整理 | 屠敏 出品 | CSDN（ID：CSDNnews） 今天凌晨，OpenAI 的劲敌 Anthropic 正式发布下一代 Claude 模型——Claude 4。 这次更新主要带来了两款模型：Claude Opus 4 与 Claude Sonnet 4。据官方介绍，这两款模型在代码生成、高级推理能力以及智能体任务执行方面 设立了新的性能标杆。 其中，Claude Opus 4 被称之为"全球最强的编程模型"，专为复杂、长时间运行的 任务而设计，可自主运行数小时。另一款升级版本 Claude Sonnet 4 相较于其前作 Son net 3.7 实现了大幅提升，在编程和推理方面更加精准响应用户指令。 殊不知，这波 Claude 4 的发布引发了与 OpenAI 之间竞争的升级，还因上线前测试中出现"自主逃逸"等行为引发热议。 连续 7 小时重构代码，最强编码模型来了！ 根据官方透露，全新的 Claude Opus 4 与 Claude Sonnet 4 不仅在性能上有了大幅提升，还可以处理之前版本无法搞定的很多任务。譬如， Claude Opus 4 能在玩《宝可梦》的同时连续运行重构代码任务长达 ...

随着以大模型为代表的第四次技术革命迈入关键阶段，科技发展正经历一场前所未有的范式转换，"AGI 新纪元"的浪潮汹涌澎湃。如何立足于这一变革 的关键节点，重塑对新一轮技术浪潮的认知，凝聚共识、深化交流，成为每一位技术从业者高度关注的核心议题。 作为中文技术社区的领军者，CSDN 以前瞻性的视野，倾力打造了聚焦全球技术创新高地的系列活动——「智研社-The Intelliger」。旨在汇聚全球技 术翘楚与行业精英，深刻洞察技术发展趋势，积极推动技术革新与战略思维的碰撞。 关于「智研社-The Intelliger」 「智研社-The Intelliger」由 CSDN 发起创立，前身为 CTO 俱乐部，自 2009 年创办以来，一直是极具影响力的高端技术管理者分享与交流平台。随 着大模型技术的迅猛发展，人工智能将成为未来 10 年最有影响力的技术力量。「智研社-The Intelliger」将继续发挥平台作用，连接技术领袖，推动 行业发展，共同开创 AGI 新纪元。 图1 CSDN 创始人&董事长 蒋涛 图2 「CSDN和它的朋友们」现场分享 本次"CSDN 与 TA 的朋友们巴黎见面会"的圆满举办，标志着CSD ...

采访 | 唐小引 整理 | 张红月 出品丨AI 科技大本营（ID：rgznai100） 从生成式 AI 到 Agentic AI ，互联网正在从"信息获取"转向"任务完成"。 强化学习带来的整个推理范式使得智能体的规划能力大大提升，让大模型具备了更强的自主规划与工具调用能力，尤其是在推理链构建、任务分解、多 Agent 协作等方面，能力提升显著。 这一趋势正在引发全球范围的智能体竞赛。 全球科技巨头抢滩智能体 放眼全球，科技巨头纷纷加速 AI Agent 布局： 国内市场同样热潮涌动，比如在 2025 腾讯云 AI 产业应用峰 会上， 腾讯集团高级执行副总裁、云与智慧产业事业群 CEO 汤道生宣布腾讯各项业务全 面拥抱 AI，以大模型、智能体、知识库和基础设施"四个加速"助力 AI 打造普惠生产力。其中，在智能体方面，腾讯云全新升级 了 智能体开发平台 （TCADP）， 旨在融合自身在知识管理、工作流编排以及 AI 能力上的优势，助力企业构建更高效、更智能的 Agent 应用，而大家所熟知的腾讯多项 C 端与 B 端应用，如 QQ 浏览器、腾讯健康、 腾讯云代码助手 CodeBuddy、腾讯企点营销云等都加入 ...

Core Viewpoint - Embodied intelligence is a key focus in the AI field, particularly in humanoid robots, raising questions about the best path to achieve true intelligence and the current challenges in data, computing power, and model architecture [2][5][36]. Group 1: Development Stages of Embodied Intelligence - The industry anticipates 2025 as a potential "year of embodied intelligence," with significant competition in multimodal and embodied intelligence sectors [5]. - NVIDIA's CEO Jensen Huang announced the arrival of the "general robot era," outlining four stages of AI development: Perception AI, Generative AI, Agentic AI, and Physical AI [5][36]. - Experts believe that while progress has been made, the journey towards true general intelligence is still ongoing, with many technical and practical challenges remaining [36][38]. Group 2: Transition from Autonomous Driving to Embodied Intelligence - Many researchers from the autonomous driving sector are transitioning to embodied intelligence due to the overlapping technologies and skills required [17][22]. - Autonomous driving is viewed as a specific application of robotics, focusing on perception, planning, and control, but lacks the interactive capabilities needed for general robots [17][19]. - The integration of expertise from autonomous driving is seen as a bridge to advance embodied intelligence, enhancing technology fusion and development [18][22]. Group 3: Key Challenges in Embodied Intelligence - Current robots often lack essential capabilities, such as tactile perception, which limits their ability to maintain balance and perform complex tasks [38][39]. - The operational capabilities of many humanoid robots are still in the demonstration phase, lacking the ability to perform tasks in real-world contexts [38][39]. - The complexity of high-dimensional systems poses significant challenges for algorithm robustness, especially as more sensory channels are integrated [39]. Group 4: Future Applications and Market Focus - The focus for developers should be on specific application scenarios rather than pursuing general capabilities, with potential areas including home care and household services [48]. - Industrial applications are highlighted as promising due to their scalability and the potential for replicable solutions once initial systems are validated [48]. - The gap between laboratory performance and real-world application remains significant, necessitating a focus on improving system accuracy in specific contexts [46][47].

