Core Viewpoint - Recent demand for inference and training computing power is strong, leading to price increases from both Amazon Web Services (AWS) and Google Cloud [1][2] Group 1: Demand for Computing Power - The demand for computing resources for inference and training has significantly increased, supporting the need for training computing power [1] - AWS raised prices by approximately 15% for EC2 machine learning capacity blocks on January 23, 2026, followed by Google Cloud announcing price hikes for its cloud network transmission services, with North America seeing a doubling of prices [2] Group 2: Inference Side - The rapid emergence of AI agents, such as MoltBot, is expected to support the demand for inference computing power, as these agents can perform more complex tasks and require more computing resources [3] - Anthropic has raised its revenue expectations for 2026 and 2027 to $18 billion and $55 billion, respectively, indicating a strong upward trend in inference demand [3] Group 3: Training Side - The industrial sector is continuously exploring scaling limits, which supports the demand for training computing power, with new models expected to be released in Q1 2026 [8] - Models like Grok-5 and GPT-6 are anticipated to utilize larger datasets and parameter scales, increasing the demand for training computing power [8] Group 4: Financial Reporting Catalyst - The upcoming earnings reports from major cloud service providers (CSPs) will be critical in confirming the demand for computing power and capital expenditure continuity [9] - Key earnings dates include Microsoft and Meta on January 29, 2026, followed by Google on February 5 and Amazon on February 6, with NVIDIA's report on February 26 expected to further influence market sentiment [9][10]

Core Insights - Claude Skills have gained significant popularity, surpassing MCP, with various CLI clients supporting them and products like扣子 and MiniMax launching similar offerings [2] - The value of Claude Skills is still greatly underestimated, as a well-designed Skill can match or exceed the intelligence of complete AI products [3][4] - Skills allow non-technical users to create their own applications, demonstrating the potential for widespread adoption and innovation in AI [4][5] Group 1: Understanding Skills - Skills are modular capabilities that extend the functionality of AI Agents, packaging instructions, metadata, and optional resources for automatic use [22][24] - The architecture of Skills resembles a comprehensive SOP package for task delegation, enabling Agents to execute tasks reliably [24][28] - Skills can be seen as an extension of general Agents, allowing them to perform specialized tasks by loading different Skills [14][16] Group 2: Value and Future of Skills - Skills represent a future-oriented approach to AI applications, enabling Agents to autonomously understand and execute tasks based on human-provided guidelines [28][30] - The design of Skills allows for zero-code development, making it accessible for non-technical users to create intelligent Agents [31][34] - Skills can be combined flexibly, allowing multiple Skills to work together to complete complex tasks [68][69] Group 3: Implementation and Usage - The article provides a comprehensive guide on how to create and use Skills, emphasizing the ease of development and the potential for rapid testing of ideas [105][130] - Users can install Skills from repositories or create their own using tools like skill-creator, which simplifies the development process [121][130] - The article outlines scenarios where Skills are particularly beneficial, such as when specific knowledge or templates are required for task completion [139][141]

此外，扣子官方视频Skill也正式上线，该功能支持自动生成视频脚本、匹配视觉素材，并完成剪辑、转 场、配乐等后续流程。 扣子2.0推出Agent Plan，即"长期计划"，让AI从"即时问答工具"升级为"可持续运作的智能体"。用户只 需要确定目标，规定好怎么完成、怎么实现，扣子能够持续执行，并向用户主动汇报、最终交付任务。 以自媒体账号运营为例，扣子能够和用户一起讨论账号定位，拆解每个阶段的运营策略，再帮用户创作 内容。如果用户想写一本书，只需把写作主题和目标发给扣子，它会自己搜集资料、撰写初稿，再根据 反馈自行调整，达成3周内写出10万字初稿的计划。用户还可以用长期计划来完成学习目标，比如考雅 思，扣子会设定每日任务并准备学习资料。 （文章来源：科技日报） 1月19日，字节跳动旗下AI Agent（智能体）平台"扣子"宣布2.0品牌升级。扣子2.0集成了Agent Skill、 Agent Plan、Agent Coding、Agent Office能力，让AI真正成为用户的"工作伙伴"。 通用Agent已展现出强大的基础任务处理能力，在日常对话、信息整合与简单推理方面有了长足进步， 但要应对高度专业化、高 ...

责任编辑：刘万里 SF014 新浪科技讯 1月19日晚间消息，字节跳动旗下AI Agent平台"扣子"宣布2.0品牌升级。据介绍，扣子2.0集 成了Agent Skill、Agent Plan、Agent Coding、Agent Office能力，让AI 真正成为用户的"工作伙伴"。 通过封装领域知识、标准化操作流程或集成专用工具，"技能"（Skills）能够将通用AI的认知能力与特 定任务需求相结合，更贴合实际应用场景中多元化、高标准的任务要求，保证输出稳定性。扣子2.0推 出的Agent Skills，本质上是'场景最佳实践 + 所需工具'的封装，旨在帮助更多用户调用专业技能，定向 增强解决复杂专业问题的能力。 在全新推出的技能商店中，用户可以浏览、选择并一键安装使用由扣子官方及优质开发者创建的各类专 项技能模块，包括但不限于"新年绘本""互动教学""投资知识库""法律类案检索"等。扣子可根据任务场 景，智能调用或组合多个已安装技能，让Agent Skills提供综合性解决方案。 扣子2.0推出了Agent Plan，即"长期计划"，让AI从"即时问答工具"升级为"可持续运作的智能体"。用户 只需要确定 ...

