最近，物流圈被"人形机器人分拣"的视频刷了屏：一群憨态可掬却动作敏捷的人形机器人，搬着包裹在仓库里穿梭，精准停靠货架、自动完成取放 ——不少老板看了眼热：" 这效率也太高了！我们是不是也该买一批？ " 物流分拣的 " 痛点 " 人形机器人能解决吗？ 先别急着跟风，我们得先搞清楚：你的仓库是否真的需要人形机器人分拣？它能解决哪些核心痛点？ 传统物流分拣面临三大难题： • 人力成本高企且效率瓶颈明显： 分拣员每天步行数万步，高峰期加班加点仍难免出错，人效天花板清晰可见； • 柔性不足，应对波动能力差： 大促期间临时增派人手难，仓库布局调整后，传统分拣线改造周期长、成本高； • 数据断层，管理决策滞后： 包裹流向、分拣进度全靠人工记录，无法实时同步到管理系统，调度效率低。 但冷静下来会发现，真正的问题不是"买不买人形机器人"，而是"买了之后怎么用"：仓库布局不规则怎么办？不同尺寸包裹怎么识别？人形机器人 和现有分拣系统怎么联动？数据安全怎么保障？ 如果只盯着"人形机器人"这个硬件，很可能陷入"买得起、用不转、 ROI（投资回报率）上不去"的困境。而这，正是未可知人工智能研究院深耕的 领域——我们不只是卖设备，更是为 ...

Core Viewpoint - The article discusses the shift from traditional SEO (Search Engine Optimization) to GEO (Generative Engine Optimization), emphasizing the importance of being mentioned by AI platforms like ChatGPT and others to enhance brand visibility and engagement in the evolving digital landscape [1]. Company Overview - Peec AI is a Berlin-based AI search platform startup founded in 2025, focused on creating AI search analysis tools for marketing teams to improve brand exposure and conversion on platforms like ChatGPT and Perplexity [3]. - Within just five months of its establishment, Peec AI secured €7 million in funding across two rounds, with weekly revenue growth of €80,000 [3]. - The company employs a small team covering product development, AI research, data analysis, and customer management, monitoring thousands of AI search dialogues daily across over 10 countries [3]. Founding Team - The founding team consists of Marius Meiners (CEO), Tobias Siwona (CTO), and Daniel Drabo (CRO), who have diverse backgrounds in entrepreneurship, technology, and market operations [4][5][6][7]. - Marius Meiners transitioned from a professional esports player to a software engineer and has experience in startup financing and mergers at PwC [5]. - Tobias Siwona is a serial entrepreneur with expertise in building AI and consumer tech products from the ground up [6]. - Daniel Drabo has a legal background and has previously run a ramen food truck and founded a LegalTech company [7]. Product Features - Peec AI stands out by offering features such as keyword suggestion generation, allowing users to avoid the hassle of brainstorming prompts themselves [9]. - The platform enables multi-platform tracking, allowing users to monitor various AI search platforms simultaneously, thus simplifying the process [10]. - It provides precise source tracking down to the specific URL, helping brands assess potential collaboration opportunities [11]. - Peec AI offers a transparent pricing model, with an entry-level plan starting at $89 per month, significantly lower than competitors [12]. - The platform allows unlimited user seats, making it cost-effective for larger marketing teams [13]. Client Success Case - SoftPro, a European SaaS company, utilized Peec AI to analyze its brand mentions on AI platforms, discovering a low mention rate of 15% on ChatGPT compared to competitors [15]. - After adjusting their marketing strategy based on Peec AI's insights, SoftPro increased its mention rate on ChatGPT from 15% to 42% and on Perplexity from 0% to 27%, resulting in a 166% growth in registered users from AI searches [15]. Industry Insights - The article highlights the transition from SEO, which focuses on keyword rankings, to GEO, which emphasizes brand mentions by AI, indicating a significant shift in how brands need to approach digital marketing [18]. - The potential for GEO solutions in the Chinese market is noted, with the company aiming to help brands appear not only in traditional search results but also in recommendations from new AI assistants [18].

