1月14日，A股三大股指走势分化，其中沪指微跌0.11点报4138.65点，深成指涨0.17%报14194.11点，创 业板指涨0.34%报3333.17点，科创50指数涨0.66%报1479.3点。贵金属板块多股高开，湖南白银涨超 3%，招金黄金、西部黄金等多股跟涨；游戏板块调整，掌趣科技跌超5%，汤姆猫跌超3%，三七互娱、 吉比特等跟跌。 盘面上，市场焦点股鲁信创投（13天11板）低开6.11%，实控人变更的友邦吊顶（9天7板）高开 2.23%，GEO概念股引力传媒（7天6板）低开3.67%、天龙集团（创业板3板）低开6.53%，商业航天概 念股巨力索具（9天5板）低开2.18%、东方通信（9天5板）高开3.82%、直真科技（4板）高开1.21%， 脑机接口概念股海格通信（10天5板）竞价涨停，军工股展鹏科技（5天4板）低开2.04%，AI医疗概念 股美年健康（3板）竞价涨停、泓博医药（创业板3天2板）低开0.99%。 公司新闻 佰维存储：公司预计2025年度实现归属于母公司所有者的净利润85,000.00万元至100,000.00万元，与上 年同期（法定披露数据）相比，将增加68,876.66万元至83 ...

《南华早报》近日发文称，瑞银集团看好中国股市在2026年的前景，全球投资者寻求从高估值的美国股票中多元化， 中国庞大的经济体和科技创新能力使其成为一个重要选择。UBS全球市场中国负责人称，企业利润增长、政策支持、 创新能力提升以及潜在的外资流入将推动股市发展，使其成为全球资本多元化的重要市场。 【环球网财经综合报道】Wind数据显示，截至1月13日，已有186家上市公司获公募、券商等机构集中调研，合计调研 次数达220次。其中，爱朋医疗、熵基科技、超捷股份等"热门"标的的参与机构数量均在120家以上。从调研内容来 看，脑机接口、商业航天、人形机器人等热门领域业务进展和布局成为机构重点问及的话题。 报道还提到，过去一年，中国股市跑赢美国股市；随着美国政府试图影响美联储，投资者转向包括中国在内的其他市 场，而AI相关公司因其较低的关联度可能成为市场关注点。 此外，上海和深圳交易所的日交易额近日达到创纪录的3.58万亿元，部分指数围绕四年来高位盘整。UBS策略师孟磊 表示，交易量的激增不应被解读为过度热炒的信号，因为2025年新开股票账户的速度适度，而且杠杆交易作为关键股 市指标市值的比例保持低位。 ...

港股AI应用板块回暖，知行科技、智谱高开逾7%，MINIMAX涨近3%，阿里巴巴涨超2%，快手、微盟 集团、百度涨近2%。 | 代码 | 名称 | | 昌新价 | 涨跌幅 √ | | --- | --- | --- | --- | --- | | 01274 | 知行科技 | C | 7.080 | 7.60% | | 02513 | 智谱 | | 194.700 | 7.10% | | 00100 | MINIMAX-WP | | 375.000 | 2.74% | | 09988 | 阿里巴巴-W | | 163.800 | 2.44% | | 06651 | 五一视界 | | 54.000 | 2.08% | | 02498 | 速腾聚创 | | 38.180 | 2.03% | | 01024 | 快手-W | | 80.000 | 1.98% | | 02013 | 微鼎集团 | | 2.370 | 1.72% | | 02252 | 微创机器人-B | | 26.660 | 1.68% | 港股AI应用板块回暖，知行科技、智谱高开逾7%，MINIMAX涨近3%，阿里巴巴涨超2%，快手、微盟 集团、 ...

周二（1月13日），A股放量调整，成交额超3.6万亿元创新高。AI赛道呈现分化行情，创业板人工智能新高后下挫明显。以GEO为代表的AI应用逆市大涨， 易点天下收涨超10%，中文在线、万兴科技大涨超5%；以光模块、IDC为核心的算力赛道则陷入调整，金信诺、光库科技领跌超10%，天孚通信跌超6%， 润泽科技下跌3%。 热门ETF方面，双线布局"AI应用+算力"的创业板人工智能ETF（159363）场内高开低走，上探新高后持续调整收跌3.64%，单日放量成交14.5亿元，继前一 日加仓近4亿元后，资金再度净流入超3亿元，两日合计吸金7亿元，吸金力度居创业板人工智能赛道第一！ 【迎流动性活水！159363入选互联互通标的】 2026年1月9日，港交所公告显示，北向深股通共有44只ETF调入，全市场首只跟踪创业板人工智能的ETF——创业板人工智能ETF华宝（159363）正式纳入 互联互通标的，生效日期为1月19日，此次入选互联互通名单，有望引入北向资金"新鲜活水"，或可进一步提升其场内流动性及交易活跃度。 数据显示，截至1月12日，创业板人工智能ETF华宝（159363）最新规模为47.31亿元，近6个月日均成交额超 ...

