2月1日零时，春节的倒计时刚刚开启，腾讯的"上元宝，分10亿"活动也同步点燃了这个假期的第一波热 闹。用户只要将元宝App升级到最新版本，就可以直接参与抽取现金红包，单个红包金额最高可达万 元。 如果回顾中国互联网的发展史，不难发现腾讯的这次活动像极了2015年的"春节摇红包"活动。那一年， 腾讯为了推广微信支付，在春节期间动用了5亿现金作为红包发放。从结果看，这场撒钱式推广可谓相 当成功。在除夕当晚，参与抢红包的人数超过2000万，红包发放数量超过10亿。这场活动之后，数以千 万计的人熟悉了微信支付的基本使用方式，成为微信支付的用户。在支付宝一统天下的市场格局之下， 腾讯的这次操作堪称一次"诺曼底登陆"。 十余年过去，腾讯再次在春节节点复刻这一剧本，而且投入规模更大、动员力度更强。不同的是，这一 次它不再推广支付工具，而是押注一款AI社交产品——元宝的"元宝派"。 元宝派是什么？简单来说，这是元宝主打的社交功能。用户可通过元宝App创建或加入一个"派"。 在"派"里，元宝AI会作为"派友"存在，用户不仅能够直接与其聊天互动，还能调用相关功能，让其完成 多种辅助任务。比如，用户可以在"派"里上传图片，让AI将 ...

一项可能改变技术发展轨迹的能力正在AI实验室内部悄然成形。当AI系统开始自主研发更先进的AI时，人类对技术演进的理解和控制能力将面临前所未有 的挑战。 据追风交易台，安全与新兴技术中心(CSET)2026年1月发布的研讨会报告，这一进程已经开始，并可能在未来数年内加速，带来"重大战略意外"。 OpenAI已公开宣布，计划在2028年3月前打造"真正的自动化AI研究员"。报告显示，前沿AI公司目前已在内部使用自家最先进模型加速研发工作，且这些模 型往往先用于内部研发，然后才对外发布。 一位参会的机器学习研究员透露，在精心选择的任务上，AI模型能在30分钟内完成原本需要他数小时才能完成的工作。随着模型能力提升，能够自动化的 研发任务范围正在持续扩大。 这项技术的风险核心在于两点：一是人类对AI研发过程的监督能力将下降，二是AI能力提升速度可能超出人类反应能力。 报告警告，在最极端情境下，AI驱动的技术改进可能形成自我强化循环，导致"能力爆炸"——生产力提升从人类水平的10倍跃升至100倍、1000倍。AI系统 将完全主导研发流程，人类参与度趋近于零，由此产生的系统能力可能远超人类。 部分AI领域领军人物已警告，这 ...

Core Insights - The report focuses on the current state of AIGC and AGI development, highlighting a competitive landscape dominated by the US and China, with a shift towards multimodal integration and autonomous agents, making human-machine coexistence inevitable [1] Group 1: Technological Developments - Key breakthroughs in AGI are concentrated in four areas: long-term memory and controllable personality, physical interface integration, autonomous scientific hypothesis validation, and institutional restructuring [2] - Core technological trends include the emergence of text generation intelligence, 3D world simulation, and video generation spatiotemporal modeling [2] - The competition among large models has led to a dual-track system of open-source and closed-source models, with China's open-source ecosystem leading and the US's closed-source models outperforming by approximately 9 months [2] Group 2: Global Competition and Industry Landscape - In 50 key AI fields, the US leads in 26 areas focusing on foundational breakthroughs and principle innovation, while China leads in 13 areas excelling in application implementation and industry integration [3] - Eleven core companies dominate the market, with OpenAI and Google DeepMind leading the closed-source camp, while DeepSeek, Alibaba, and ByteDance drive the open-source ecosystem and application scenarios [3] - The development of models is shifting towards "personalization + specialization," with agentification and ecological embedding becoming mainstream [3] Group 3: Application Scenarios - In content production, AIGK achieves knowledge self-organization, with AI in literature, art, music, and video realizing large-scale creation [4] - Industry applications span education, healthcare, government, energy, and agriculture, with AI + education promoting personalized learning and AI + healthcare constructing multimodal models for cancer diagnosis [4] - The intelligent internet is accelerating, with social AI integration and AI socialization reshaping information retrieval logic, leading to a subtle integration of AI into daily life [4] Group 4: Challenges and Future Outlook - Current challenges include cumulative errors, long-term memory drift, and accountability attribution among nine technical challenges, with a gap between capital enthusiasm and technological reality [5] - Over the next decade, AGI will undergo four stages: toolification, scenario-based application, theoretical development, and embodiment, transitioning human-machine relationships from collaboration to coexistence [5] - The focus of human value will shift towards creativity, emotionality, and reflective value, with the economy moving from "scarcity economics" to "meaning economics," making intelligent capital a core production factor [5]

