Investment Rating - The report provides an investment rating of "Overweight" for the industry, indicating an expectation that the industry stock index will outperform the benchmark [61]. Core Insights - The report emphasizes the emergence of AI agents as a transformative technology, highlighting their ability to automate complex tasks and enhance productivity across various sectors [14][32]. - Manus AI is identified as a leading general AI agent, showcasing superior performance in handling complex tasks compared to other AI assistants [14][41]. - The report discusses the engineering phase of AI agents, focusing on their integration into complex data scenarios and the importance of data value in their development [27][34]. Summary by Sections Industry Overview - The AI agent industry is entering a phase of engineering, with advancements in user interface development and memory management technologies [27][28]. - Companies like Workday are launching AI agent management systems to enhance efficiency and data security in enterprise environments [32]. Technology and Performance - Manus AI has achieved state-of-the-art results in benchmark tests, particularly excelling in complex task execution [13][14]. - The technology architecture of Manus AI includes various models that support its capabilities, indicating a robust framework for task automation [17][18]. Market Trends - The report notes a growing trend of AI agents being utilized in both personal and enterprise settings, with applications ranging from recruitment automation to payroll processing [33][32]. - The competitive landscape includes major players like Tencent and ByteDance, which are actively developing AI agents for diverse applications [30][32]. Future Outlook - The report predicts that AI agents will continue to evolve, enhancing their task planning and tool usage capabilities, moving towards more autonomous and generalized functions [41][42]. - The potential for multi-agent collaboration is highlighted, suggesting that AI agents can work together to solve complex problems and improve overall efficiency [48][51].

点击 上方 硬AI 关注我们 如果Scaling Law继续有效， 继续看好AI系统组件供应商（如芯片、网络设备等），谨慎对待那些不得不持续投入巨额资 本支出的科技巨头。如果预训练缩放停滞： 看好科技巨头（因为自由现金流将回升），并关注那些拥有大量用户、能够 从推理成本下降中获益的应用类股票。 硬·AI 作者 |硬 AI 编辑 | 硬 AI 还抱着"越大越好"的AI模型不放？华尔街投行巴克莱最新研报给出了一个颠覆性的预测： AI行业正经历一 场"巨变"（Big Shift），"推理模型"和"Agent"将成为新时代的弄潮儿，而"大力出奇迹"的传统大模型， 可能很快就要过气了！ 这场变革的核心，是AI模型从"死记硬背"到"举一反三"的进化。过去，我们追求更大的模型、更多的参 数、更海量的训练数据，坚信"量变产生质变"。但现在，巴克莱指出，这条路可能已经走到了尽头。 算力无底洞、成本高企、收益却难以匹配……传统大模型的"军备竞赛"让众多科技巨头苦不堪言。更要命 的是，用户真的需要那么"大"的模型吗？在许多场景下，一个更"聪明"、更会推理的小模型，反而能提供 更精准、更高效的服务。 这究竟是怎么回事？对于投资者来说 ...

Investment Rating - The report suggests a positive outlook on the industrial AI sector, highlighting potential breakthroughs in deployment, reliability, and cost-effectiveness [1]. Core Insights - The report emphasizes that the application of AI in industrial settings may progress faster than market expectations, with significant advancements in multi-modal large models and the integration of AI agents [1][6]. - It identifies three core application modes of industrial AI: recognition applications, data modeling and optimization applications, and knowledge reasoning and decision-making applications [25][26]. - The report indicates that the cost of AI token inputs has significantly decreased, while labor costs in the manufacturing sector have been rising, suggesting a potential tipping point for "machine replacement" [27][28]. Summary by Sections 1. Industrial AI - The report discusses the challenges of high data complexity, low tolerance for errors, and high cost sensitivity in industrial AI applications [6]. - It highlights the evolution of multi-modal large models, which are expected to reduce the difficulty of processing unstructured data in industrial scenarios [7][9]. - The integration of large models for guidance and small models for execution is proposed as a collaborative approach to enhance reliability in production processes [22][23]. 2. Industrial AI Middleware - The report notes that industrial AI middleware is in its early penetration phase, addressing the need for seamless iteration between model and data sides [1][2]. - It outlines the commercial progress of industrial AI middleware, with significant contracts awarded, such as a project worth 48.67 million yuan for AI middleware capabilities [39][41]. - The middleware is expected to have high construction barriers, requiring capabilities in computing power integration, model management, and industrial data governance [2][3]. 3. Industrial AI Applications - The report identifies that the maturity of AI applications in production control is leading, with over 57% of applications focused on this area [1][3]. - It highlights specific use cases, such as the AI+PCB solution by Saiyi Information, which automates the entire process from parameter analysis to cost query and quote generation [21]. - The report also mentions the emergence of vertical agent applications in various sectors, indicating a shift towards subscription-based models in industrial AI [22][39]. 4. Investment Recommendations - The report recommends focusing on key players in the industrial AI sector, such as Zhongkong Technology, Saiyi Information, and Zhongwang Software, as they are expected to benefit from the ongoing developments in industrial AI applications [1][2].

