企业级应用：AI 加速在企业端应用落地 20251214 摘要 AI 应用加速渗透企业级服务，龙头企业业绩开始兑现，预示应用大行情 催化。美股、港股、A 股应用龙头公司表现各异，硬件驱动业绩，AI 算 力成基础设施关键。 企业级服务表现出色，如合合与亚马逊云合作股价上涨，ChatGPT 5.2 与杰米玛 3 Pro 对比表现优异，Deepseek V3.2 带来启发。大模型与 编程结合，降低 APP 发布门槛，促进应用生态繁荣。 大模型对行业影响深远，Adobe 等公司面临转型压力， AppLovin、Salesforce 等触底反弹。深入行业并反哺数据的企业将与 大模型结合，启用 AI 战略并扩大团队。 2026 年 AI 发展重点包括 Chatbot 向 Agent 演进、多模态物理模型及 Agent。顶级模型竞争格局未定，海外 Gemini、GPT 与国内千问、 Deepseek 等值得关注。 未来三到五年内，增强现实（AGR）、核聚变、量子计算等领域可能迎 来爆发。Deepseek V 3.2 论文指出开源模型在长文本处理、算力及 AI 代理能力方面存在限制。 Q&A 2026 年企业级应用的 AI ...

Core Insights - The article discusses the evolution of Google and its approach to AI, highlighting both past mistakes and future opportunities in the context of education and technology [3][10][12]. Group 1: Google's AI Strategy - Google initially missed opportunities in AI commercialization due to hesitance in promoting chatbots, fearing they would produce nonsensical outputs [3][15]. - The company's competitive edge in AI stems from long-term investments in foundational technologies, such as AI-specific chips (TPUs) and large-scale data centers [4][16]. - Future breakthroughs in AI are expected to rely more on algorithmic advancements rather than merely scaling data and computational power [5][29]. Group 2: Education and Career Guidance - Students should view AI as a tool to enhance their capabilities rather than a reason to abandon traditional fields like computer science [7][18]. - The future of universities may shift away from geographical constraints, emphasizing remote learning and collaboration [20][21]. - The path from academia to industry may need reevaluation as the timeline for turning ideas into commercial products shortens [22][23]. Group 3: Research and Innovation - While industry leads many innovations, academic research remains crucial for long-term exploratory projects that require extensive timeframes [24][25]. - Emerging technologies, particularly in materials science, are seen as underappreciated areas with significant potential for impact [32][34].

Group 1: Industry Changes - The computer industry in 2026 will witness a convergence of "industrial cycles" and "policy cycles," marking a decisive year for both existing tasks and new growth opportunities [2][3] - AI applications are expected to reach a critical point of explosion, transitioning from a phase of high expenditure to profitability, with significant scale deployment in vertical scenarios [11] - Domestic computing power has evolved from being a backup to becoming fully usable in training and inference for domestic large models, with 2026 anticipated to be a year of comprehensive replacement [12] - The completion of the "信创" (Xinchuang) initiative is set for 2027, making 2026 a peak year for bidding and delivery, with strong performance certainty for related companies [13] Group 2: Policy Changes - The "十四五" (14th Five-Year Plan) elevates commercial aerospace to a national strategic level, with 2026 expected to be a year of industry explosion driven by satellite networking and reusable rockets [6] - The low-altitude economy is transitioning from policy enthusiasm to industrial heat, with substantial construction expected in 2026 due to infrastructure standards and special bonds [6] - The integration of AI with various industries is emphasized in the "十四五" plan, aiming for deep integration in manufacturing, healthcare, transportation, and finance, which will enhance productivity and create greater economic value [20][36] Group 3: Investment Recommendations - Companies in the AI application sector should be selected based on their alignment with national policies and the "AI+" initiative, focusing on sectors like agriculture, industrial software, and healthcare [36] - Companies with strong foundational platforms and aggregation entry points for large models are recommended for long-term investment, such as Alibaba and iFlytek [37] - Data barrier companies that possess proprietary data to train models are crucial, with a focus on firms like 海天瑞声 (Haitian Ruisheng) and 同花顺 (Tonghuashun) [38] - Companies that dominate high-frequency usage scenarios, such as 金山办公 (Kingsoft Office) and 东方财富 (Eastmoney), are positioned to benefit significantly from AI integration [40]

