一些具备普遍性、共通性且在AI解题范围内的简单咨询，可以交给AI。同时，也要确保一些非常规、 可能难倒AI的需求能及时转人工，避免让用户陷入AI不灵又无人求助的困境。 在AI客服的使用上耍小聪明，企业可能因小失大。消费者维权无门，客服视而不见，过度追求降本很 容易陷入品牌与消费者信任损耗、口碑影响力下滑的恶性循环。 想转人工客服，难上加难？近日，据央视报道，通过对主流电商、社交、金融、物流等10多家平台客服 系统实测发现，无论是在线客服还是电话客服，AI客服都存在较明显的理解能力不足，而人工客服接 入障碍重重，严重影响用户体验。 在调查中，一边AI"听不懂"诉求，一边用户要转人工如"闯关"，这样的两难在现实中并不陌生。 而造成转人工难的原因之一竟是企业"人为"设置的。企业手握用户寻找人工客服难易程度的自主决定 权，有的企业主动利用AI设置拦截障碍。 "听不懂"有技术受限的客观原因，也可能存在企业有意压缩成本选用低版本应付的情况。 低价AI客户服务多是基础版本，面对复杂需求难免力不从心，而要升级相关服务却需要更新语料库优 化系统，这就不可避免要持续的资金投入，让有的企业动了歪脑筋。 人为设障则反映了一些企业不愿 ...

想转人工客服，难上加难？近日，据央视报道，通过对主流电商、社交、金融、物流等10多家平台客服 系统实测发现，无论是在线客服还是电话客服，AI客服都存在较明显的理解能力不足，而人工客服接 入障碍重重，严重影响用户体验。 在调查中，一边AI"听不懂"诉求，一边用户要转人工如"闯关"，这样的两难在现实中并不陌生。 而造成转人工难的原因之一竟是企业"人为"设置的。企业手握用户寻找人工客服难易程度的自主决定 权，有的企业主动利用AI设置拦截障碍。 "听不懂"有技术受限的客观原因，也可能存在企业有意压缩成本选用低版本应付的情况。 低价AI客户服务多是基础版本，面对复杂需求难免力不从心，而要升级相关服务却需要更新语料库优 化系统，这就不可避免要持续的资金投入，让有的企业动了歪脑筋。 人为设障则反映了一些企业不愿直面问题的心理。它们把降本增效当作"降服减效"，把技术当作压缩成 本的工具，忽视了用户诉求与服务质量。 众所周知，消费场景中AI客服广泛使用，本意是提高效率，帮助用户更快更好地解决问题。无论AI失 效无法有效读懂用户需求，还是企业有意避开人工服务，都与初衷严重背离。 北京商报评论员 陶凤 当今社会AI使用渗透之广，几 ...

户外炫光让机器人 "瞬间失明"、商场跌倒识别与小区宠物粪便排查等安防需求碎片化难解、100 元报销需 经八人审批 ……这些曾长期困扰空间运营的痛点，在12月12日上海国际传媒港举行的万物云睿见大会 2025"睿见・灵石" 圆桌论坛上，被一一拆解为 AI 赋能的鲜活实践。 这场以《存量时代的突围与共生：智慧空间的韧性考验》为主题的对话，汇聚了资产持有方、技术提供 方、物业服务方、与学术机构代表，在中央经济工作会议 "好房子建设" 与 "房地产发展新模式" 的政策导向 下，共同探寻存量资产盘活的核心密码。 政策锚点：存量博弈催生韧性新需求 万勋科技创始人王峥分享了机器人户外应用的突破："没有 AI 赋能前，工厂里表现优异的机器人，拿到室 外遇到炫光就会'失明'，瞬间回到史前时代。"AI 技术让机器人的光线识别能力提升 1-2 个数量级，低成本 的户外清洁、安防机器人得以普及，成功应对了环境不确定性带来的运营挑战。 高仙科技创始人程昊天则聚焦安防领域的碎片化困境："十年前安防机器人根本做不起来，商场要识别奔跑 跌倒、小区要排查违停与宠物粪便，需求太过多样，传统算法下成本高昂且难以解决。" 大模型与深度学习 技术的突 ...