都2026了，你还在为写提示词掉头发吗？ 我知道，大伙儿不管上班的上学的早就离不开 AI 了，但我的评价是，最折磨人的，还得是用 AI 的前戏，因为 AI 是很难一句话，就听懂你想要什么的。 得把一大坨一大坨的提示词搬来搬去，把背景需求格式交代一遍，还得把各种陈年老文件喂给AI，看着他学。 结果还没开始，AI 就顶不住了，聊天框又得remake了。 然而最近，世超发现个新项目，只能说巨火，各大 AI 社区都在讨论这玩意，甚至有说法是比提示词用着爽。 这次，他们又搓了个 Skills 回来了，看架势好像又想引领新潮流了。。别的不说，隔壁 OpenAI 反正好像已经开始抄作业了。 这玩意叫 Agent Skills ，是由 Claude 母公司 Anthropic 搞出来的。 经常看咱文章的差友可能有印象，这公司之前搞了个 MCP 协议，直接把 AI 抄家伙干活的难度打了下来，后来谷歌和 OpenAI 这种巨头全跟进了。 这玩意的作用，顾名思义，AI 现在可以像宝可梦一样，学会任意新技能了。 我们就拿 Skills 的亲兄弟 Claude 来演示下。 首先你得在设置里，找到 Skills 的开关把它打开。 然后你 ...

Group 1: Nvidia and TSMC Collaboration - Nvidia and TSMC unveiled the first Blackwell chip wafer produced in the U.S., marking a significant milestone in domestic chip manufacturing [1] - The TSMC Arizona factory has a total investment of $165 billion and will produce advanced chips using 2nm, 3nm, and 4nm processes [1] - The Blackwell chip features 208 billion transistors and achieves a connection speed of 10TB/s between its two sub-chips through NV-HBI [1] Group 2: Anthropic's Agent Skills - Anthropic launched the Agent Skills feature, allowing users to load prompts and code packages as needed, enhancing the capabilities of AI [2] - Skills can be used across Claude apps, Claude Code, and API platforms, with a focus on minimal necessary information loading [2] - The official presets include nine skills for various document formats, and users can upload custom skills [2] Group 3: New 3D World Model by Fei-Fei Li - Fei-Fei Li's World Labs introduced a real-time generative world model, RTFM, which can render persistent 3D worlds using a single H100 GPU [3] - RTFM employs a self-regressive diffusion Transformer architecture to learn from large-scale video data without explicit 3D representations [3] - The model maintains spatial memory for persistent world geometry through pose-aware frames and context scheduling technology [3] Group 4: Manus 1.5 Update - Manus released version 1.5, introducing a built-in browser that allows AI to interact with web pages, test functions, and fix bugs [4] - A new Library file management system enables collaborative editing within the same Agent session, reducing average task completion time significantly [4] - The system allows for no-code music web application construction through natural language, supporting real-time updates [4] Group 5: Windows 11 Major Update - Windows 11's major update features "Hey Copilot" for voice activation and Copilot Vision for screen understanding, enhancing user interaction [5][6] - Copilot Actions can perform operations on local files, while Copilot Connectors integrate with OneDrive, Outlook, and Google services [5][6] - Manus AI operations are integrated into the file explorer, allowing for automatic website generation and video editing functionalities [6] Group 6: Baidu's PaddleOCR-VL Model - Baidu open-sourced the PaddleOCR-VL model, achieving a score of 92.6 on the OmniDocBench V1.5 leaderboard with only 0.9 billion parameters [7] - The model supports 109 languages and excels in text recognition, formula recognition, table understanding, and reading order prediction [7] - It utilizes a two-stage architecture combining dynamic resolution visual encoding and a language model, achieving high inference speed on A100 [7] Group 7: AI in Fusion Energy Development - Google DeepMind collaborates with CFS to accelerate the development of the SPARC fusion device using AI [8] - The partnership focuses on creating precise plasma simulation systems and optimizing fusion energy output [8] - The TORAX simulator is a key tool for CFS, enabling extensive virtual experiments and real-time control strategy exploration [8] Group 8: Harvard Study on AI's Impact on Employment - A Harvard study tracking 62 million workers found a significant decline in entry-level positions in companies using AI, primarily through slowed hiring [9] - The impact of AI is most pronounced among graduates from mid-tier universities, while top-tier and bottom-tier institutions are less affected [9] - The wholesale and retail sectors face the highest risk for entry-level jobs, with a trend towards skill polarization [9] Group 9: Concerns Over AI-Generated Content - Reddit co-founder Ohanian warned that much of the internet is "dead," overwhelmed by AI-generated content [10] - Reports indicate that automated traffic could reach 51% by 2024, with AI-generated articles surpassing human-written ones [10] - Research suggests that training models on AI-generated data may lead to a decline in model performance [10] Group 10: Andrej Karpathy on AGI Development - AI expert Andrej Karpathy expressed skepticism about the current state of AI agents, predicting that AGI is still a decade away [11] - He criticized the noise in reinforcement learning and the limitations of pre-training methods [11] - Karpathy anticipates that AGI will contribute modestly to GDP growth, emphasizing the importance of education in the AI era [11]

Product Update - Anthropic Engineering Blog 发布了关于 Agent Skills 的开发者使用技巧，Agent Skills 是一种通过指令文件夹、脚本和资源扩展 Claude 功能的新方法 [1]