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].

Summary of Baifengyun Conference Call Company Overview - Baifengyun reported a net profit exceeding 200 million yuan in the first half of 2025, with a net profit margin of 12% and an adjusted margin of 16, indicating strong profitability [2][3] - The company employs approximately 1,400 staff, with 57% in R&D, and an average annual income exceeding 2 million yuan, reflecting a strong emphasis on R&D and high-value talent [2][3] - Baifengyun has served over 8,000 institutions, including banks, internet finance companies, and major internet firms like Alibaba and Baidu, showcasing a broad client base [2][3] Business Structure and Core Advantages - The business is divided into two main segments: Model as a Service (MaaS) and Business as a Service (BaaS) [3] - **MaaS** contributes about one-third of total revenue, providing decision-making support for financial institutions through AI technology, with over 300 million daily calls [2][3][4] - **BaaS** accounts for approximately two-thirds of revenue, utilizing intelligent voice robots for sales and customer operations, relying on generative AI technology [2][3][5] - The launch of the Cyber Star platform aims to enhance internal efficiency across various sectors, significantly reducing contract review times [2][9] Financial Performance - Baifengyun has maintained stable revenue growth of over 20% annually in recent years, with the first half of 2025 exceeding expectations [12] - The BUS financial cloud business saw a 45% year-on-year revenue growth in the first half of 2025, driven by the expansion into broader financial scenarios [14] Market Dynamics and Challenges - The company faces policy uncertainties impacting performance, particularly in the insurance sector, which has shown negative growth since 2024 due to regulatory pressures [13][14] - Despite these challenges, Baifengyun remains optimistic about long-term prospects, having demonstrated resilience in past downturns [13][22] Technological Innovations - The intelligent voice robot technology has proven effective in enhancing customer communication efficiency, with cost reductions to one-fifth of human labor costs and achieving 99% accuracy in voice recognition [7][8] - Baifengyun differentiates itself by utilizing a strong mathematical foundation for user segmentation, focusing on vertical small models rather than general large models [8] Future Outlook - The company plans to continue investing in R&D, with a 30% increase in spending in the first half of 2025, focusing on AIGC and computing clusters [19] - Baifengyun aims to expand its AI business into non-financial sectors, anticipating gradual increases in revenue contribution from these areas [19] Conclusion - Baifengyun is positioned as a resilient player in the AI technology sector, with a commitment to long-term growth despite short-term challenges, maintaining confidence in its strategic direction and market adaptability [22]

近日，未可知人工智能研究院副院长张孜铭受邀出席 "2025年科普服务能力提升之人工智能科普辅导活动" 。 本次活动 由杭州市科学技术协会主 办、杭州市人工智能学会承办，旨在锻造基层科协干部和科普工作者的科普活动组织力与创新力，加快适应新时代科普工作要求。全市220余名 科普骨干参加了本次专题学习。 本次活动的核心环节，由张孜铭副院长为全体学员带来了题为 《AI趋势洞察与工具实战应用》 的精彩分享。他从基础概念入手，系统讲解了当 前人工智能的发展脉络。通过深入对比解析生成式AI与决策式AI的核心区别，并结合详实的全球AI市场数据，明确指出生成式AI已成为驱动科 普内容创新的核心引擎。这一论断为科普工作者理解AI价值提供了清晰的方向。 针对学员们普遍关心的"如何选择AI工具"这一现实问题，张孜铭副院长进行了细致的对比分析，重点剖析了DeepSeek、文心一言、通义千问等主 流国产AI工具的特点，指出不同工具在应用侧的差异主要体现在产品生态与功能设计上。 更为重要的是，结合科普工作的具体场景，张孜铭副院长分享了AI工具的实操逻辑与应用技巧。他强调，科普工作者应根据具体场景精准选择工 具功能，让AI技术真正成为提升科 ...

近日，未可知人工智能研究院成功举办了民营企业家AI战略工作坊，吸引了众多民营企业家的积极参与。本次工作坊聚焦于生成式AI与提示词 工程的基本原理、AI提示词实用技巧与工作应用，以及AI办公工具协同提升组织效能，旨在帮助民营企业家更好地理解和应用AI技术，提升企 业竞争力。 一、深度解析生成式AI与提示词工程 工作坊 第一天上午，未可知人工智能研究院副院长张孜铭先生为企业家们带来了精彩的分享。张副院长首先深入解析了生成式AI与决策式AI的 区别，指出生成式AI的核心在于生成新的内容，如AI绘画、生成对话等，而决策式AI则更关注如何做出满意决策，如人脸识别、风险管理等。 他还回顾了生成式AI的发展脉络，从早期的萌芽阶段到如今的快速发展，强调了技术进步对AI应用的推动作用。 在AI提示词技巧方面，张副院长详细介绍了提示词工程的重要性，并分享了多种实用技巧。他指出，提示词（Prompt）是为AI模型提供的输 入，通过设计和调整输入，可以有效改善模型性能、控制生成结果。他介绍了经典提示词框架如CO-STAR、TCREI、CRISPE等，并通过实际 案例展示了如何运用这些框架来优化AI生成内容。他还分享了如何通过符号划重 ...

近日， 未可知人工智能研究院副院长张孜铭老师受邀前往南方基金总部，开展了一场主题 为"DeepSeek+：企业的AI战略落地"的企业培训。 此次培训聚焦于 AI技术在企业战略中的应用与落地 ，旨在帮助南方基金的员工们深入理解AI 如何赋能企业运营、提升工作效率并推动业务创新，为企业的数字化转型提供有力支持。 张孜铭老师是未可知人工智能研究院副院长 ，北京大学与新加坡国立大学双硕士，著有 《DeepSeek使用指南》等多部作品，并参与起草了《生成式人工智能数据应用合规指南》等 行业标准。他在人工智能领域拥有深厚的学术背景和丰富的实践经验，为本次培训提供了坚实 的专业支撑。 培训中，张老师还分享了 未可知人工智能研究院在 AI培训、解决方案开发、咨询研究等方面 的丰富经验和成果。 他介绍了研究院的 专家团队 ，他们在人工智能领域拥有深厚的学术背景 和丰富的实践经验，为研究院的发展提供了坚实的人才支撑。 针对企业如何落地 AI战略，张老师提出了诸多建议。 他强调，企业应积极培养员工的AI技 能，掌握AI工具的使用方法；同时，要善于发现工作中的重复性任务，思考如何用AI替代，将 AI融入业务流程的标准化操作中。他还 ...