▲一些平台人工客服接入障碍重重。图/央视新闻 不知道你有没有这样的经历？拨打客服热线或点开一个网站的客服功能，出现的总是一位AI客服。对话时，AI客 服听不懂话、解决不了问题，当你一遍一遍呼唤"转人工"的时候，等待的却是一次次的"对不起，人工座席目前全 忙"…… 据"央视新闻"报道，记者近日对主流电商、社交、金融、物流等10多家平台客服系统实测发现，无论是在线客服 还是电话客服，AI客服都存在较明显的理解能力不足，而人工客服接入障碍重重，严重影响用户体验。 听不懂人话，却擅长废话；"会说话的墙"与"失语的服务"……消费者可以说苦这种一点儿都不"智能"的AI客服久 矣。 AI客服不仅难以准确识别用户诉求，反而可能将简单问题复杂化，让用户的"求助"落空，并进一步加深用户的焦 虑与不满。这样的AI客服，非但未能成为沟通的"桥梁"，反倒异化为一堵阻碍服务和沟通的"围墙"。 客观说，企业追求降本增效无可厚非，如有服务商承诺"一个超级体客服可代替50个客服""一年节省费用60万 元"，这对多数企业都具有很大的"诱惑力"。但"降本"的重心应放在哪，"效"又该增在何方，却需要科学评估。 以AI客服代替人工服务，可能确实能大幅 ...

Core Insights - The rise of AI in music creation is transforming the industry, making music composition more accessible and leading to the emergence of AI-generated songs as a new trend [1][2][5] Group 1: AI Music Creation Competitions - NetEase Cloud Music has launched an "AI Music Creation Competition" with a total prize pool of 1 million yuan to encourage high-quality AI music submissions [1] - The trend of AI music creation is gaining traction, with various platforms like Doubao and QQ Music offering user-friendly AI music creation tools [2][5] Group 2: User Experience and Technology - Users can easily create songs by inputting simple ideas, and the AI can generate lyrics and melodies in a short time, showcasing the technology's efficiency [2][5] - The AI tools can produce songs across various genres, including pop, folk, electronic, and rap, demonstrating versatility in music creation [2] Group 3: Industry Impact and Collaboration - The collaboration between humans and AI in music creation is becoming a prominent feature, with competitions and initiatives highlighting this trend [7] - Music industry professionals emphasize that the evaluation of AI-generated music remains focused on quality, regardless of the technology used [7] Group 4: Challenges and Copyright Issues - While AI can produce quality music quickly, there are concerns regarding the originality and copyright of AI-generated works, as the creative process involves user input and algorithm execution [8] - The music industry faces challenges in establishing clear copyright ownership and fair profit distribution for AI-generated content [8]