昨晚到今天，AI圈有3个重磅消息，中国科技的叙事持续加强。 阿里通义没有食言，说这周再开源一个RL新模型，昨晚放出来了。最厉害的是32B性能比肩满血DeepSeek R1，在测试数学能力的AIME24评测集上，以及评 估代码能力的LiveCodeBench中，千问QwQ-32B表现与DeepSeek-R1相当，远胜于o1-mini及相同尺寸的R1蒸馏模型，现在已经可以在通义APP和网页端体 验了。 而且看起来，这个RL训练并没有花费太长时间，阿里的朋友反馈，与以往奖传统励模型不同的是，说这次是通过校验生成答案的正确性来为数学问题提供反 馈。 14:10 M Junvang Lin @ 17 阿里通义开源RL新模型 @ lustin| in610 This week we release QwQ-Max-Preview on Qwen Chat. I know you guys may think what happened to the opensource of this team. Here is a straight answer to you all: we will opensource the m ...

智谱很快将发布全新大模型并将其开源。 更进一步来讲， 本次获得杭州地方国资的注资，再一次证明了智谱的能力和价值 ——毕竟，今年1 月15日，智谱旗下多个实体曾被美国商务部工业和安全局（BIS）列入实体清单。智谱彼时第一时间 发布声明称，智谱有能力也将更专注地为我们的用户和伙伴提供世界一流的大模型技术、产品和服 务。同时公司将继续参与全球人工智能竞争，坚持最高安全标准和公平、透明、可持续原则，推动人 工智能技术发展。 成立于2019年的智谱以"让机器像人一样思考"为愿景，研发了具有国产独立知识产权的GLM大模型 预训练架构，GLM-4-Plus作为最新基座模型，技术实力位居世界领先梯队。尤其是，智谱在 Agentic LLM 方 向 优 势 明 显 ， 先 于 OpenAI 提 出 Phone Use 概 念 并 推 出 Agent 产 品 AutoGLM 及 GLM-PC，Agentic GLM已经与全球车企、PC及手机厂商展开深度合作，推动大模型从Chat走向 Act。 同时，智谱以Model as a Service(MaaS)为理念构建的开放平台 bigmodel.cn，正持续为 千行百业带来人工智能创 ...

以下文章来源于晚点对话 ，作者程曼祺 晚点对话 . 最一手的商业访谈，最真实的企业家思考。 "创业没有天选之子。" 文丨程曼祺 编辑丨宋玮 *头图是 Dota 2019 国际邀请赛决赛（TI9）中，OG 战队的 Ana 使用 IO（小精灵，图中球形发光体）的经典作战。 经过 "一切在加速" 的 2024 年，围绕中国大模型创业的讨论，从 "谁又融资了？" 变成 "谁会第一个倒 下？" 行业分化时刻，我们与中国大模型六小龙之一，估值已超 30 亿美元的 MiniMax 创始人兼 CEO 闫俊杰访 谈 3 小时，聊了 MiniMax 的新技术目标、新模型，去年一年的公司变化和人员调整，和他作为一个 "练习 时长 3 年" 的初次 CEO 的自我复盘。我们也对他进行了 "信仰之问"。 10 个月前， 闫俊杰也接受过《晚点》访谈 ，那时他提了 16 次字节、47 次 OpenAI，8 次 Anthropic。 这次再聊，他主动提字节少了，提 Anthropic 多了。这与行业风向形成微妙的反差。 闫俊杰更在意字节的 2024 年 3 月，中国大模型创业公司势头正盛，此前 6 个月里，各模型公司至少融了 20 亿美元。 ...

2024 年 12 月的全球 AI 大事记。 文丨贺乾明 编辑丨程曼祺 2024 年 12 月的 AI 月报，你会看到： OpenAI、Google 发布新模型，中国的 DeepSeek 也抢到了风头 GPT-5 训练遇阻的更多细节 强化学习的重要性持续提升 至少有三个团队推出了世界模型 Google 霸占大模型竞技场前三 中国公司在开源社区存在感大涨 博通帮大公司自研 AI 芯片，市值破万亿美元 OpenAI 正式启动转型营利公司 20+ AI 公司获 5000 万美元以上投资，有 2 家中国公司 大模型的幻觉并不是一无是处 以下是我们第 2 期 AI 月报，欢迎大家在留言区补充我们没有提到的重要进展。 技术｜10 亿美元没训出 GPT-5，新版 Scaling Laws 初步证明可行，多款世界模型亮相 GPT-5 训练遇阻的更多细节 OpenAI 训练 GPT-5（代号 Orion）遇阻，是大模型能力提升放缓的重要证据。12 月，多家媒体提供了更多的细 节： 2023 年 4 月推出 GPT-4 后，OpenAI 一直在开发 GPT-5，已经持续 20 个月。OpenAI 看到过乐观信号：24 年 4 月 ...