Core Viewpoint - The training conducted by Zhang Ziming emphasized the integration of AI technologies into the fund industry, highlighting the importance of AI in enhancing operational efficiency and decision-making processes. Group 1: AI Development and Application - Zhang Ziming outlined the evolution of AI technology from its early stages to its current applications, focusing on the distinction between generative AI, which emphasizes content creation, and decision-making AI, which focuses on optimizing decisions [3]. - The training included a detailed explanation of structured prompt engineering frameworks such as CO-STAR, TCREI, and CRISPE, demonstrating how to generate high-quality marketing content for funds using the RBTR method [3]. Group 2: Fund Marketing Techniques - Practical techniques for generating marketing content, images, and videos using AI were showcased, with participants experiencing the entire process from market analysis to complete marketing copy generation [3]. - Zhang Ziming demonstrated the use of DeepSeek to analyze fund product selling points and quickly generate attractive marketing content related to trending themes like carbon neutrality [3]. Group 3: Investment Research Empowerment - The training introduced professional AI tools like Reportify and Alpha派, showcasing their applications in data collection, information organization, and visual analysis, significantly enhancing the efficiency of investment research personnel [4]. - Zhang Ziming emphasized that AI is not meant to replace investment researchers but to free them from tedious information processing, allowing them to focus on value judgment and decision-making [4]. Group 4: Future Directions of AI in Business - The Unforeseen AI Research Institute aims to assist more enterprises in achieving "AI+" strategic transformation, maintaining competitive advantages in the era of intelligence through dual-driven strategies of "AI strategy + technology empowerment" [6].

最近逛商场、进学校，你是不是总能被一群"萌酷担当"吸引——它们摇头摆尾、会打招呼，还能精准互动，没错，就是当下爆火的 机器狗 迎宾 。 从必胜客门店里主动上前"说欢迎词"的机器狗，到商场中庭吸引小朋友围观点赞的互动机器人，这些科技感十足的"新员工"，不仅成了品牌 的"流量密码"，更悄悄改变着用户体验的打开方式。 不少企业老板看到这波热潮，也想给自己的品牌"安排上"，但一动手就犯了难： 直接买机器狗？市场上型号五花八门，功能参差不齐，怕 买错了用不了；买来之后怎么控制？怎么让它说品牌专属话术、做定制动作？怎么和门店系统联动？ 一连串问题下来，热情瞬间浇灭一半。 别担心！你的"机器狗迎宾落地难题"，交给 未可知人工智能研究院 就对了！我们带来 机器狗迎宾整包解决方案 ，从选品到落地再到运 维，全程"一条龙"服务，让科技营销轻松落地。 不是"买机器"，是"做方案"：我们的整包服务有多全？ 很多企业以为机器狗迎宾只是"买个硬件"，但真正的核心在于"软硬件协同+场景定制"。我们的方案，拒绝"一刀切"，从需求出发打造专属 体验： 1. 需求诊断：精准匹配场景 ——先别急着选机器！我们的团队会第一时间上门，了解你的使用场景 ...

Core Viewpoint - The article emphasizes the transformative impact of AI, particularly ChatGPT, on the e-commerce landscape, highlighting the necessity for brands to adapt to this shift in consumer behavior and optimize their visibility through Generative Engine Optimization (GEO) [1][4][22]. Group 1: Impact of AI on Consumer Behavior - Consumers are increasingly using AI tools like ChatGPT to discover products, leading to a significant increase in conversion rates for retail websites, from 6% to 11% year-on-year [4][22]. - The shift from traditional search methods to conversational AI means that brands must ensure their products are recognized and recommended by AI to avoid losing potential customers to competitors [3][6]. Group 2: Importance of GEO - GEO (Generative Engine Optimization) is identified as a crucial strategy for brands to enhance their presence in AI-driven environments, allowing for better product recommendations and visibility [8][12]. - Brands that optimize their content for AI can ensure that their products are included in AI recommendations, thus increasing their chances of being seen and purchased by consumers [10][18]. Group 3: Implementation of GEO Strategies - The process of GEO involves comprehensive research on brand positioning, product features, and target user profiles to tailor content that aligns with consumer inquiries in AI platforms [13][15]. - Continuous monitoring and adjustment of strategies are essential to maintain relevance and competitiveness in the evolving AI landscape, ensuring brands adapt to changing consumer behaviors and preferences [18][20]. Group 4: Call to Action - The article concludes by urging brands to adopt GEO services to capitalize on the growing trend of AI in e-commerce, warning that failure to do so may result in being overshadowed by competitors who effectively utilize these strategies [22][24].