Core Viewpoint - Tianyang Technology (300872) has invested 30 million yuan in the Qingdao Hongma Jinxin Venture Capital Fund, indirectly investing in Benyuan Quantum, China's first quantum computing company, which has submitted an IPO counseling record to the Anhui Securities Regulatory Bureau [1][3][4] Group 1: Investment Details - Tianyang Technology's investment of 30 million yuan gives it a 47.54% stake in the Hongma Jinxin Fund, making it a limited partner [1] - The Hongma Jinxin Fund was established in May 2023, with Beijing Jinxin Guotai Investment Management Co. and Beijing Hongma Tianan Investment Co. holding 99.5% and 0.5% stakes, respectively [1][2] - The investment aims to leverage the professional capabilities and resources of the fund to enhance the company's strategic development and overall value [2] Group 2: Benyuan Quantum Overview - Benyuan Quantum, founded in September 2017 with a registered capital of approximately 30 million yuan, is a leading quantum computing company in China [3] - The company focuses on building a self-controlled, engineered quantum computer ecosystem, including quantum chips, measurement and control systems, operating systems, software, and cloud platforms [3] - Benyuan Quantum is the first company in China to commercialize quantum computing, with an estimated valuation of approximately 6.88 billion yuan based on a recent share transaction [4] Group 3: Strategic Implications for Tianyang Technology - The investment in Benyuan Quantum aligns with Tianyang Technology's strategic direction in the financial market, particularly in risk assessment, investment, trading, and compliance [4] - The company has acquired exclusive permanent licensing for Algo market risk software in mainland China, enhancing its competitive edge in the financial sector [4] - A recent seminar on quantum computing highlighted the company's comprehensive layout around "data + algorithms + computing power" as a core advantage for implementing quantum technology in financial scenarios [5]

这意味着，QuantWare能够主动拥抱现有算力生态。按照公司描述，其VIO-40K架构芯片能与英伟达的 NVQLink平台相兼容。未来低延迟、高吞吐量的传统AI超级计算机将能够与大规模量子计算相集成， 并通过英伟达CUDA-Q平台为开发者提供访问这些资源的接口。换言之，VIO-40K架构的设计意图并非 取代，而是加入主流。 就连英伟达CEO黄仁勋也表态，量子计算的未来核心在于"纠错"，而实现这一目标的重要路径，是将量 子处理器与GPU超级计算机深度融合。 一直以来处于算力竞争边缘的量子计算，究竟还需多久才能步入主流？ 对于谷歌来说，这是一个尚待摸索的问题。12月12日，其宣布与英国国家量子计算中心达成合作，拟邀 请后者为公司研制的Willow量子处理器寻找应用场景。根据新闻稿，研究人员或尝试运用这项技术去破 解疑难化学和医学问题。 而在英特尔前首席执行官帕特·基辛格（Pat Gelsinger）看来，量子计算仅需两年便可步入主流。日前接 受《金融时报》采访时，基辛格表示，量子计算将在两年内普及并加速戳破AI泡沫，且将在2030年前 彻底取代GPU。在他看来，量子计算将与经典计算、AI计算共同构成未来计算世界 ...

以下文章来源于科创板日报 ，作者张真 而在英特尔前首席执行官帕特·基辛格（Pat Gelsinger）看来， 量子计算仅需两年便可步入主流 。 日前接受《金融时报》采访时，基辛格 表示，量子计算将在两年内普及并加速戳破AI泡沫，且将在2030年前彻底取代GPU。在他看来，量子计算将与经典计算、AI计算共同构成 未来计算世界的"神圣三位一体"（Holy Trinity）。 这一预言在短短几天内便得到了部分验证：12月9日，量子硬件初创公司QuantWare正式发布了全新的量子处理器（QPU）扩展架构VIO- 40K，并计划于2026年实现量子芯片的大规模量产。在荷兰代尔夫特总部，公司正在积极建设Kilofab——这座全球最大且首个专门用于量 子芯片生产的晶圆厂。据称，这将使其产能较现有水平提升20倍。 值得注意的是，QuantWare宣称VIO-40K架构能够支持1万量子比特（qubit）的量子处理器， 相当于当前主流商用量子处理器的近100倍 。 如谷歌的Willow芯片是 105 个量子比特，而IBM的Heron系列是156个。 这是否意味着，量子计算加速取代GPU，已是板上钉钉的事实？ 尚未收敛的路线之争 ...