Core Insights - The global technology competition is rapidly evolving, with cutting-edge technologies like AI, spatial computing, and human-machine collaboration reshaping production, lifestyle, and national competitiveness [1] - The 20th National Congress of the Communist Party of China emphasizes accelerating the development of new productive forces and strengthening the role of enterprises in technological innovation, placing "technology finance" as a top priority in building a strong financial nation [1] Development Challenges - Traditional AR glasses face commercialization challenges, with global sales projected at only 500,000 units in 2024, significantly below early market expectations [1] - The core issue lies in the "all-or-nothing" development paradigm, which creates a negative cycle of high R&D investment, high-cost pricing, low user acceptance, and immature supply chains [1][3] - This approach neglects critical variables such as market acceptance, user behavior inertia, and capital patience, making it incompatible with the new paradigm of "early, small, long-term, and hard technology" in technology finance [1] Evolution Path - A new "gradual iterative" paradigm is emerging, led by AI smart glasses, which is validating a three-stage evolution path: audio/camera glasses, AI smart glasses, and AI+AR glasses [2][5] - The first stage involves audio/video glasses that integrate basic functions to cultivate user habits without altering wearing preferences [5] - The second stage introduces AI capabilities for enhanced functionality, transforming devices from mere tools to intelligent companions, as evidenced by the success of Meta's Ray-Ban Meta glasses [7] - The third stage aims to incorporate lightweight AR display modules, achieving "what you see is what you get" spatial computing, supported by accumulated orders that drive down optical module costs [8] Market Logic - The "gradual iterative" approach targets a substantial existing market of over 1.54 billion units of traditional glasses sold annually, providing a natural user base for smart glasses [9] - This paradigm shift redefines smart glasses as "smart traditional glasses," significantly lowering decision-making barriers and facilitating market penetration [9] - Investment in the AR sector is transitioning from a technology risk-driven model to one focused on market validation, with significant funding increases observed in 2025 [9] Competitive Landscape - The global AR glasses market is evolving, with competition shifting from short-term hardware comparisons to long-term ecosystem building [11] - Companies like Meta and Google are adopting different strategies, with Meta focusing on a closed-loop experience and Google promoting an open ecosystem [11] - Domestic players are leveraging rapid hardware iterations and vertical market penetration, while larger companies like Huawei and Xiaomi are creating seamless cross-device experiences [11] Capital Mechanism - The evolution of AR glasses represents a microcosmic experiment in the collaboration of technology, finance, and institutional evolution [12] - The "gradual iterative" paradigm addresses structural mismatches between technological innovation and financial capital, allowing for phased value release mechanisms [14] - This approach enables capital to receive mid-term market feedback and cash flow support without sacrificing long-term visions, alleviating common challenges faced by early-stage hard technology projects [14] Future Outlook - The true revolution of consumer-grade AR glasses lies in redefining the relationship between humans, information, and the world, facilitating seamless integration of digital information into physical reality [16] - AR glasses have the potential to enhance social interactions, transforming them from social isolators to social enhancers, provided they are designed thoughtfully [17] - The successful adoption of AR glasses will depend on the establishment of ethical frameworks and institutional support to address privacy concerns and ensure equitable access [18]

一家机器人企业如果要再创业会选择哪里？全球机器人"四大家族"中的库卡、ABB等国际巨头给出了答 案，他们早已率先落子广东。特别是库卡，2017年被美的收购后，如今已在佛山顺德建成全国最大工业 机器人生产基地。 作为"世界工厂"，广东沉淀出的市场广度、产业厚度和迭代速度，正是令这里成为全球机器人落地的首 选试验场的原因。 每3台工业机器人就有1台"广东造"，工业机器人产量连续五年稳居全国第一；机器人相关企业超过16万 家，居全国第一。广东可以说是当之无愧的全国最大的智能机器人产业聚集区。 从全球机器人巨头如库卡、ABB纷纷落户广东，到本土创业者加速涌入，高校与企业协同攻关，推动 机器人成群结队"进厂打工"……我们会发现，如今谈及全球机器人创新，都离不开广东。 12月12日至14日，2025年粤港澳大湾区人工智能与机器人产业大会暨广东省人工智能与机器人技能大赛 在广州举行，汇聚多方资源，加速推动人工智能与机器人领域核心技术攻关与成果转化落地。 为什么全球机器人创新离不开广东？广东又将如何进一步打造独一无二的创新创业生态，实现在全球机 器人产业的新跃升？ 为什么是广东？ 全球机器人落地的首选试验场 时间回到2010 ...

Core Viewpoint - The seventh International Medical Robot Innovation Development Forum was successfully held, focusing on new opportunities and innovative breakthroughs in the medical robot industry [1] Group 1: Industry Development Insights - The Ministry of Industry and Information Technology emphasized significant progress in the domestic medical robot industry, highlighting breakthroughs in core component localization and key technology innovation [3] - Beijing has established a solid industrial foundation with over 1,000 production enterprises and a total output value exceeding 35 billion [4] - The medical robot industry is a key area of national strategy, with a focus on technological innovation and industry upgrades in the context of an aging population and the prevalence of chronic diseases [5] Group 2: Key Achievements Announced - Four major achievements were announced at the forum, covering enterprise cooperation, capital empowerment, talent cultivation, and industry research, providing multi-dimensional support for high-quality development in the medical robot sector [7] - The Beijing High-end Medical Equipment Industry Development Fund was launched to support high-end medical devices and intelligent equipment, leveraging local research and clinical resources [12] - The "Medical Equipment Industry Talent Job Capability Requirements" standard was released, filling a gap in the industry talent evaluation system [13] Group 3: Expert Discussions on Technological Trends - Experts discussed the innovative value of ophthalmic surgical robots, emphasizing human-machine collaboration to enhance precision in surgeries [18] - The construction of a precise treatment system for orthopedic robots was highlighted, focusing on minimizing surgical trauma and improving technology through collaboration with universities [21] - The importance of integrating environmental responsibility into surgical robotics was raised, advocating for sustainable medical practices [22] Group 4: Roundtable Discussions on Industry Challenges - A roundtable discussion emphasized the need for universities to focus on foundational research to address the challenges of homogenization in medical robotics [28] - Clinical application challenges were discussed, including inconsistent pricing and procurement limitations for laparoscopic robots, which hinder widespread adoption [29] - Innovative financial models, such as "rent-to-own," were proposed to alleviate procurement pressures on hospitals and facilitate product entry into clinical settings [31] Group 5: Future Outlook and Trends - Experts expressed cautious optimism for the industry by 2026, anticipating significant opportunities for companies that survive the current downturn [37] - The potential for medical device companies to expand internationally through partnerships and acquisitions was highlighted as a key trend [37] - The need for continuous efforts to align the industry with international standards and enhance competitiveness was emphasized [37]

