截至2026年1月9日收盘，中证金融科技主题指数(930986)强势上涨2.39%，成分股星环科技(688031)上涨 15.86%，东信和平(002017)上涨10.00%，税友股份(603171)上涨10.00%，博彦科技(002649)，拓尔思 (300229)等个股跟涨。金融科技ETF汇添富(159103)收涨2.38%，最新价报0.95元。拉长时间看，截至 2026年1月8日，金融科技ETF汇添富近1周累计上涨2.10%。（以上所列股票仅为指数成份股，无特定推 荐之意） 华鑫证券表示，2026年AI应用将迎来"黄金元年"，这主要得益于三大拐点：第一，技术的逐步成熟， 2025年GPT-5、Gemini 3、Qwen-Max等模型已具备强工具调用、多模态理解、自主规划能力；第二，政 策持续护航，提出深入实施"人工智能+"行动的意见并指出形成商业化应用；第三，市场需求共振，从 B端降本增效到C端普及。 国泰海通证券指出，工信部等四部门印发《汽车行业数字化转型实施方案》重点攻关智能机器人、智能 检测设备等关键装备；AI领域，月之暗面获大额融资、Meta高价收购Manus，验证Agent商业化前景； 数字人 ...

炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ A股今日（1月9日）再度走高，沪指突破4100点，连续16日收阳；深证成指、科创50指数等涨超1%； 港股亦上扬，两大股指小幅走高。 具体来看，沪指盘中强势上扬，一举突破4100点；全A成交额再度放大，突破3万亿元大关，为2025年 10月以来首次突破3万亿元关口。截至收盘，沪指涨0.92%报4120.43点，深证成指涨1.15%，创业板指涨 0.77%，科创50指数涨1.43%，沪深北三市合计成交3.15万亿元，较此前一日放量约3260亿元。 全A超3900股飘红，逾110股涨停。AI应用概念爆发，易点天下、昆仑万维（维权）20%涨停，星环科 技创历史新高；商业航天概念热度不减，中国卫通尾盘涨停创出新高，臻镭科技（维权）、理工导航、 航天电子等均创新高；有色板块强势，云南锗业、厦门钨业等涨停；创新药概念拉升，前沿生物、泓博 医药等涨停。值得注意的是，锋龙股份（002931）斩获11连板，鲁信创投11日收获9板，志特新材 （300986）连续5日20%涨停。 AI应用概念爆发 AI应用概念盘中大幅走高，个股掀涨停潮。截至收盘，易点天下、 ...

摘要 算力、模型、数据齐上阵 工信部等八部门联合印发的《"人工智能+制造"专项行动实施意见》近日发布，给"AI进工厂"划出 了可验收的时间表与交付物： 到2027年，推动3—5个通用大模型在制造业深度应用，推出1000个高水平工业智能体，打造 100个工业领域高质量数据集，并推广500个典型应用场景，同时培育2—3家生态主导型企业、选 树1000家标杆企业。 这份文件由工业和信息化部、中央网信办、国家发展改革委、教育部、商务部、国务院国资委、市 场监管总局、国家数据局八部门联合印发，落款时间为2025年12月25日，近期对外公开。 从"上系统"到"交付工业智能体" 与此前更多强调"智能工厂""数字化改造"的表述不同，《实施意见》把抓手进一步落到"算力—模 型—数据—场景"四件套上： 一方面提出强化算力供给，支持训练芯片、端侧推理芯片、AI服务器、高速互联、智算云操作系统 等关键技术，并推动大模型一体机、边缘计算服务器、工业云算力部署； 另一方面提出培育重点行业大模型、发展"云—边—端"模型体系，推动模型轻量化部署，加快在 工业场景落地。 文件还专门提出开展"模数共振"行动：推动建立企业首席数据官制度，推进数据 ...

昨天（1月4日），记者从苏州市新型工业化推进会议暨"AI+制造"创新发展大会上获悉，苏州将深 入贯彻落实国家、省"人工智能+"行动部署，大力实施"AI+制造"八大行动，全面推动人工智能与制造业 深度融合发展。 通过智能终端品牌塑造行动，苏州聚焦具身智能机器人、智能消费电子终端、智能高端装备等九大 细分领域，打响智能终端苏州品牌；加快推进智能终端产品在工业制造、政务服务、医疗健康等领域应 用，培育入库智能终端产品超300个。在平台载体赋能行动中，苏州将高水平建设国家人工智能应用中 试基地，遴选建设10个制造业重点行业人工智能应用赋能中心，建好一批产业创新中心，推动"模术空 间"等平台载体深度赋能行业发展。 作为推动制造业高质量发展的关键举措，此次"AI+制造"八大行动将从大模型培育、数据支撑、场 景应用、品牌培育等多个维度协同发力，构建人工智能与制造业深度融合的创新生态。 算力供给提质行动将着力构建高效智能算力网络，持续升级苏州市公共算力服务平台功能，通 过"算力券"补贴等形式，为中小企业提供普惠易用算力服务，力争全市算力总规模达40000PFLOPS。标 准体系引领行动支持企业开展工业大模型评价标准研究和评测 ...

