Core Viewpoint - Kunlun Core has recently completed a new round of financing, but there is a noticeable divergence in information disclosure, with investors and financial advisors announcing the news while Kunlun Core remains silent, raising questions about the underlying issues [1][2]. Financing Situation - Kunlun Core's latest financing round has seen participation from various investors, including Shanghe Momentum Capital and Shanzheng Investment, with the latter confirming their involvement just a day before the announcement by Shanghe [1]. - The company has undergone six rounds of financing since its establishment, with Baidu remaining the largest shareholder, though its stake has been diluted from 76.17% to 67.49% [4][6]. IPO Context - The financing is taking place against the backdrop of a surge in domestic GPU and AI chip companies preparing for IPOs, with nearly ten companies expected to file for listings soon, collectively referred to as the "Chinese Nvidia" [6][9]. - The current market conditions have made it difficult for GPU projects to attract investment, with many investors expressing reluctance to invest in the GPU sector due to significant losses reported by existing companies [7][9]. Product Development and Market Position - Kunlun Core, which originated from Baidu's smart chip division, has launched its first and second-generation chips, with plans for a third-generation chip (P800) set for release in 2025 [11]. - The company has achieved a notable milestone by creating a fully self-developed 30,000-card cluster capable of training large models, which is a significant achievement in the domestic market [11][13]. Competitive Landscape - In terms of performance, Kunlun Core's P800 ranks among the top in the domestic market, but it still lags behind some competitors like Birun's BR100, which boasts superior specifications [18][19]. - According to IDC, Kunlun Core ranks second in the domestic AI accelerator card market, although the accuracy of this data has been questioned by industry insiders [19][20]. Production Capacity and Future Outlook - The production capacity required to meet the projected demand for Kunlun Core's products is substantial, with estimates suggesting that 1,400 wafers would be needed to achieve the anticipated output [20]. - The upcoming regulatory changes may impact the production capacity of domestic AI chip companies, making it crucial for them to secure sufficient manufacturing resources to maintain their market positions [21].

Core Viewpoint - The rise of domestic AI chip companies, particularly Muxi Integrated Circuit (Shanghai) Co., Ltd., is accelerating their entry into the capital market, with Muxi's IPO on the Sci-Tech Innovation Board being a significant event in the GPU sector [1][2]. Company Overview - Muxi aims to raise 3.904 billion yuan for the development and industrialization of next-generation general-purpose GPUs, AI inference chips, and advanced heterogeneous computing architectures [1]. - Founded in 2020, Muxi is part of the "Four Little Dragons" of domestic GPUs, alongside companies like Moore Threads and Birran Technology [2]. - Muxi's flagship product, the "Xiyun C series," is a self-developed GPU chip that has achieved significant sales and application in AI public computing platforms [3]. Financial Performance - Muxi's revenue projections for 2022 to 2024 are 426,000 yuan, 53.021 million yuan, and 743 million yuan, respectively, indicating substantial growth [3]. - Despite revenue growth, Muxi is facing significant net losses projected at 780 million yuan, 870 million yuan, and 1.41 billion yuan over the same period, totaling 3.06 billion yuan in losses [3]. Market Context - The domestic AI chip market is still in its early stages, with increasing penetration rates for local brands, but lacking a clear competitive landscape [1]. - The rise of domestic GPU manufacturers is driven by the growth of AI models, the "East Data West Computing" initiative, and ongoing policies promoting domestic innovation [5]. - By 2025, domestic AI chips are expected to account for 40% of the AI server market in China, while NVIDIA's share is projected to decrease to 41.5% [7]. Policy Environment - The recent reforms in the Sci-Tech Innovation Board have created a more favorable environment for unprofitable but technologically advanced companies like Muxi, signaling a shift towards supporting "hard tech" enterprises [4].

图片系AI生成 6月6日消息，在2025智能经济论坛上，百度集团执行副总裁、百度智能云事业群总裁沈抖宣布，目前已 有65%的央企选择与百度智能云开展深度合作，同时百度智能云发布千帆慧金金融大模型，并推出了覆 盖能源、交通、汽车、医疗、环境等领域的精选行业场景智能体家族。 百度摸索行业大模型，金融领域做试点 行业大模型是指基于通用大模型技术底座，在落地到特定行业时，针对特定行业需求和应用场景融入大 量行业特定的数据和知识，从而在专业领域内表现出更高的准确性和实用性。 一个关键的问题是，行业大模型由谁来构建？ 如果是垂直行业头部厂商，领域内其他厂商可能心存顾虑，担心自己的核心数据安全，以及是否会越来 越落后于头部厂商；如果是通用大模型厂商，核心数据从哪来，行业知识是否足够，行业厂商能否认 可，同样是问题。 百度智能云以自己积累较多的金融领域为试点，探索行业大模型的可行性。沈抖表示，基础模型能力再 强，直接放到具体的行业场景中，效果往往不达预期。 拿金融行业来说，金融对大模型的要求非常高，知识面广、时效性强，而且对大模型的准确性和幻觉率 要求更严格。通用模型因为缺乏专门金融语料的训练，很难精准回答，容易出现幻觉。 ...