Core Insights - The Chinese large model sector is experiencing accelerated development in 2025, with the SuperCLUE annual evaluation covering 23 representative models from both domestic and international sources, focusing on general capabilities, specialized tasks, and application scenarios [1][2]. Group 1: Model Performance - The top-ranking closed-source model is Anthropic's Claude-Opus-4.5-Reasoning, scoring 68.25, followed by Google Gemini-3-Pro-Preview and OpenAI GPT-5.2 (high) [1][23]. - Domestic models are transitioning from "catching up" to "running alongside," with Kimi-K2.5-Thinking (61.50) and Qwen3-Max-Thinking (60.61) ranking fourth and sixth globally, excelling in code generation and mathematical reasoning tasks [1][2][23]. - The performance gap in precise instruction adherence and hallucination control remains significant, with average score differences exceeding 7 points and nearly 2 points, respectively [2]. Group 2: Technological Evolution - The evolution of technology is characterized by three stages: early competition among numerous models and the emergence of multimodal capabilities, a mid-stage explosion of multimodal applications and reasoning breakthroughs, and the rise of intelligent agents and ecosystem reconstruction by 2025 [1][2]. - The mixed expert (MoE) architecture has become mainstream, with domestic open-source models capturing a significant share of the global market, led by DeepSeek and Qwen3 [1][2]. Group 3: Application and Cost-Effectiveness - In application scenarios, general intelligent agents are still in their foundational stages, lacking in complex task handling capabilities; however, domestic models excel in multimodal areas such as image-to-video generation and Chinese adaptation [2]. - Domestic models demonstrate significant cost-effectiveness, with Kimi-K2.5-Thinking priced at only one-third of similar overseas models, although overseas models outperform in reasoning efficiency [2]. Group 4: Future Directions - The Chinese large model sector has made significant advancements in technological innovation, application deployment, and ecosystem construction, establishing core competitive advantages in open-source ecosystems, vertical applications, and cost-effectiveness [2]. - Future efforts should focus on overcoming shortcomings in precise instruction adherence and hallucination control to drive technology towards more efficient and reliable outcomes [2].

一款诞生于个人开发者之手的AI助手，在数天内席卷全球技术圈。 想象这样一个画面，深夜，一台 Mac Mini 在无人看管的情况下自动运行，清理了收件箱中7.5万封邮 件，保护了重要数据；企业的工程师仅需在通讯软件中输入一句话，AI便能自动将PPT转换为PDF并发 送给客户。 这些曾出现在科幻电影中的场景，因一个名为Clawdbot（现名"OpenClaw"） 的开源项目，在2026年初 成为了全球极客与开发者桌面上的现实。 这个项目在GitHub上以近乎疯狂的速度收获超过10万星标，甚至一度带火了苹果Mac Mini的销量。尽管 其作为AI个人助手全面商业化应用，仍有安全与成本两大问题，但生态位价值的意义重大。从技术圈 蔓延至资本圈的热潮，让Clawdbot被视为从"对话式AI"迈向"代理式AI"的标志性拐点。 又一个现象级产品 首先就是产品名称，因为先被 Anthropic 指控侵权而被迫改名，短暂改为"Moltbot"后，又正式命名 为"OpenClaw"。另外，用户隐私与数据安全也被不少业内人士视为潜在的巨大风险。 当然，由于这类产品的部署和使用还有一定的技术门槛，当前参与"尝鲜"的用户还是以技术极客为 ...

中国软件技术发展洞察 和趋势预测研究报告2026 研究数据说明——研究⽅法 1桌⾯研究 通过对⾏业公开信息进⾏桌⾯研 究，资料包括但不限于专业机构 研究报告、技术领域书籍、技术 社区⽹站、技术企业官⽹及专家 公开演讲内容等； 2技术模型 通过技术专利数量、技术诞⽣ 时间、技术舆论指数指标，进 ⾏技术发展阶段类型模型设计， 作为细分技术发展阶段展现； 3专家访谈 InfoQ 研究中⼼针对本次研究定 向邀请了多位技术企业管理层、 垂直技术领域专家、技术从业者、 产业从业者等各⽅⾯专家； 2 研究数据说明——数据来源 本次研究通过收集并整理160+细分技术领域的技术专利数量、技术诞⽣时间、技术舆论指数、技术融资事件作为2025年重要技术发展回 顾与技术发展特征解读的基础。 技术专利数量 技术专利数据来⾃国家知 识产权局专利数据库。使 ⽤对应技术领域关键词进 ⾏检索，截⽌时间2025 年12⽉31⽇。 技术诞⽣时间 考虑到数据可得性与统⼀ 性，技术诞⽣时间使⽤知 ⽹论⽂库进⾏相关技术领 域论⽂最早收录年份统计。 技术舆论指数 技术舆论指数数据来源为 搜索引擎和主要技术媒体， 其中包括百度、InfoQ中 ⽂站和CSDN ...