现在的问题是，这些规模最终能存的住么，持仓的这些投资者能赚到钱么？这是需要回答的问题，还有就是监管对这些现象意识到问题了没 有，很多时候市场不理性的时候，我们要学会看到问题，这样才能更好的保护自己。 结论很简单，对于热门的赛道ETF投资的时候悠着点，一定要控制好比例，千万别抱着发财的梦想。 免责声明：文中内容仅供参考，不构成任何操作建议或提示，股市有风险，投资请谨慎！ 商业航天昨天出现了重挫，相关的ETF跌幅在5%左右，当然这个跌幅并不算大，有比这更夸张的，有些航天航空相关的ETF单日跌幅在9%， 而还有刚刚起来的AI应用方面，比如说个别的科创创业人工智能ETF单日下跌超过11%。 看到这样的波动，不知道大家作何感想？似乎也在警告我们，最近主题赛道似乎有点过热了，我看到有人对过往时间的主题赛道的涨幅和表 现做了一个统计，可能唯一一个表现时间长、涨幅明显的就是商业航天了，大多数主题赛道的表现都很一般，这样说其实已经很客气了，简 单说几乎都是从哪里起来的又回到了那里，表现的时间周期很短，等你刚刚明白过来的时候，结果短期就见顶了。 | 名称 | 现价 - | 涨跌幅 | 估算规模(亿元) | 跟踪指数名称 | | ...

Core Insights - Elon Musk predicts that Starlink will transport 300 to 500 GW of solar photovoltaic components to space annually for AI computing, potentially exceeding the total computing power of the United States within two years [1] - Musk emphasizes the rapid advancement of AI, forecasting that by 2030, AI intelligence will surpass the combined intelligence of all humans [3] - He asserts that within three years, robotic surgeons will outperform top human surgeons, rendering medical school obsolete [4][5] Group 1: AI Advancements - Musk describes the exponential growth of AI, stating that breakthroughs occur so rapidly that he is frequently astonished [3] - He predicts the arrival of AGI (Artificial General Intelligence) by 2026, with AI intelligence surpassing human capabilities by 2030 [3] - The potential for robotic doctors to provide superior medical care is attributed to three factors: AI capability growth, chip performance improvements, and mechanical dexterity advancements [4] Group 2: US-China AI Competition - Musk highlights that China is set to surpass other regions in AI computing power, citing three main advantages: significant electricity generation capacity, diminishing chip performance gaps, and unmatched execution speed of Chinese engineers [5][6][7] - By 2026, China's electricity generation is expected to reach three times that of the US, with a substantial portion derived from solar energy [6] - The decline of Moore's Law indicates that the performance gap in chip technology is narrowing, making it easier for China to catch up [6] Group 3: Economic Predictions - Musk suggests that in 10 to 20 years, traditional concepts of money may become irrelevant, as AI and robotics will drastically reduce production costs, leading to a new economic paradigm of "Universal High Income" [8] - He warns of a tumultuous transition period over the next 3 to 7 years, characterized by radical changes and societal upheaval [8] Group 4: Energy Solutions - Musk advocates for solar energy as the key to human energy independence, proposing a three-step plan: improving existing grid efficiency, launching solar AI satellites into space, and establishing satellite manufacturing facilities on the Moon [9][10][11] - He emphasizes the vast potential of solar energy, arguing that utilizing solar power from space is more efficient than terrestrial nuclear fusion [9] Group 5: Future of Currency - Musk concludes that the future of currency will fundamentally be energy, as it will drive AI and enable the production of goods [13]

2026开年，全球AI竞赛场上，再次出现零售巨头的身影。 1月11日，沃尔玛与谷歌宣布，计划将沃尔玛及山姆会员店的商品整合进谷歌的Gemini。与此同时，谷 歌在全国零售联合会（NRF）大会上，正式发布通用商业协议（UCP），用于为谷歌搜索和Gemini的AI 模式提供智能购物能力。美国用户无需离开AI聊天界面，即可在Gemini的对话框中浏览商品并完成购 买。 作者 | 肖思佳 编辑 | 乔芊 在此之前，上一个把AI对话变成购物场景的，是OpenAI。2025年9月底，ChatGPT推出的"即时结 账"（Instant Checkout），跑通了从对话到下单的完整购物闭环。 从2022年底ChatGPT发布算起，短短三年时间，科技行业已经历多轮高频的"你追我赶"。而在经历过一 轮的搜索入口博弈之后，AI竞赛的焦点，正在进一步延伸至电子商务领域。 据纽约邮报报道，2025年11月底的黑色星期五，在这美国一年中最繁忙的购物日里，消费者借助人工智 能完成搜索、比价、筛选与决策，推动在线消费额达到创纪录的118亿美元。Adobe Analytics数据显 示，这一天美国的在线消费额比去年同期增长了9.1%。AI正逐 ...