现状：技术供给与落地成熟度的巨大落差 "智能体元年"的热度背后，企业落地的真实情况如何？12月9日，由中关村科金联合甲子光年举办的"超级连接· 智见未来"EVOLVE 2025大模型与智能体产业创新峰会上，来自研究机构、技术服务商和产业应用方的嘉宾，围 绕"从通用到专用：智能体在企业核心业务场景的价值涌现"展开了一场务实的对话。 甲子光年创始人兼CEO张一甲担任圆桌主持，与中关村智用人工智能研究院院长孙明俊、顺丰科技AIGC增长部 负责人刘宇、极氪汽车数智研发总监唐畅、中关村科金副总裁刘倩共同探讨了智能体落地的挑战与机遇。 当被问及为智能体落地现状打分时，几位嘉宾给出了差异化的答案，这种差异本身就反映了行业的复杂现状。 孙明俊直言不讳地指出了技术供给与实际落地之间的巨大鸿沟。他表示，智能体的技术供给成熟度约为80%，但 落地成熟度远远不到这个水平，实际上仅在30%左右。他透露，研究院在做行业测试时发现，很少有智能体可以 直接解决行业中的问题。 他举了一个医疗行业的例子来说明沟通的困难："我在金华看到几个中医院，还在解决信息化如何连通的问题。 对医院院长来说，他不知道是信息系统的问题、数据连通的问题，还是靠人工 ...

Investment Rating - The report does not explicitly provide an investment rating for the banking wealth management industry Core Insights - The banking wealth management market is experiencing a shift towards "hard technology" investments, with a focus on innovation and regulatory compliance [3][4] - The new generation of wealth management systems has been fully launched, marking a significant breakthrough in market infrastructure and laying the groundwork for improved information disclosure [3][12] - The industry is facing challenges due to low interest rates and stringent regulatory environments, prompting firms to adjust their operational strategies [3][14] Summary by Sections Market Overview - As of November, the total scale of wealth management products in the market reached 31.67 trillion yuan, a slight increase of 0.12% month-on-month and a year-on-year increase of 6.21% [5][10] - The annualized yield for cash management products recorded 1.28%, a decrease of 1.64 basis points from the previous month [5][10] - The overall market saw a decline in yields across various product categories, with pure fixed-income products yielding 2.04%, down 1.13 percentage points month-on-month [5][10] Regulatory and Industry Dynamics - The "China Banking and Insurance Asset Management Association" has completed its name change, reflecting a shift towards "functional regulation" in the asset management industry [3][12][14] - Several wealth management companies have undergone significant leadership changes, indicating a strategic shift in response to the current market conditions [3][14] - The introduction of the new wealth management system is expected to enhance data quality and reporting efficiency, promoting transparency in the industry [3][12] Product Innovations - New product launches in November included customized wealth management products and multi-asset strategies aimed at supporting technology enterprises [4][17] - The trend of wealth management funds participating in equity investments is growing, with firms actively engaging in the technology innovation sector [4][17] - The report highlights the emergence of innovative index products focused on technology and green bonds, indicating a shift in investment strategies towards sustainable development [4][19]