Group 1 - The A-share market experienced a rise and then a decline, with the Shanghai Composite Index briefly increasing over 1% before turning negative in the afternoon [2] - The AI application sector saw significant growth, with companies like Liou Co., Ltd. achieving six consecutive trading limits in nine days, and others like Shengguang Group and Youyou Network also performing strongly [2] - The Ministry of Industry and Information Technology released a plan for the high-quality development of industrial internet platforms from 2026 to 2028, aiming for over 450 influential platforms and a connection of over 120 million industrial devices by 2028 [2] Group 2 - Huayuan Securities' report emphasizes that AI remains a crucial direction in global industry narratives, focusing on product implementation with revenue-generating applications [3] - Generative AI products are becoming core entry points for information acquisition, leading to a new marketing paradigm that enhances brand visibility and authority in AI-generated responses [3] - The current AI application model is still in its early stages, and companies that are rapidly advancing their strategies should be closely monitored [3]

（原标题：AI企业范式智能推GEO服务 抢占生成式AI时代品牌话语权） 随着全球消费者越来越习惯"问AI"做购买决策——从家用电器到专业服务，答案背后的信息来源正成为 品牌新战场。人工智能企业范式智能今日正式推出"生成式引擎优化"(Generative Engine Optimization， 简称 GEO)服务，旨在帮助品牌在大模型推理过程中提升可信度与被引用概率。 范式智能创始人兼CEO戴文渊与首席研究科学家陈雨强，曾共同主导百度"凤巢"系统开发——中国首个 大规模商用机器学习广告平台，也被视为全球最早将深度学习应用于商业变现的AI引擎之一。该经验 被视为GEO理念的雏形：如何在算法推理中平衡商业价值与用户体验。 此次推出的GEO服务涵盖四大模块：策略设计、知识工程、效果度量及生态协同，已对接主流大模型 平台，支持动态更新与合规治理。公司表示，过去十年深耕金融、医疗、制造等高复杂度行业，使其具 备将真实业务逻辑映射为AI可处理信号的工程能力。 分析指出，在生成式AI成为下一代流量入口之际，品牌影响力正从"曝光量"转向"知识可信度"。范式智 能此举，或标志着中国科技企业开始定义AI时代的新型数字基建标准。 ...

1月14日，《国际金融报》记者获悉，"新经济SaaS第一股"微盟集团（2013.HK）近日正式上线了 自研生成式引擎优化（GEO）解决方案——"微盟星启"。 据介绍，"微盟星启" 采用基于AI搜索意图的非线性逻辑，通过大模型驱动的全链路数据监控与诊 断、智能化内容生成与智能匹配分发等技术，帮助品牌在AI平台中完成"捕捉（Catch）、监测 （Monitor）、策略（Strategy）、执行（Execute）"，打造从用户意图捕捉、AI可见度诊断、内容策略 规划、创作及分发的GEO全链路营销闭环，系统性提升品牌在AI对话中的可见度，让品牌在AGI时代全 流程获得更高曝光被AI优先看见、推荐，从而让消费者选择。 微盟方面表示，AI 搜索正在全面重构流量生态。立足自身在 SaaS 和精准营销领域的技术优势与客 户资源，微盟集团将紧跟产业机遇，聚焦 AI 生成式应用生态，抢先布局未来流量新形态，持续发掘 AI 流量场景下的企业服务新机会。此次自研核心技术并上线 "微盟星启"，标志着微盟进一步完善了 "AI + 营销" 业务布局，完成了面向未来品牌营销万亿赛道的技术生态卡位，亦是集团 "All in AI" 战略的进一 ...

| 上证指数 | 深证成指 北证50 | | --- | --- | | 4188.24 | 14449.57 1611.99 | | +49.48 +1.20% +280.18 +1.98% +46.41 +2.96% | | | 科创50 | 创业板指 万得全A | | 1524.03 | 3396.35 6900.67 | | +54.46 +3.71% +74.47 +2.24% +128.08 +1.89% | | | 沪深300 | 中证500 中证A500 | | 4812.48 | 8360.89 5990.97 | | +51.45 +1.08% +217.61 +2.67% +89.76 +1.52% | | | 中证1000 | 深证100 中证红利 | | 8410.43 | 6000.77 5613.55 | | +207.29 +2.53% +81.79 +1.38% +21.58 +0.39% | | | 万得全A涨跌分布 | | | 跌575 | 涨4753 | | 成交额2.25万亿 | 预测成交额3.50万亿,缩2023亿 | 从板块来看，AI应用方向领涨市场，互联网、软件 ...