6月6日，在2025智能经济论坛上，百度集团执行副总裁、百度智能云事业群总裁沈抖指出，随着基础模型的持续迭代和AI产品体验的不断优化，人工智能 技术正从"能用"走向"好用"，越来越多的领先企业开始在高价值场景中主动布局，推动大模型技术的深度应用。 他强调，百度智能云作为国内领先的云计算服务商，已与65%的央企建立深度合作，共同探索AI创新路径，助力企业加快"智改数转"步伐。 针对医疗领域的痛点，沈抖正式发布了"智慧就医智能体"。他表示，该智能体通过自然语言对话快速理解患者病情，生成结构化的电子病情卡，并在分导 诊、预约挂号、问诊等环节提供辅助支持，有效提升了接诊效率和患者满意度。在武汉协和医院的应用案例中，智慧就医智能体显著缩短了患者等待时间， 提高了医疗资源的利用效率。 在金融领域，沈抖宣布百度智能云正式推出千帆慧金金融大模型。他强调，金融行业对大模型的要求极高，需要具备广泛的知识面、强大的时效性和高度的 准确性。千帆慧金金融大模型通过深度清洗和挖掘海量金融数据，优化了推理与知识增强算法，形成了兼具知识广度与逻辑深度的模型能力。在实际应用 中，该模型能够更精准地识别业务流程关键要素，提升金融机构的服务水平和 ...

编辑丨 包永刚 落地大模型的速度和质量正成为企业在智能化浪潮中抢占产业制高点的关键胜负手。 大模型竞争下半场，全栈能力将成关键看点。 作者丨 刘伊伦 据《2024中国企业AI大模型应用现状》调研报告显示，AI大模型落地总体上仍处在探索孵化阶段，渗透率 不足1%，但在已部署大模型的企业中， 超半数企业感受到了大模型落地带来的业务价值。 割裂感充斥在这场智能化变革之中：一端是洞察价值的企业持续加码投入，另一端则是受限于技术、资金 与人才的企业，无奈将技术浪潮视为"行业泡沫"。二者间存在的认知差距与行动鸿沟，折射出大模型落地 从"试点红利"迈向"普惠深水区"的行业阵痛。 技术断层与能力失衡，则是横亘在企业智能化转型路上的双重障碍。不具备技术能力的企业面临桎梏，而 具备一定研发实力的企业，也难以规避单一能力短板引发的"木桶效应"。 某大型集团曾斥资3000万下场研发企业大模型，重金聘请技术专家，却因技术落地难、数据隐私风险及商 业模式模糊等问题，一年内耗尽预算，项目最终搁浅。 实践表明，企业大模型落地需要与拥有全栈大模型技术基因的产业专家深度协作。在大模型中标项目数、 行业覆盖数、央国企中标项目数三个维度皆"领跑"的 ...

6月6日，在2025智能经济论坛期间，百度集团执行副总裁、百度智能云事业群总裁沈抖称，"目前已有 65%的央企选择与百度智能云开展深度合作，共同探索AI创新。"此外，百度智能云还正式发布千帆慧 金金融大模型，并推出了覆盖能源、交通、汽车、医疗、环境等领域的精选行业场景智能体家族。 人工智能要真正融入千行百业，切实释放出提升生产力的效能，就需要构建起与人工智能技术—经济范 式相契合的新型生产关系。 百度智能云依托千帆大模型平台，面向企业用户推出覆盖金融、电力、交通、环保、医疗等多个行业 的"场景智能体"解决方案，推动人工智能在具体业务中从试点走向规模化应用。 面对人工智能技术从基础突破走向产业融合的关键阶段，百度智能云以金融行业为突破口，推出千帆慧 金金融大模型。据介绍，该模型在充分吸收海量金融语料基础上，通过构建金融专用数据生成体系，优 化推理与知识增强算法，形成了兼具知识广度与逻辑深度的模型能力。当前，百度智能云已推出千帆慧 金金融知识增强大模型和千帆慧金金融推理增强大模型，提供 8B 和 70B 两个版本，支持最长 32K 上 下文输入，覆盖金融行业多数场景。 沈抖指出，要做出好的智能体、好的AI应用，国 ...