Core Viewpoint - The article discusses the current state of the investment landscape in China, emphasizing the importance of adapting to economic cycles and focusing on internal growth strategies within the venture capital and private equity sectors. Group 1: Investment Landscape and Trends - The 25th China Private Equity Annual Conference will be held in Shenzhen from December 2-5, 2025, gathering over a thousand top investors and entrepreneurs to observe China's technological innovation [2] - The investment logic has not changed significantly this year, focusing on companies that lead in technology and manufacturing, with an increase in investment in emerging technologies such as quantum computing and AI [9][10] - The current economic cycle is characterized as an L-shaped stable period, with a focus on long-term growth and addressing shortfalls in various sectors [9] Group 2: Institutional Insights and Strategies - Institutions are increasingly diversifying their investment strategies, combining primary and secondary markets, public and private equity, and domestic and international investments [3][4] - The National New Capital Fund has established a series of funds with a total subscription scale exceeding 3 trillion yuan, focusing on strategic emerging industries and technological innovation [6] - Investment strategies are shifting from direct investments to a combination of fund-of-funds and direct investments, with a focus on strategic and merger investments [11] Group 3: Sector-Specific Opportunities - AI is identified as a foundational trend for future investments, with significant opportunities in sectors such as biomedicine, hard technology, and semiconductor industries [16][20] - The automotive sector is expected to see substantial transformation due to AI, particularly in intelligent driving and related technologies [19] - The advanced manufacturing sector is projected to offer significant investment opportunities, with many companies likely to expand globally [21] Group 4: Post-Investment Management - Effective post-investment management is crucial, focusing on identifying market needs and leveraging institutional strengths to enhance portfolio companies [22] - Institutions emphasize the importance of finding financial resources, talent, and business opportunities to support the growth of their portfolio companies [23] - A structured approach to post-investment management, including categorization and precise resource allocation, is essential for driving industry development [25] Group 5: Future of Entrepreneurship and Investment - The future of entrepreneurship in China is expected to see higher barriers to entry, particularly in hard technology sectors, requiring both scientific and entrepreneurial expertise [28] - The investment landscape is undergoing differentiation, with various types of GP (General Partners) emerging, each with distinct strategies and focuses [28] - The integration of AI into investment processes is anticipated to revolutionize traditional methods, enhancing efficiency and decision-making [24]

机器之心报道 机器之心编辑部 布林于 1993 年进入斯坦福工程学院，攻读计算机科学研究生。读研期间，他结识了拉里・佩奇。两人共同 开发了一种搜索算法，并于 1998 年创办了谷歌。 回顾谷歌的来时路， 布林 坦言 8 年前提出 Transformer 时，他们没有予以足够的重视，而且因为担心聊天 机器人说蠢 话而害怕将其展示给世人。但他同时认为，他们这些年也做了很多正确的事情，比如投资研发 TPU 并建立规模庞大的数据中心。 对于未来，布林也表达了一些自己的看法，比如认为 大学未来可能不应该再限制于某个地理位置，学界未 来应该投身更具探索性质的研究，材料等科研方向可能被低估了 …… 以下是这场对话内容的摘录。 Google 早期做对了什么？ 学术基因、敢碰难题 校长：Google 已经是一家市值 4 万亿美元的公司，业务范围极其广泛。你们这些年肯定做了很多正确的决 定。有没有什么是你们在创建 Google 初期就做对的事情？ 布林： 我觉得早期的话，Larry 一直非常有雄心。他现在也是。对你提出的每个计划，他几乎都会说「这不 够有野心」。我们确实很早就有了非常宏大的使命宣言 —— 整合全球信息。我认为这是 ...

国际人士表示，面对各种外部挑战，中国始终保持战略定力，中国经济展现出强劲韧性，也持续为世界经济提供稳定预期和发展希望。 毕马威德国公司国际业务管理合伙人 安德烈亚斯·格隆茨："十五五"规划涵盖了许多与欧洲市场息息相关的主题，例如重点关注科技创新、高质量发展、可 持续发展等。我对中国经济一直充满信心，中国企业具有创新精神、务实高效，中德两国企业合作潜力巨大。 国际货币基金组织总裁 格奥尔基耶娃：中国经济以创新为引擎展现强劲韧性，政策制定者采取了负责任的措施来支持经济。中国创新经济活跃，转型潜力 大，这正是国际货币基金组织上调中国2025年经济增速预期的原因。"十五五"规划彰显了以人民为中心的价值理念，我要向中国领导人表示敬意。将中国建 设成为开放和负责任的经济体，让我深感钦佩。 澳大利亚公民党全国主席 罗伯特·巴威尔：中国的发展相当出色，中国强调高质量发展是极具重要性的一步，不仅在提升本国人民的生活水平，还为世界其 他地区创造了机遇。我更欣赏的是中国能够始终坚持向着目标前进，而且深知如何稳步推动发展，中国是全球经济中极具确定性的存在。 (责任编辑：王晨曦) 印度尼西亚经济改革中心执行董事 穆罕默德·费萨尔：我认 ...

在美国众议院科学委员会听证会上，能源部负责科学事务的副部长详细介绍了以人工智能为核心的"创 世纪计划"投资，包括3.2亿美元用于"美国科学云"和模型联盟，并强调量子计算与核聚变为重点方向。 在美国众议院科学委员会听证会上，能源部负责科学事务的副部长详细介绍了以人工智能为核心的"创 世纪计划"投资，包括3.2亿美元用于"美国科学云"和模型联盟，并强调量子计算与核聚变为重点方向。 责任编辑：张俊 SF065 责任编辑：张俊 SF065 ...