Core Insights - The GEO (Generative Engine Optimization) concept has seen a resurgence in trading activity, with notable stocks like ZhiDeMai rising by 20%, continuing to reach new highs, and accumulating over 80% gains in the last four trading days [1] - The GEO market, driven by AI search technologies, is projected to reach a scale of $10 billion, as traditional search engine traffic is expected to decline by 25% by 2026, with market share shifting towards AI chatbots and virtual agents [1] - Companies in the advertising sector are anticipated to transition from providing marketing services to offering technology services, enhancing profitability [1] Industry Analysis - AI remains a critical narrative in global industries, with a focus on applications that have revenue structures [1] - Generative AI products are becoming core entry points for information acquisition, leading to a new migration of traffic [1] - GEO is expected to adapt to the new marketing paradigm of the AI era, optimizing content's semantic expression, structural form, credibility, and multimodal adaptability to enhance brand visibility and authority in AI-generated responses [1] - The GEO model is still in its early stages, and companies that are rapidly advancing their layouts should be closely monitored [1]

1）1月13日，据彭博社援引知情人士透露，随着雷朋Meta眼镜销售势头强劲，Meta已建议EssilorLuxotticaSA到2026年底 将年产能提升至2000万副或以上。双方还讨论了如果需求足够强劲，将进一步建立3000万副以上的产能。 2）苹果、谷歌、字节跳动等巨头加速布局，苹果计划2026年WWDC公布AppleGlasses，谷歌重启独立AI眼镜项目，字节 跳动首款AI眼镜预计2026年一季度发布。 三、机构解读 1）随着以Meta为代表的AI眼镜产品销量持续攀升，国内外厂商积极入局，AI眼镜有望成为下一款千万级至亿级销量的终 端产品。根据WellsennXR预测，未来全球AI眼镜销量将持续增长，到2030年销量有望达到9000万副，6年CAGR为 97.42%。（开源证券） 一、行情 1月14日，AI眼镜板块早盘迎来集体走强。翰博高新（20CM）、比依股份、博士眼镜（20CM）等纷纷涨停，明月镜片、 佰维存储、国科微、天健股份、虹软科技等集体大涨。 | 股票名称 | 最新价 = | 活的原则是一 | | --- | --- | --- | | 翰博高新 301321.SZ 减持 | | 首板 | ...

Core Insights - Fudan University has launched the AI3A education co-creation platform and released the "Guidelines for the Application of Generative Artificial Intelligence in Education" to integrate AI into teaching while fostering innovation and maintaining ethical boundaries [1][2][9] Group 1: AI Application Guidelines - The guidelines provide detailed action suggestions, ethical warnings, and tool recommendations for various educational scenarios, including classroom teaching and academic evaluation [2] - The focus is on how students use AI tools rather than just the correctness of results, emphasizing the importance of process documentation and responsible use [2][3] - The guidelines aim to ensure that AI assists in tasks like language polishing but does not replace core academic work such as research conception and data analysis [2][3] Group 2: AI3A Platform Features - The AI3A platform includes a teaching case library, practical learning platform, and a collection of global AI case studies, designed to support a progressive learning path [4][5] - The platform encourages collaboration across disciplines, allowing students and teachers to share and build upon each other's AI educational experiences [4][5] - It features over 100 exemplary practices in AI education developed by faculty and students, showcasing innovative course designs and applications [5][6] Group 3: Educational Transformation - The integration of AI into education is seen as a transformative opportunity rather than a challenge, with the potential to enhance educational quality [9] - The collaborative model between students and teachers is fostering interdisciplinary research and innovation, breaking down traditional academic silos [7][8] - The platform aims to help educators adapt to AI technologies, promoting a new ecosystem of education that combines AI with existing academic strengths [7][8]

计算的炼金术 JENSEN HUANG | FOUNDER & CEO 英伟达CES 2026 / PART 1: 物理AI革命 COMPUTING its ACCELERATED COMPUTING 加速计算 "每隔十年到十五年,计算行业会迎来新的平台变革。但这次,是两个。" 一个历史时刻:两场平台变革同时发生 APPLICATIONS GENERATIVE AI 生成式AI 整个技术栈,全面重闷 CODE PRE-COMPILED ■ TRADITIONAL APPLICATION-FIRST 不再是预编译，而是实时生成每个像素与Token MODE 不再编写软件代码，而是训练软件模型 不再运行在CPU上，而是运行在GPU上 GENERATED ACCELLERATED 每次计算都因加速计算被彻底重塑 ALFIRST 不再是构建应用，而是在AI之上构建新应用 被现代化的计算价值。 资金来源：[研发预算的转移（FROM TRADITIONAL METHODS TO AI METHODS） @10 000 000 000 000 � 10,000,000,000,000 测试时扩展（TEST-TIME SCA ...