近日，未可知人工智能研究院院长杜雨博士应邀为 国家能源集团 开展主题为 "AI赋能能源行业智能化转型：创新趋势与实践应用" 的企业内训。此次培 训聚焦人工智能在能源行业的最新发展趋势、核心技术突破及落地应用场景，吸引了集团各业务板块的管理与技术骨干参与。 培训中，杜雨博士结合 国家电网、南方电网、华为云、施耐德电气 等国内外典型案例，深入剖析了AI在智能巡检、功率预测、客服系统、能源管理等场 景中的成熟应用。他特别提到，由未可知人工智能研究院持续关注的国产大模型代表——DeepSeek，正以其高效低成本的训练优势，加速AI在能源等垂 直行业的落地进程。 杜雨博士从宏观、中观、微观三个维度系统讲解了AI如何重塑能源产业格局。他指出，当前全球AI产业正处于快速发展期，生成式AI作为新一轮技术革 命的核心引擎，正深刻改变传统行业的生产方式与服务模式。 尤其在能源领域，AI不仅在资源勘查、发电调度、电网运维等环节实现降本增效，更在推 动"双碳"目标落地、构建新型电力系统中发挥关键作用。 " AI不是未来的技术，而是当下的生产力。 "杜雨博士强调，能源企业应积极拥抱AI技术，从顶层设计到业务场景逐步推进智能化转型，构建 ...

Core Insights - The article highlights the rapid adoption of robotic dogs in various industries, emphasizing their role in enhancing operational efficiency and safety during inspections [1][3]. Group 1: Advantages of Robotic Dogs - Robotic dogs address three major pain points in traditional inspection methods: cost reduction and efficiency improvement, safety assurance, and flexible adaptability to uneven terrains [3]. - A single robotic dog can replace 1-2 inspection personnel, saving companies tens of thousands in labor costs annually and increasing efficiency by over 300% with 24/7 operation [3]. - Robotic dogs can operate in hazardous environments, reducing the risk of human injury [3]. Group 2: Challenges in Implementation - Companies face difficulties in effectively utilizing robotic dogs due to the variety of brands and performance discrepancies, leading to challenges in selecting the right model for specific scenarios [5]. - The complexity of route design for inspections makes it hard to manage, as traditional manual setups are time-consuming and prone to errors [5]. - The vast amount of data generated by robotic dogs often goes unanalyzed due to a lack of professional data analysis capabilities within companies [6]. Group 3: Comprehensive Solutions Offered - The company provides a full-service solution that includes selection, deployment, operation, and iteration of robotic dog technology, ensuring they become effective inspection tools for businesses [8]. - The solution emphasizes precise selection of robotic dogs tailored to the specific needs of the enterprise, including customized hardware modifications for enhanced data collection [10][12]. - An intelligent deployment system automates route planning and allows for dynamic adjustments, enabling real-time responses to changes in the inspection environment [13][15]. - The AI data analysis platform processes collected data for proactive maintenance, transforming operational strategies from reactive to preventive [17]. Group 4: Benefits of the Comprehensive Solution - Companies can expect reduced labor costs, improved inspection efficiency, and enhanced fault prediction capabilities, minimizing production losses due to equipment failures [17]. - The service includes ongoing upgrades and optimizations to keep the solution aligned with technological advancements and business growth [17][20].