回望2025年，我国制造业全速驶入以人工智能(AI)为重要引擎的新航道。在国内，工业大模型赋能下， 智能转型从"车间的示范点"迅速铺开，标杆工厂提质增效，千行百业迸发发展新动能。在海外，多个行 业技术、方案与标准的系统性输出，正为中国智造赢得全球新坐标（603040）。 这一年，《证券日报》记者进工厂、入车间，走访了京津冀、成都、内蒙古等多地的制造基地，从所见 的一幅幅实景中感受到了智能制造发展的新气象。制造业，正成为"AI+"融合应用的重要战场。AI不仅 是驱动新型工业化的核心引擎，也是重塑产业系统的关键变量。中国制造以扎实的产业实践，将智能融 入工业血脉，奋力完成从"规模优势"向"智能优势"的跃迁。 智能制造工程的扎实推进是实现这一跃迁的根基。工业和信息化部数据显示，"十四五"以来，我国已建 成3.5万多家基础级、7000多家先进级、230多家卓越级智能工厂，推动工艺、装备、软件集成创新。 产线深处藏着数字化引擎 在长安汽车的智能工厂，《证券日报》记者的目光被总装线旁伫立的"数字之眼"吸引。它紧盯着经过的 车身上的关键焊点，将数以万计的数据点采集、分析并进行判断。不远处，一块巨大的屏幕上，焊接参 数、机器 ...

来源：环球网 【环球网科技报道 记者 王楠】12月26日，在以"环球相约 智启新程"为主题的第六届环球趋势大会现 场，出海已成为工业领域热议的核心议题。当前，部分领先中资企业的海外收入占比已达30%-40%，且 保持稳健增长态势，全球化布局成为企业拓展增长空间的关键选择。京东工业越南总经理黄恺在会上表 示："在全球市场的复杂环境中，供应链的稳定与可靠远比单纯追求扩张速度更为重要。京东工业的核 心目标，是为出海工业企业构建覆盖全周期、适配多场景的可信赖全球化服务体系，让企业出海之路走 得更稳、更远。" 随着制造业等领域中资企业加速"走出去"，跨境供应链的服务需求日益迫切。黄恺指出，企业出海面临 的挑战远不止表面的语言差异，尤其是在新兴市场，非英语官方语言环境虽带来沟通不便，但更核心的 难题集中在深层运营层面。"商品标准化的复杂程度、不同国家和地区的税制差异，以及供需两端的精 准匹配，这些才是制约企业海外业务推进的关键症结，也是我们重点突破的方向。" 面对这一需求，京东工业的全球化布局已初见成效。黄恺介绍，公司近期在巴西、印度尼西亚等海外关 键市场持续发力，与多家本地优质合作伙伴达成战略合作，从商品资源整合、本地 ...

Core Viewpoint - Huangtang Town is leveraging its geographical advantages and focusing on industrial transformation, tourism development, and community spirit to achieve high-quality economic growth [1][3][8] Industrial Transformation - Huangtang Town is focusing on precision machinery and electronics, implementing smart transformation for 40 enterprises, resulting in three companies becoming provincial-level smart factories [3] - The town has nurtured 21 national high-tech enterprises and 35 technology-based SMEs, supported by a robust service environment that facilitates project execution and rapid responses to business needs [3][5] Investment and Infrastructure - The town has signed seven new industrial projects with a total investment of 2.208 billion yuan, emphasizing a "project-first" approach to enhance the park's capacity [4] - Investments include 18 million yuan for park infrastructure improvements and plans for a 30 million yuan substation to address land and labor challenges for enterprises [4][5] Tourism Development - Huangtang Town has developed diverse tourism offerings, attracting over 2,000 visitors daily during peak seasons, with activities ranging from agricultural experiences to cultural heritage [7] - The town is integrating ecological, industrial, and cultural tourism, enhancing its appeal through events and creative products [7] Community Spirit - The "Eight Sisters" militia team has been a local spiritual landmark, contributing significantly to community welfare and establishing a service alliance that benefits over 20,000 people annually [8] - The town is committed to promoting community values and governance through volunteerism and public service initiatives [8]

