40 participants from AI hardware and AI agent sectors, exchanging insights on industry trends observed during the CES event [3] - The "Predict 2026" roundtable gathered AI builders to share their predictions for the year, focusing on supply-side discussions and the evolving landscape of content production and trust in a saturated market [5] - A session on AI application gaps explored the challenges and future prospects of AI deployment, with founders and practitioners sharing their experiences [7] Group 4 - A conversation with a top AI comic company centered on multimodal content and the industrialization of content production, addressing emotional expression and monetization strategies [8] - The article highlights the achievements of various companies, including Inke's recent financing round of nearly 200 million RMB, indicating strong investor interest in humanoid robotics and core components [12] - The article also mentions the successful launch of several AI products at CES 2026, showcasing advancements in humanoid robots and smart home technology [19][21][23]

Core Insights - The AI funding landscape has seen a dramatic increase, with global AI financing reaching $225.8 billion in 2025, a 97% year-over-year increase, despite a slight decrease in the number of deals [3][10] - The funding is increasingly concentrated, with 78% of the capital flowing to less than 5% of projects, indicating a shift towards larger investments in fewer, high-potential teams [3][4] - The valuation dynamics have shifted from "scale-driven" to "density-driven," where smaller, more efficient teams are achieving higher valuations per employee [5][75] Investment Trends - Global AI financing reached $225.8 billion in 2025, a 97% increase from the previous year, while the number of deals slightly decreased, indicating larger average deal sizes [10][26] - In Q4 2025, AI financing surged to $83.2 billion, doubling compared to the average of the first three quarters [13] - The median deal size in the AI sector rose to $4.1 million, with the U.S. leading at a median of $5 million per deal [28][26] Regional Insights - Over 85% of global AI funding in Q4 2025 was directed towards the U.S., with a significant valuation gap between U.S. and Asian projects [4][16] - The median deal size in the U.S. was $5 million, compared to $3 million in Asia, highlighting the regional valuation disparity [4][28] Valuation Dynamics - The capital's focus has shifted to "density-driven" valuations, where smaller teams are achieving higher valuations per employee, such as OpenEvidence with a valuation of $173.9 million per employee [5][75] - In 2025, 67% of M&A targets had fewer than 50 employees, indicating a trend towards smaller, more agile companies being favored in acquisitions [68][68] Exit Trends - In 2025, there were 830 global AI exit transactions, with 782 through M&A, marking a 61% increase year-over-year and the highest in five years [94][94] - The U.S. accounted for 47% of exit transactions, demonstrating its dominance in both investment and exit activities [98][98] Talent Trends - The fastest-growing segments in AI talent include AI agent browser infrastructure (87.2% growth), voice AI development platforms (54.1% growth), and multi-agent systems (49.8% growth) [66][66] - Talent is migrating from foundational model layers to application infrastructure, indicating a shift in focus within the AI industry [7][7] Unicorn Insights - In 2025, 75 new AI unicorns were created, with the U.S. dominating the landscape, holding 256 out of 360 total unicorns by year-end [80][81] - The top three newly minted unicorns in Q4 2025 were Mercor ($10 billion), Metropolis ($5 billion), and Unconventional AI ($4.5 billion) [90][90]

「Jinqiu Select」 < Overview > 在 AI 时代，这意味着虽然单行代码的编写速度加快、成本大幅下降，但全球对软件的需求却完全没有放缓的迹象。未来的软件工程将经历本质重构， 更高比例的全球 GDP 将通过这种方式创造，且未来的软件将不再是通用型的"大厂产品"，而可能是仅为个人或极小群体定制的、持续进化的"私人软 件"。 跨越语言与时差，传递科技圈最值得被听到的声音。 更高比例的全球 GDP 将以此种方式被创造与消费。 代码免费、智力通缩，2026年后的AI创业者靠什么建立护城河？ 我们正处在一个"智力"作为生产要素被彻底重构的奇点 。 最近，OpenAI 首席执行官萨姆·阿尔特曼（Sam Altman）在内部交流会中的发言，为这种焦虑提供了一份极具清醒感的"内参" 。 Sam Altman的回答基于一个深刻的经济学逻辑——杰文斯悖论： 当技术的进步提高了某种资源的利用效率，该资源的消耗量反而会因为需求的指数级 增长而增加。 OpenAI 内部预测， 到 2027 年底，提供 GPT-5.2x 级别智力的成本将比现在降低 100 倍以上 。 这意味着"智力"将真正成为一种像电力一样廉价、按 ...