以下文章来源于混沌学园 ，作者混沌学园 混沌学园 . 学创新，就在混沌！ 本文整理自李丰在混沌学园的2026开年课程，来自微信公众号： 混沌学园 ，作者：李丰，原文标 题：《李丰：2026，关于赚钱、AI与竞争逻辑，我的展望和预判》，题图来自：AI生成 关于AI下半场：所有技术周期都有上半场和下半场。上半场美国领先技术，但下半场，中国更有优 势。而每一个技术浪潮到了后半场，中国往往开始追赶并反超。 关于中国AI机遇：AI+硬件将成为中国的战略机遇，当"软件+硬件"成为中国极为擅长的组合拳，我 们能够利用中国制造业"卷"出来的供应链优势，实现产业转换与升级。 关于终极竞争：中美AI竞争里，中国正握住另一张底牌，数据。十年之后，大国竞争的终局将聚焦 于两件事：能源和数据。谁在这两个问题上有更确定性和长期的优势，谁就有可能赢。 以下为演讲内容： 感谢混沌的邀请，让我每年有一次机会来跟大家分享。我每年也以此为契机，试图从我们的角度来探 讨：这个世界和我们身处的中国，为什么发展到了今天这个样子？为什么你周围的状况，和你切身的 体验是现在这般模样？ 今天我们先讨论一下最近非常热的话题，也是中美竞争的焦点，其核心主要在于： ...

站在2026年，我们会猛然发现，过去几年的技术爆发仅仅是时代的序章，真正的社会级应用与产业洗牌才刚刚开始。面对未来5到20年的巨变 与重构，新一轮的红利与机遇到底在哪里？ 峰瑞资本创始合伙人李丰，在混沌学园的年度重磅分享中，给出了他关于2026年的关键展望，这不仅是一次关于AI技术的讨论，更是一场关 于钱、科技创新与AI产业竞争逻辑的深度复盘。 关于AI下半场：所有技术周期都有上半场和下半场。上半场美国领先技术，但下半场，中国更有优势。而每一个技术浪潮到了后半场，中国 往往开始追赶并反超。 关于中国AI机遇：AI+硬件将成为中国的战略机遇，当"软件+硬件"成为中国极为擅长的组合拳，我们能够利用中国制造业"卷"出来的供应链 优势，实现产业转换与升级。 关于终极竞争：中美AI竞争里，中国正握住另一张底牌，数据。十年之后，大国竞争的终局将聚焦于两件事：能源和数据。谁在这两个问题 上有更确定性和长期的优势，谁就有可能赢。 以下为李丰老师2026开年课程的干货精编，建议收藏细读。本文仅占全部内容的50%，完整内容在混沌APP。 感谢混沌的邀请，让我每年有一次机会来跟大家分享。我每年也以此为契机，试图从我们的角度来探讨： ...

Group 1 - The article discusses the initial skepticism towards AI advancements due to many major companies' new versions falling short of expectations, leading to concerns about future developments [1] - However, after participating in discussions about AI implementation, there is a renewed optimism as AI is being widely adopted across various industries, subtly transforming the world [2] - There is a distinction made between high-end AI technologies, such as large language models and autonomous driving, and more mature technologies like voice and image recognition, which are not considered groundbreaking [3][4] Group 2 - AI is portrayed as a tool accessible to everyone, capable of improving efficiency and outcomes in specific scenarios, thus demonstrating the value of technological progress [4][5] - Numerous practical applications of AI are highlighted, such as automatic transcription of meetings and structured processing of customer interactions, which significantly enhance digital capabilities [6][7] - Despite some professionals dismissing these applications, they are recognized as valuable and memorable, showcasing AI's ability to meet user needs and gain acceptance [8] Group 3 - The article notes that while AI is a hot topic in the tech industry, many projects are still struggling to achieve profitability, indicating that the AI industry is not yet stable [23][24] - From a supply-side perspective, AI applications often lack economies of scale, as the backend systems require extensive customization, making it difficult to standardize and productize solutions [25] - Users expect AI applications to be cost-effective, and while many AI solutions are currently subsidized, the sustainability of this model is questioned as companies may eventually need to charge for their services [27] Group 4 - There are differing opinions on the future of AI, with some focusing on continuous investment in generative AI, while others seek to commercialize existing technologies and create tangible value [28][31] - The article suggests that without a consensus in the industry, the fragmented approach to investment may lead to suboptimal outcomes for all parties involved [32] - Despite the challenges, the gradual integration of AI is enhancing the overall digital landscape, benefiting both individuals and organizations [33]