在线体验链接： https://chat.intern-ai.org.cn/ 2月4日，上海人工智能实验室开源基于打造的万亿参数科学多模态大模型 Intern-S1-Pro，为AI4S从"工 具革命"的1.0阶段迈向以"革命的工具"驱动科学发现的2.0时代，提供创新的系统性开源基座。 作为当前全球开源社区中参数规模最大的科学多模态模型，Intern-S1-Pro的核心科学能力实现了质的跃 升，高难度综合学科评测稳居AI4S领域国际领先水平，复杂数理逻辑推理能力达奥赛金牌水平，面向 真实科研流程的智能体能力位居开源模型第一梯队。 此次发布的Intern-S1-Pro是通过SAGE实现 "可深度专业化通用模型" 的关键实践。该模型基于混合专家 架构（MoE），共拥有512个专家，总参数达1T，每次调用仅激活8个专家、22B参数。其通用能力和科 学能力协同演进，并在底层架构实现了两大核心突破：在SAGE的基础模型层，通过引入傅里叶位置编 码①并重构时序编码器，赋予模型统一理解从微观生命信号到宏观宇宙波动的"物理直觉"；通过高效路 由机制，系统攻克了训练万亿参数MoE模型在稳定性与算力效率上的瓶颈，为超大规模模型的训 ...

Core Insights - Nanshan District has become the first district-level jurisdiction in China to surpass RMB 1 trillion in GDP, highlighting its economic vitality and innovation density [4] - SIXUNITED has set ambitious targets for 2026, aiming for RMB 10 billion in annual revenue and shipments of 15 million AI terminals, marking a significant step in large-scale AI commercialization [2][30] Company Strategy - SIXUNITED's dual strategic targets for 2026 include achieving RMB 10 billion in revenue and shipping 15 million AI terminals, leveraging its 18 years of technological evolution and collaboration with partners like Intel [2][30] - The company has transitioned from an Independent Design House (IDH) to a full-stack AI services provider, integrating hardware and software across various AI applications [9][10] Industry Context - Nanshan District is a core hub for technological innovation and advanced manufacturing within the Guangdong–Hong Kong–Macao Greater Bay Area, housing over 1,000 AI enterprises and forming a complete industrial chain [4][5] - The region's supportive policies, including a RMB 3 billion AI fund and initiatives to foster innovation, are designed to empower AI enterprises and enhance industrialization [7][28] Ecosystem Collaboration - The 18th Anniversary Gala served as a platform to showcase Nanshan's AI industry strength and SIXUNITED's strategic upgrade, with nearly 2,000 attendees from various sectors [6][30] - SIXUNITED emphasizes collaboration with upstream and downstream partners to advance its "All in AI" strategy, focusing on joint technology development and resource sharing [27][30] Product Development - SIXUNITED has developed a comprehensive AI terminal portfolio, including notebooks, tablets, and servers, optimized for mainstream computing platforms [16][17] - The company has achieved significant performance improvements in AI compute capabilities through its partnership with Intel, co-developing products that enhance power efficiency and performance [12][13] Global Market Strategy - The company plans to localize its market strategy in key regions such as North America, Europe, and China, while expanding into high-growth areas like the Middle East and Southeast Asia [22][23] - Supported by global R&D centers and manufacturing bases, SIXUNITED's production capacity aligns with its shipment goals, ensuring it meets market demand [24]

左为王士立（Alexandr Wang）与马克・扎克伯格 据《信息》杂志获取的一份内部备忘录显示，元宇宙平台公司（Meta Platforms）对其新成立 AI 团队即 将推出的首款核心大模型，态度愈发乐观。 这份日期为1 月 20 日的备忘录由 Meta 超级智能实验室（Meta Superintelligence Labs）产品经理梅根・ 傅（Megan Fu）发布，其中明确指出，下一代大语言模型Avocado（牛油果）已完成预训练，是 "Meta 迄今能力最强的预训练基础模型"。预训练是 AI 模型开发的初始阶段，模型需接触海量数据，学习通用 知识、模式与关联关系。 备忘录称，Avocado 的性能已超越当前最优的开源基础模型。（基础模型指仅完成预训练、尚未通过 "后训练" 阶段优化的大语言模型；后训练阶段会通过人类反馈强化学习等技术，针对特定任务对模型 进行精调。）尽管 Avocado 尚未完成后训练，但其在知识储备、视觉感知及多语言能力上，已与顶尖 的后训练模型持平。 作者：乔蒂・曼（Jyoti Mann） 在 Avocado 正式公开发布前，Meta 内部对其 AI 模型进展的乐观评估，能否经受住 ...