Alphabet(GOOGL.US)正在以一种强劲的势头向OpenAI发起挑战，这突显了华尔街对这家谷歌母公司作 为AI领导者的认知。而在短短一年前，投资者还认为它严重落后于竞争对手，并因此惩罚了其股价。 智通财经APP注意到，在周三的财报电话会议上，Alphabet高管们展现出了更加自信的姿态。这是自 Gemini3模型发布以来的首次财报会议，该模型令用户惊艳，并帮助谷歌在人工智能竞赛中迎头赶上。 尽管Alphabet没有点名提及其次要AI竞争对手，但其展现出的新自信强调了一个关键对比：对AI的投资 已开始在整个公司范围内产生回报。 这成为了Alphabet计划在2026年将资本支出增加近一倍——达到1750亿至1850亿美元之间——的理由， 这些支出将用于大规模投入AI计算能力。 Alphabet在2025年关于AI的准备发言中，重点还放在产品使用率和专门由其云计算部门产生的AI收入 上。"总的来说，我们看到AI投资和基础设施正在全面推动收入和增长，"首席执行官桑达尔·皮查伊表 示。 谷歌对AI驱动收入的新信心得到了其消费者和企业业务增长的支持。 尽管如此，这一数字仍落后于ChatGPT，OpenAI首席 ...

目前这轮加密市场"跌跌不休"，可以理解为多重外部利空（贵金属、美股回调、IPO 抽血、货币政策预期转向）叠加内部资金结构问题，在 10 月大跌后把 原本"没来得及跑"的那部分筹码也一起洗出去，导致趋势从"强震荡"演变成更明确的熊市段落。 在这种背景下，用"刻舟法"类周期经验来估算，本轮自顶部 起计约一年左右见真正周期低点是有历史参考性的，大方向落在今年 9 月附近，而价格区间大概率会回踩到接近上一轮牛市高点（约 6 万）一带形成阶段底 部，但过程中会有数次剧烈反弹和情绪反复。 白银兼具贵金属和工业金属属性，对宏观预期更敏感，历史上白银在急涨后的暴跌，往往伴随大量杠杆多头被强平、追加保证金，机构为了满足保证金要 求，会优先卖出流动性更强、交易更方便的资产，其中就包括比特币、以太坊这类可以快速变现的标的。 从宏观资产视角看，近期不仅是币圈在回调，黄金、白银以及美股本身也出现了动能减弱甚至高位滞涨、回调的信号，这说明"风险资产整体在去杠杆"，而 不是加密单独出问题。 贵金属的"被动连坐"逻辑 黄金在地缘风险和通胀预期高企时往往走出一波避险行情，但一旦通胀下行、实际利率抬升或市场开始交易"更长时间的高利率"，黄金往往 ...

Core Insights - Artificial intelligence (AI) is identified as the greatest investment opportunity of the current era, with a strong emphasis on the urgent need for energy to support its growth [1][2][3] Group 1: AI and Energy Demand - AI technologies, particularly large language models like ChatGPT, are extremely energy-intensive, with data centers consuming as much energy as small cities [2] - The increasing demand for AI is straining global power grids, leading to rising electricity prices and a need for utilities to expand capacity [2] - Industry leaders, including Sam Altman and Elon Musk, have highlighted the critical link between AI development and energy availability, warning of potential shortages [2] Group 2: Investment Opportunity - A specific company is positioned as a key player in the AI energy sector, owning critical energy infrastructure assets that will benefit from the anticipated surge in energy demand from AI data centers [3][7] - This company is not a chipmaker or cloud platform but is described as a "toll booth" operator in the energy market, profiting from the increasing need for electricity [5][6] - The company is debt-free and has significant cash reserves, equating to nearly one-third of its market capitalization, making it an attractive investment option [8] Group 3: Market Position and Growth Potential - The company is involved in large-scale engineering, procurement, and construction projects across various energy sectors, including nuclear energy, which is crucial for America's future power strategy [7] - It has a stake in another AI-related company, providing investors with indirect exposure to multiple growth opportunities without the associated premium costs [9] - The stock is currently undervalued, trading at less than seven times earnings, which presents a compelling investment case given its ties to the booming AI and energy sectors [10] Group 4: Future Trends - The ongoing trends of onshoring, driven by tariffs, and the surge in U.S. LNG exports are expected to further enhance the company's market position [14] - The influx of talent into the AI sector is anticipated to drive continuous innovation and advancements, reinforcing the importance of investing in AI-related infrastructure [12]

芯东西2月5日报道，今日，美国AI芯片独角兽Cerebras Systems宣布完成10亿美元（约合人民币69亿元）F轮融资，估值达到230亿美元（约合 人民币1596亿元）。 本轮融资由Tiger Global领投，Benchmark、Fidelity Management & Research Company、Atreides Management、Alpha Wave Global、Altimeter、 AMD、Coatue以及1789 Capital（合伙人包括小唐纳德·特朗普）等机构跟投。 成立于2015年的Cerebras，以餐盘大小的AI芯片而闻名。其晶圆级引擎3（WSE-3）芯片是全球最大、速度最快的AI芯片，体积是当前最大 GPU的56倍，单位计算功耗却远低于同类产品，同时推理和训练速度比竞品快20倍以上。 其芯片用于处理AI推理所需的顺序执行、内存密集型工作负载。与需要在芯片和内存之间来回传输数据的GPU不同，WSE将所有运算都保存 在芯片内部，从而消除了限制GPU推理能力的内存带宽瓶颈。 Cerebras上一轮融资是在2025年9月宣布完成的11亿美元（约合人民币76亿元）G轮融资，当时 ...