Core Insights - The 2025 Smart Economy Forum was held in Beijing, focusing on the theme of developing the smart economy and accelerating the construction of a digital China, in line with the national "Artificial Intelligence +" action plan [1] - Baidu's intelligent cloud has seen 65% of central enterprises choose to collaborate deeply with it to explore AI innovation [1][3] - Baidu Intelligent Cloud launched the Qianfan Huijin financial model and introduced a family of intelligent agents covering various sectors such as energy, transportation, automotive, healthcare, and environment [1] Group 1 - Central enterprises are becoming a key force in driving the integration of digital and real economies, with a focus on large model applications [2] - Baidu Intelligent Cloud's Qianfan model platform offers "scene intelligent agent" solutions across multiple industries, promoting the large-scale application of AI in business [2] - The intelligent power supply solution developed in collaboration with State Grid has automated the entire process from user service acceptance to power supply plan generation, significantly improving efficiency [2] Group 2 - Baidu's Qianfan Huijin financial model is designed to support the development of financial technology in China, utilizing a vast amount of financial data to enhance its capabilities [4] - The model offers two versions, 8B and 70B parameters, and supports a maximum context input of 32K, covering most scenarios in the financial industry [4] - The model has outperformed general-purpose models in various tasks, demonstrating its potential to enhance service levels and risk management capabilities in financial institutions [4] Group 3 - Baidu emphasizes the importance of domestic chips for developing effective AI applications and has increased investment in domestic chip and self-developed platform infrastructure [6] - The Kunlun chip P800 has achieved large-scale commercial use, and Baidu has successfully activated the third-generation Kunlun chip clusters in collaboration with major enterprises [6] - Baidu's Baijie platform efficiently schedules and is compatible with various domestic chips, achieving over 95% utilization in training time for large clusters, supporting model development in key national industries [6]

Investment Rating - The report maintains a "Buy" rating for Baidu with a target price of $146.70, representing a potential upside of 61.7% from the current price of $90.74 [2][3]. Core Insights - Baidu is actively promoting its business transformation by integrating more generative AI-related search results to enhance user experience and engagement. Although the monetization of these search results has not yet begun, it is expected to start by the end of Q2, which should help boost advertising revenue growth and operating profit margins [9]. - The company has introduced several AI applications, including the Wenxin large model 4.5 Turbo and X1 Turbo, which feature multi-modal capabilities, strong reasoning, and reduced costs. The input price for the 4.5 Turbo model is only 0.8 RMB per million tokens, and the output price is 3.2 RMB, marking an 80% price reduction compared to its predecessor [1]. - Baidu's cloud business is anticipated to maintain strong revenue growth driven by increasing demand for digitalization and AI solutions, supporting overall revenue growth for the group [9]. Financial Summary - The financial forecast for Baidu shows expected sales revenue of 137,622 million RMB in FY25, with a projected growth rate of 3.4%. The adjusted net profit is estimated at 26,943.5 million RMB, reflecting a slight decrease of 0.2% [10]. - The company’s sales revenue for FY23A was 134,598 million RMB, with a year-on-year growth of 8.8%. However, FY24A is projected to see a decline of 1.1% in sales revenue [11]. - The adjusted net profit margin is expected to stabilize around 19.6% by FY27E, with a return on equity projected at 7.6% [12].

Investment Rating - The report maintains a "Buy" rating for Baidu with a target price of $146.70, representing a potential upside of 61.7% from the current price of $90.74 [2][9]. Core Insights - Baidu is actively promoting its business transformation by integrating more generative AI-related search results to enhance user experience and engagement. Although the monetization of these search results has not yet begun, it is expected to start by the end of Q2, which should help boost advertising revenue growth and operating profit margins [9]. - The company has introduced several AI applications, including the Wenxin large model 4.5 Turbo and X1 Turbo, which feature multi-modal capabilities, strong reasoning, and reduced costs. The input price for the Wenxin 4.5 Turbo is only 0.8 RMB per million tokens, and the output price is 3.2 RMB, marking an 80% price reduction compared to its predecessor [9]. - Baidu's cloud business is anticipated to maintain strong revenue growth driven by increasing demand for digitalization and AI solutions, supporting overall revenue growth for the group [9]. Financial Summary - The financial forecast for Baidu shows expected sales revenue of 137,622 million RMB in FY25, with a projected growth rate of 3.4%. The adjusted net profit is expected to be 26,943.5 million RMB, reflecting a slight decrease of 0.2% [10][11]. - The company’s operating profit is projected to be 21,430 million RMB in FY25, with a slight increase in operating margin to 15.6% [11]. - Baidu's total assets are expected to grow from 427,780 million RMB in FY24 to 457,698 million RMB in FY25, indicating a healthy balance sheet [11].