Core Viewpoint - The current AI market is experiencing a significant transformation, with optimism for 2024 and beyond, driven by advancements in technology and a shift in investment focus towards practical applications and embodied intelligence [1][3][4]. Summary by Sections AI Market Overview - In 2023, the AI market saw a surge in interest, reminiscent of the internet boom, as many internet professionals sought new opportunities in AI due to a lack of significant developments in the internet sector since 2015 [1]. - The influx of capital primarily targeted large model companies, with less focus on intermediate layers and applications [1]. 2024 Market Dynamics - The first half of 2024 is expected to be the lowest point for the primary market in the past decade, with minimal funding for new startups [2]. - A notable shift occurred post-September 2024, with a recovery in the financing market and the emergence of high-valuation startups [3]. - The focus in 2024 has shifted from large models to embodied intelligence, with some institutions also exploring AI hardware and consumer electronics [2]. Investment Trends - The valuation of application companies remains low, with most having zero annual recurring revenue (ARR) as they refine their products [2]. - The market is witnessing a bifurcation, with a preference for investing in founders with strong backgrounds and higher valuations [5]. Future Directions for AI - The anticipated trends for 2025 include a focus on application landing, particularly in productivity tools, which are expected to dominate the market [5][6]. - The concept of "Prosumer" or "Pro C" individuals is emerging, targeting a demographic that combines consumer traits with business capabilities [6]. Key Areas of Growth - Two promising areas for 2025 are Agents and multimodal applications, with Agents seen as a potential evolution of traditional SaaS models [7][9]. - The potential for Agents to disrupt existing SaaS companies is significant, as they may offer a results-based payment model rather than a subscription model [9][10]. Multimodal Applications - The future of AI products may lie in multimodal capabilities, allowing for a complete transformation in user interaction and content consumption [13][14]. - The development of products that integrate various forms of content and user interaction is expected to redefine how information is managed and utilized [14][15]. Conclusion - The AI market is poised for growth, with a strong emphasis on practical applications and innovative business models, suggesting a bright future for companies that adapt to these changes [16].

我对当下的 AI 市场和明年的发展都极度乐观，明年肯定是个 AI 大年，我发现市场太悲观了，这 就是我拖延了两周，最后决定一定要做这期内容的原因。 来，我们直入主题，先来看这两年 AI 发生了什么。 23 年，AI 来了，很多互联网人和美元基金就直接冲了，因为不管从什么角度看，AI 这波都和大 家熟悉的互联网那波机会太像了，而且天下其实已经苦互联网人久已，从 15 年以后大机会其实就 不多了，18 年以后更是几乎没有，我记得过去两年涨起来的到千万日活的产品可能也就是番茄小 说等极少数的几个。 那互联网人发现我练成一身武功绝学，江湖却没了，这怎么能忍？ 然后市场做了个判断，AI 是不是大机会？肯定是，是什么量级先不说，是对标电、互联网还是云 也先不管，但这里又有个判断，就是 AI 肯定还在早期，所以很多人有个结论，说 AI 要先投技术 背景的人，所以像清华的教授都被撸了一遍，然后 23 年最多的钱就都流向了大模型公司，很少量 的钱流向了做中间层和应用的公司。23 年的时候，但凡你是从 OpenAI 出来的，都像是神坛上的 人，大家到美国去学习也是千方百计拼谁能约到个 OpenAI 的人聊聊。 那冲的结果怎么样呢 ...

本文为IPO早知道原创 作者｜Stone Jin 微信公众号｜ipozaozhidao 据IPO早知道消息，作为最早探索 Agent 的大模型企业之一，智谱于11月29日带来了多个新进展： AutoGLM 可以自主执行超过50步的长步骤操作，也可以跨 A pp执行任务 ； AutoGLM开启「全 自动」上网新体验，支持等数十个网站的无人驾驶 ； 像人一样操作计算机的GLM-PC 启动内测， 基于视觉多模态模型实现通用Agent的技术探索 。 具体来讲，新升级的AutoGLM可以挑战完成复杂任务：1. 超长任务：理解超长指令，执行超长任 务。2. 跨App：AutoGLM 支持跨App来执行任务。3. 短口令：AutoGLM能够支持长任务的自定义 短语。4. 随便模式：AutoGLM可以主动帮你做出决策。 同时 AutoGLM启动大规模内测，并将尽快上线成为面向C端用户的产品。AutoGLM同时宣布启动 「10个亿级App免费Auto升级」的计划，邀请 App 伙伴联合探索自己的Auto新场景。 此外，智谱还带来基于PC的自主Agent——GLM-PC是GLM团队面向「无人驾驶」PC的一次技术 探索，基于智谱的 ...