Core Viewpoint - The article emphasizes the increasing demand for VLA (Variable Latency Algorithms) talent, particularly in the autonomous driving sector, highlighting the challenges faced in data collection and model optimization [2][3][4]. Group 1: VLA Demand and Challenges - There is a significant demand for VLA algorithms, especially for autonomous driving, as reflected in the job market and academic publications [2]. - Many practitioners express frustration over the difficulties in tuning VLA models and the complexities involved in data collection [3][4]. - The reliance on real machine data for effective model training is underscored, with many companies advocating for a "real machine data" approach despite its challenges [5][8]. Group 2: Learning and Practical Application - The article discusses the difficulties beginners face in integrating data, VLA models, training optimization, and deployment, with some struggling for months without success [8]. - A new course has been developed to address these challenges, providing practical tutorials and hands-on experience with VLA methods [10][11]. - The course covers a comprehensive curriculum, including hardware, data collection, VLA algorithms, and real machine experiments, aimed at enhancing learning efficiency [13]. Group 3: Course Details and Target Audience - The course is designed for individuals seeking practical experience in the VLA field, including students and professionals transitioning from traditional fields [21]. - Participants will receive a SO-100 robotic arm as part of the course, facilitating hands-on learning [14]. - The course schedule is outlined, with classes starting on December 30, 2025, and continuing into early 2026 [22].

Core Viewpoint - The article emphasizes the transformative impact of AI on industries, highlighting the shift from discussing AI as a concept to its practical implementation in products and services, particularly observed during the CES 2026 event in Las Vegas [2][3]. Group 1: AI Implementation and Industry Trends - The CES event showcased the integration of AI into various products, with companies like Nvidia and Samsung demonstrating advancements that support the notion that "everything can be AI-enabled" [4]. - Chinese brands are evolving from merely exporting products to a more comprehensive "value export" that includes technology narratives, brand communication, and ecosystem building, reflecting a deeper competitive edge [4][11]. - Lenovo's presentation at CES highlighted its "hybrid AI" strategy, showcasing a personal super-intelligent agent and a complete enterprise solution, marking a significant leap from product output to co-building technology standards and ecosystems [8][9]. Group 2: Insights from Silicon Valley - The visit to Silicon Valley focused on understanding the foundational aspects of innovation, emphasizing that true innovation requires an ecosystem that supports exploration and embraces uncertainty [14][18]. - Discussions with industry leaders revealed that the main barriers to AI implementation are often organizational restructuring rather than technical challenges, underscoring the importance of addressing business pain points [17]. - The experience at tech giants like Google and Meta illustrated the significance of a collaborative culture and the integration of AI with hardware, providing a clearer vision of future possibilities [17][19]. Group 3: Upcoming Opportunities in Germany - The upcoming Hannover Industrial Fair in Germany will focus on "AI in manufacturing," providing insights into smart manufacturing, industrial automation, and AI technologies, which are crucial for Chinese companies aiming to enhance their global competitiveness [30][31]. - The journey to Germany aims to explore the deep-rooted manufacturing practices and standards that can serve as a strategic reference for Chinese enterprises looking to expand into European markets [28][29].

Core Viewpoint - The "Artificial Intelligence +" Action Plan of Jiangsu Province aims to accelerate AI technology innovation and integration across various industries, enhancing productivity and driving economic growth. Group 1: Action Plan Overview - The plan leverages Jiangsu's strengths in industry, data, scenarios, and talent to promote AI technology innovation and application across multiple sectors [2] - Key goals include achieving over 70% penetration of new intelligent terminals and applications by 2027, over 90% by 2030, and establishing a leading AI innovation hub by 2035 [3] Group 2: Research and Development Focus - The plan prioritizes AI-driven scientific research, establishing key laboratories and innovation platforms to foster breakthroughs in various fields [4] - It aims to cultivate high-level talent in AI and enhance the capabilities of research institutions [4] Group 3: Industrial Upgrading - The initiative emphasizes the integration of AI into traditional industries, particularly manufacturing, to drive transformation and efficiency [5][6] - It includes the development of a comprehensive framework for AI-enabled manufacturing and support for small and medium enterprises in digital transformation [6] Group 4: Education and Talent Development - The plan outlines initiatives to integrate AI into education, including the establishment of AI-related programs in universities and the promotion of AI literacy among students [8] - It aims to create a robust ecosystem for AI talent development, including the establishment of AI colleges and research centers [8] Group 5: Healthcare Integration - The plan highlights the integration of AI in healthcare, with significant data management initiatives and the establishment of platforms for data sharing and application [9] - It aims to enhance the healthcare industry through AI technologies, improving medical devices and health services [9] Group 6: Data Infrastructure - The plan emphasizes the importance of high-quality data for AI development, with initiatives to create valuable data sets and support the data annotation industry [9] - It aims to establish over 1,000 high-quality data sets by 2027 to support AI applications across various sectors [9]