Core Insights - The AI red envelope competition has sparked widespread public participation, with companies like Yuanbao and Qianwen spending billions to attract users, while Doubao is set to make an appearance during the Spring Festival gala [1][2] User Metrics - Doubao leads the industry with 54 million daily active users, followed by Yuanbao with 30 million and Qianwen with 7 million, indicating significant user growth pressure for the latter two [1][2] Recruitment Strategies - Qianwen and Yuanbao's concerns about user growth are reflected in their recruitment strategies, with high salaries offered to attract talent on job platforms like Maimai. For instance, positions such as "User Growth Algorithm Engineer" at Qianwen can offer salaries up to 1.28 million yuan, while "User Growth" roles can reach 1.12 million yuan [1][2] - Yuanbao offers salaries exceeding 750,000 yuan for user operation and activity operation roles, while Doubao's AI Product Manager position offers 600,000 yuan, and the AI Application Engineer role approaches 1 million yuan [1][2]

Core Insights - The article highlights that Shengshu Technology has completed over 600 million RMB in A+ round financing, setting a record for the largest single financing in China's video generation sector [1] - The company aims to achieve over tenfold growth in users and revenue by 2025, with a global reach across more than 200 countries and regions [1] Financing Details - The financing round was led by Zhongguancun Science City and Xinglian Capital, with strategic investments from companies like Wanxing Technology, Visual China, and Tuolisi [1] - Shengshu Technology has completed a total of six financing rounds and one equity transfer, with notable investors including Huawei, Ant Group, and Baidu [7][9] Product Development - Shengshu Technology focuses on developing multimodal general large models and applications, providing video generation and multimodal generation products through various platforms [2] - The company is recognized as one of the earliest teams to research multimodal generation algorithms, having introduced the U-ViT architecture ahead of OpenAI's DiT [2] Model Performance - The Vidu Q3 model, aimed at professional film production, ranked first in China and second globally in a recent AI benchmark test, surpassing competitors like Runway Gen-4.5 and Google Veo3.1 [3] - Vidu Q3 supports features such as 16-second audio-visual synchronization, 1080P quality, and multilingual output [4] Market Presence - Vidu has established a strong presence in the film industry, covering over 90% of content providers and production institutions, with clients including Sony Pictures and Tencent Animation [7] - The company also serves clients in the internet and smart hardware sectors, including ByteDance and Samsung, focusing on content production and product interaction innovation [7] Competitive Landscape - The video generation sector remains highly competitive, with significant investments flowing into startups, while major companies like Kuaishou and Google are also expanding their influence [10] - The article emphasizes the need for startups to differentiate themselves in technology, application scenarios, or ecosystems to succeed in this competitive environment [10]

Core Viewpoint - Haizhi Technology (02706) is set to launch its IPO on February 5, 2026, and is recognized as the "first stock of large model de-illusion" in Hong Kong, leading the enterprise-level knowledge graph market in China with over 50% market share [1][5][7]. Company Overview - Haizhi Technology specializes in AI solutions based on a "graph-model fusion" technology path, combining the accuracy of knowledge graphs with the reasoning capabilities of large models to provide end-to-end AI solutions for enterprise clients [6][8]. - The company offers two main solutions: Atlas Graph Solutions and Atlas Intelligent Agents, which empower enterprises to achieve intelligent automation and natural language interaction across various applications [7][13]. Financial Performance - The revenue from Atlas Intelligent Agents is projected to grow by nearly 9 times in 2024 compared to 2023, with a nearly 5-fold increase expected in the first half of 2025 [1]. - Revenue from Atlas Graph Solutions is expected to increase from 367 million RMB in 2023 to 417 million RMB in 2024, reflecting a growth rate of 13.6% [21][22]. - The gross profit margin is anticipated to rise significantly, with the gross profit for 2024 expected to reach 45.7%, an increase of 28 percentage points from 2023 [23]. Market Dynamics - The global AI market is experiencing exponential growth, with AI intelligent agents identified as the fastest-growing segment in the Chinese market, significantly outpacing the overall growth of enterprise-level AI solutions [25][27]. - Despite over 500 competitors in the Chinese enterprise AI solutions market, the top five companies hold nearly 58.1% of the market share, indicating a concentrated competitive landscape [28][29]. Competitive Advantages - Haizhi Technology boasts industry-leading technical capabilities, particularly in graph computing and proprietary graph-model fusion technology, which enhances performance and efficiency [8][12]. - The company has a robust business expansion capability, serving over 3,010 clients across various application scenarios, including telecommunications fraud prevention and financial risk control [15][19].

新华社曼谷2月5日电 通讯｜中国AI技术为泰国中文教育注入新活力 对于学生而言，这个学习APP让中文学习从"被动接受"变成了"主动探索"。高一学生达兰蓬·安法里说， 她几乎每天都用它练发音，不管读错哪个音节，它都能立刻指出，现在说中文自信多了。 北榄府教育局（中学部）局长沃拉波·辛哈拉介绍，目前，当地的25所中学中已有23所开设了中文课 程，覆盖率达92%，学习中文的学生人数持续攀升。引入中国AI技术辅助中文教学，既是响应泰国教育 部数字化外语教学的政策导向，更是贴合本地发展需求的务实之举。 从装饰满中国元素的沉浸式中文课堂，到AI赋能的个性化中文学习，中文教学已不再局限于传统课 堂，而是走上"云端"让人人可及。科大讯飞国际中文运营总监高玉洁介绍，随着中国AI技术持续落地与 推广，相信会有更多海外学子借助AI的力量，走近中文、读懂中国。（完） 作为泰国工业重镇和经济门户，北榄府对中文人才的需求日益迫切。帖诗琳中学已深耕中文教学20余 年，目前学校中文教师团队由7名泰国中文老师和1名中国老师组成，要支撑全校学生的中文学习需求， 压力不小。于是，2025年，学校引入来自中国的AI中文智能教学系统来辅助中文教学。 ...

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].