Core Viewpoint - The article emphasizes the importance of Generative Engine Optimization (GEO) for brands to be visible in AI search results, highlighting that traditional content marketing strategies are ineffective in the AI-driven landscape [3][10]. Group 1: The Challenge of AI Visibility - Many brands are struggling to be found in AI search results despite significant investments in content marketing [1][4]. - There is a misconception that popular human-centric content will automatically rank well in AI searches, which is not the case [5][9]. Group 2: Understanding GEO - GEO is not just about publishing articles; it involves structuring content according to AI preferences and ensuring it is published on platforms that AI prioritizes [10][11]. - The first step in GEO is to decode AI's content preferences, which include structured information, precise keyword matrices, and authoritative sources [12][14]. - The second step is to publish content on high-priority information sources that AI is more likely to crawl, such as authoritative industry platforms [14][16]. Group 3: The Urgency of Adopting GEO - The window for capitalizing on AI traffic is limited, with only about 15% of companies currently recognizing the importance of GEO [16][18]. - The algorithms for generative AI are still evolving, making it easier to optimize content now rather than later when competition increases [16][18]. - User behavior is shifting, with 72% of users preferring AI-generated summaries over multiple webpage clicks, making it crucial for brands to be included in AI's answer database [16][18]. Group 4: GEO Services Offered - The company provides customized GEO services, including AI search diagnostics, content optimization, high-priority publishing strategies, and data tracking for continuous improvement [18][19]. - The effectiveness of these services is demonstrated by helping 128 clients achieve top 10 rankings in AI searches, with average exposure increasing by 5-10 times and consultation volume growing by 150-300% [21].

近日，腾云Ai俱乐部正式宣布聘任未可知人工智能研究院副院长张孜铭为特聘导师。此次聘任是对张孜铭副院长在人工智能领域深厚学术素养与丰富 产业实践的 高度认可 ，也标志着未可知人工智能研究院在 推动AI产学研融合与生态共建 方面再获重要突破。 腾云Ai是一个 专注于AI领域的企业家社群平台 ，由腾云人工智能研究院运营，主要面向高净值商业人群提供AI技术应用、产业资源对接和商业机会 挖掘服务。其核心服务包括组织AI标杆企业游学、发布行业榜单、举办大型AI创业大会等，帮助成员快速掌握AI技术趋势并实现商业落地。 张孜铭副院长专注于 AI技术在垂类业务场景的应用培训与解决方案落地 ，拥有北京大学与新加坡国立大学双硕士学位，以及华中师范大学（信息管 理与信息系统）和华中科技大学（计算机科学与技术）双学士学位的复合学术背景。著有《AIGC：智能创作时代》、《DeepSeek使用指南：全职 业场景应用实践》、《AI for Science：人工智能驱动科学创新》等多部影响广泛的著作，同时也为华润置地、邮政集团、国家电网、南方基金等多 家知名机构提供AI战略咨询服务。 此外，张孜铭副院长还作为重要参与者参与了由国家工业信息安全 ...

近几年，机器狗凭借其灵活的动作、酷炫的外观，迅速成为商业宣传活动中的"新宠"。从商场开业到品牌发布会，从节日庆典到地标打卡，一场精彩的机 器狗群表演总能瞬间引爆现场氛围，吸引无数目光，其热度不亚于当年火遍全网的无人机表演。 但对于不少对这个行业不太了解的品牌主而言，想要打造一场成功的机器狗群表演，却面临着诸多困惑：直接买机器狗成本太高？买来后不知道如何实现 精准群控？表演动作设计毫无头绪？场地协调与技术保障更是无从下手？ 别担心！这些难题， 未可知人工智能研究院 都能为你轻松解决。我们专注于人工智能技术在商业场景的创新应用，针对品牌campaign活动推出机器狗群 表演 全套软硬件整包方案 ，从创意策划到现场执行，一站式服务让你省心、省力、更省钱！ 为什么不建议品牌主直接买机器狗？ 很多品牌主最初会考虑直接购买机器狗，但深入了解后就会发现其中隐藏着不少问题： 成本高昂且利用率低 ：高性能机器狗单价不菲，一场群表演少则十几只，多则上百只，前期采购投入巨大。而大多数品牌的机器狗表演需求仅为单 次或短期活动，活动结束后机器狗长期闲置，造成资源浪费和资金沉淀。 群控技术门槛高 ：机器狗群表演的核心在于精准的群控系统， ...