Core Viewpoint - The company has actively revised its logic regarding "DAU/traffic = barrier," recognizing that the only moat in the AI era is the intellectual advantage of models. By reducing inefficient ToB sales teams and C-end user acquisition costs, resources are intensely focused on high-intensity model research and technological breakthroughs. This "anti-consensus" contraction is essentially a strategic move to gain an edge in the second half of the Scaling Law, focusing on reasoning and architectural innovation. The management team possesses top-tier research and ToB commercialization and delivery experience [1]. Industry Transformation - AI is defining a new generation of productivity, with the Total Addressable Market (TAM) shifting from software budgets to labor budgets. The industry is undergoing a qualitative change from discriminative AI to generative AI. The Scaling Law is driving exponential improvements in model intelligence while reasoning costs are decreasing exponentially, making AI not just a traditional SaaS "tool" but a "digital employee" with reasoning and planning capabilities. For instance, the traditional software market targets about $300 billion of IT budgets, while AI, as a production factor, is expected to penetrate a global labor cost market of approximately $13 trillion [1]. Technical Evolution - The technical path is evolving, with increasing engineering barriers and a gradual consolidation of model frameworks. The extensive pre-training Scaling (computational power/data) is facing diminishing marginal returns, leading the industry into a new phase of "architectural innovation & reasoning-side Scaling." Companies like DeepSeek (MLA/architecture compression) and Google (multimodal association) represent different technical breakthrough directions, with technical barriers returning to a combination of "engineering capability + architectural innovation" [2]. Company Advantages - The MiniMax team benefits from a founder with both research capabilities and ToB delivery experience. The founder, Yan Junjie, previously served as Vice President of SenseTime and CTO of the Smart City Business Group, demonstrating exceptional technical and management skills. Under his leadership, a team of over 700 achieved industry-leading facial recognition algorithms, with the smart city business generating over 2 billion RMB in revenue in 2021, targeting government and large enterprises with a focus on engineering delivery. Unlike the mobile internet era, the management team understands that "user scale ≠ model intelligence." Therefore, the company's strategic focus is shifting from "revenue generation/user acquisition" to "technological iteration" by 2025 [3]. Financial Projections - The company expects to achieve revenues of $80 million, $185 million, and $351 million for FY25-27, representing year-on-year growth of 162%, 131%, and 90%. AI-native product revenues (To C) are projected to be $58 million, $139 million, and $263 million, with growth exceeding 140%. Open platform revenues (ToB) are expected to be $22 million, $46 million, and $88 million. As reasoning costs optimize and high-margin ToB business stabilizes, Non-GAAP gross profits are projected to be $20 million, $74 million, and $193 million, corresponding to Non-GAAP gross margins of 25.0%, 40.0%, and 55.0%. Despite ongoing competition in computational power, Non-GAAP net losses are expected to narrow, recording losses of -$240 million, -$180 million, and -$80 million for FY25-27, with a significant trend of decreasing loss rates [4]. Investment Logic - Within the AI sector, the investment logic between the "infrastructure layer (e.g., DeepSeek)" and the "native application layer" is diverging. Compared to DeepSeek, which establishes barriers on the cost side through architectural innovation, MiniMax's deep focus on multimodal (voice/video) interaction experience provides a stronger moat in user stickiness and commercialization. The integration of "high-sensory interaction" and "productivity tools" is key, with the former (Talkie/Xingye) providing vast RLHF data and the latter (Hailuo/open platform) generating high-margin cash flow. Greater revaluation potential lies in the technological unlocking in the second half of the Scaling Law. As the company's strategic focus returns to technological research, new multimodal models (e.g., Video-01, end-to-end voice) are expected to significantly contribute to incremental ARR starting in FY26-27 [5].

Core Viewpoint - Apple has announced a strategic partnership with Google in the field of artificial intelligence, confirming the integration of Google's Gemini large model and cloud technology into future foundational models and the new version of Siri [1][10]. Group 1: Strategic Implications - This collaboration is seen as a critical move for Apple in the generative AI era, accelerating the system-level implementation of AI capabilities while maintaining system control and privacy principles [2][11]. - The partnership is not unexpected, as prior discussions hinted at potential collaboration between Apple and Google following Apple's alliance with OpenAI [2][11]. - Following the announcement, Alphabet's stock price surged, marking its market capitalization surpassing $4 trillion for the first time, joining the ranks of Nvidia, Microsoft, and Apple [2][11]. Group 2: Market Dynamics - Elon Musk has publicly commented on the partnership, expressing concerns about potential power concentration due to Google's control over Android and Chrome [2][11]. - Apple's AI deployment in the Chinese market remains uncertain, with local collaboration plans under scrutiny due to regulatory requirements [6][12]. Group 3: AI Development Strategy - Apple's choice to collaborate with Google does not indicate a departure from its self-research path but reflects a strategic balance based on current realities [4][14]. - The increasing complexity and capital intensity of generative AI development have made it a more viable option for Apple to leverage established large model capabilities to expedite AI functionality [5][14]. - Apple's focus on AI emphasizes enhancing user experience, integrating AI capabilities into iOS and macOS rather than offering them as standalone products [5][15]. Group 4: Dual Strategy - Apple is adopting a "dual-track strategy" by collaborating with companies like OpenAI and Google to quickly address capability gaps in global markets while proceeding cautiously in key regions like China to ensure compliance [7][16]. - The partnership with Google is significant not only for Apple but also represents a pivotal moment for Google, enhancing its AI technology's reach to over 2 billion Apple devices globally [8][17]. Group 5: Industry Trends - The competitive landscape in AI is shifting from focusing on model parameters and performance to embedding AI capabilities into various ecosystems at lower costs and higher stability [8][17]. - The collaboration between tech giants is becoming a more efficient choice in the capital-intensive and rapidly evolving AI sector, as seen in partnerships like Microsoft with OpenAI and Amazon with Anthropic [9][18].