" 谁能构建未来智算的标准、模式与底座，谁就将在下一代智能化 竞争中拥有真正的主导权。 " 作者丨杨依婷 赵之齐 刘伊伦 编辑丨包永刚 上午场深入分享的余韵尚未散尽， GAIR 2025「AI算力新十年」 下午场便接续开启，思辨与洞察仍在回 响，关于中国智算体系未来走向的更宏大命题，已在会场内外激起新的波澜和期待。 本次大会由GAIR研究院与雷峰网共同举办，于深圳·博林天瑞喜来登酒店隆重召开。作为粤港澳大湾区的 AI标杆盛会，GAIR 自创办以来始终致力于连接技术前沿与产业实践，推动人工智能生态的交流、融合与 发展。 下午的论坛以 【谁将定义中国智算未来】 为主题，关注的焦点，从"实现0到1的突破"，转向"完成1到N 的系统化构建和价值闭环"，算力不再只以内核、生态或架构的单点创新为中心，而是迈向以系统运营、 模式创新与价值闭环为核心的全栈竞争。 在这一主题之下，下午的八位嘉宾从学术研究、产业实践、基础设施运营到算力服务模式创新等多个维度 展开了密集而深刻的分享。 他们讨论的议题不再局限于单个技术路线或单项产品突破，而是聚焦于一个更宏大的命题：谁能构建未来 智算的标准、模式与底座，谁就将在下一代智能化竞争中拥 ...

Group 1: Core Business Strategy - JD Industrial plans to strengthen its product offerings and leverage data from leading manufacturers for training [1] - The international business is a significant growth avenue for JD Industrial, with Southeast Asia identified as the first target market for overseas expansion starting in 2024 [1] - JD Industrial has established a presence in markets such as Brazil, Thailand, Indonesia, Malaysia, Vietnam, and Saudi Arabia, and is also beginning to expand into Europe [1] Group 2: Challenges in International Expansion - The primary challenges for JD Industrial's internationalization include local tax and legal compliance, as well as building partnerships with local ecosystem players [2] - Recruiting suitable local talent is essential for understanding the nuances of the local market [2] - JD Industrial's international business is one of the least dependent on JD's existing resources, requiring tailored business models for each market based on local supply chains and regulations [2] Group 3: Development of Large Models - JD Industrial has made progress in developing large models, with the launch of JoyIndustrial, the first industrial model focused on supply chains, utilizing over 81.1 million SKU data points [2] - The core of the large model is centered around data and scenarios, aiming to identify valuable use cases and accumulate comprehensive data across the supply chain [2] - There is a strong demand from clients for large models, particularly in the product sector, indicating a focus on enhancing supply chain efficiency [3] Group 4: Operational Efficiency - JD Industrial's collaboration with clients, such as XCMG Group, has significantly reduced procurement cycles for non-production materials to within 3-5 days, demonstrating improved cost efficiency [3] - Previously, the procurement process for urgently needed tools could take up to 20 days, highlighting the efficiency gains achieved through digitalization [3]

Core Insights - The first batch of leading intelligent factories in China has been officially announced, marking a significant leap from digitization and networking to intelligence in manufacturing [1][3] - The 15 leading intelligent factories span various industries, including equipment manufacturing, raw materials, electronic information, and consumer goods, indicating a comprehensive transformation in production methods and supply chains [3][5] - The penetration rate of artificial intelligence technology in these leading factories exceeds 70%, significantly higher than the 45% rate in previously cultivated excellent-level intelligent factories [4][10] Industry Transformation - The leading intelligent factories are expected to drive a comprehensive transformation in innovation paradigms, production methods, and supply chain structures, accelerating the establishment of new manufacturing systems based on data and models [3][15] - The average research and development cycle for products in excellent-level and leading factories has been reduced by 29% and 38% respectively, showcasing the substantial value of intelligent manufacturing [5][10] Technological Advancements - The implementation of AI and data-driven technologies has led to significant improvements in production efficiency, with product development cycles reduced from 420 days to 240 days and product introduction cycles cut from 40 days to 15 days [10][12] - The integration of AI with lean management systems in engine manufacturing has achieved near-zero defects in high-end engine production, demonstrating the effectiveness of smart technologies [12][14] Future Development - The Ministry of Industry and Information Technology plans to continue promoting the digital transformation of the manufacturing sector and develop intelligent manufacturing further [16][18] - There will be a focus on creating a high-end brand of "leading factories" that represent China's capabilities and possess global competitiveness, along with encouraging these factories to share advanced experiences and solutions [17][18]