Core Viewpoint - The article highlights the significant breakthroughs by ZhiYuan Robotics in the field of embodied intelligence, introducing the world's first action sequence-driven embodied world model EVAC and the evaluation benchmark EWMBench, both of which are now open-source. These innovations aim to establish a new development paradigm of "low-cost simulation - standardized evaluation - efficient iteration" to empower global research in embodied intelligence and accelerate technology implementation and industry development [1][21]. Group 1: Industry Challenges - The evolution of embodied intelligence faces two key constraints: high costs and risks associated with real machine validation during testing, and the lack of an efficient utilization mechanism for vast amounts of real machine data, which limits diversity generation and generalization training [3][21]. - ZhiYuan Robotics aims to address these challenges by leveraging its technical expertise and insights into industry pain points, launching the action sequence-driven world model EVAC and the evaluation benchmark EWMBench to redefine the development paradigm of embodied world models [3][21]. Group 2: Technological Breakthroughs - EVAC represents a dynamic world model capable of reproducing complex interactions between robots and their environments, marking a transition from traditional simulation to generative simulation [5][21]. - The core capabilities of EVAC include precise mapping from "physical execution" to "pixel space," enabling end-to-end generation through a multi-level action condition injection mechanism [7][21]. Group 3: Dual Value Proposition - EVAC introduces a generative simulation evaluation scheme that addresses the high costs and risks of real machine evaluations, allowing for interactive evaluation pipelines that significantly enhance the efficiency of strategy model screening [9][10]. - The data augmentation engine of EVAC can generate large-scale data from minimal expert trajectory data, leading to a task success rate increase of up to 29% for strategy models trained with this augmented data [10][21]. Group 4: Evaluation Benchmark EWMBench - EWMBench is the world's first evaluation benchmark for embodied world models, designed to fill industry gaps and establish a unified, credible evaluation standard [12][21]. - The benchmark features a three-dimensional evaluation system focusing on scene consistency, motion correctness, and semantic alignment and diversity, utilizing advanced metrics for precise assessment [15][20]. Group 5: Collaborative Synergy - The synergy between EnerVerse, EVAC, and EWMBench creates a "spiral evolution" where EnerVerse provides a robust framework for EVAC, while the diverse high-quality data generated by EVAC continuously optimizes the EnerVerse model [18][21]. - The combination of EVAC and EWMBench has been officially selected as the baseline system and evaluation standard for the AgiBot World Challenge @ IROS 2025, offering a valuable platform for developers and teams engaged in embodied intelligence research [19][21].

在 AI 光环的放大效应之下，今天的产品经理可能比程序员更重要。 "用户体验至上。"这是乔布斯在产品设计中始终坚持的核心信条。他曾说："人们并不知道他们想要什么，直到你把它摆在他们面前。"在 AI 大模型时 代，这一理念显得尤为重要。产品经理的挑战不再只是"做出来"，而是如何将技术真正转化为用户价值：让智能真正可感，让体验真正可用。 8 月 15–16 日，由 CSDN & Boolan 联合举办的「2025 全球产品经理大会」将在北京威斯汀酒店召开。围绕生成式 AI 与智能体产品设计、商业落地 与用户体验创新等 12 大专题方向，展开为期两天的深度分享与思维碰撞。 这是一次关于"产品与 AI 如何共创未来"的深度讨论，也是一场专属于产品 人的智能时代聚会。 一场聚焦 AI 产品未来的行业盛会，亮点前瞻： AI 时代的产品全景图 12 大核心专题揭晓 本届大会共设 12 大专题板块，全景式呈现 AI 驱动下的产品实践路径与战略方法： 1.生成式人工智能产品｜GenAI Products AI 产品发展前沿深度解析 全球化实战案例干货分享 增长与创新策略碰撞交流 用户需求新思维解码洞察 从模型能力到交互体验，探 ...

在人工智能的世界，有一群人正深耕于推动通用人工智能（AGI）从科幻走向现实。CSDN、《新程序员》特别策划 " AGI 技术 50 人 "访谈栏目 ，挖掘 AI 背后的思考，激荡 AGI 的智慧，走近那些在 AI 领域不断探索、勇于创新的思想领袖和技术先锋们的心路历程。 年初 DeepSeek 爆火，引起 X、谷歌、OpenAI、Anthropic 的顶级模型大战，随后又有 Manus 通用 Agent 问世、全世界的程序员拜入 Cursor 门下……在 2025 的 AI 炮火中，有一个名字总在提醒我们，需要时不时地从日常的喧嚣中抬起头，去思考一些更长远、也更根本的问题。 作者 | 王启隆 出品丨 《 新程序员 》编辑部 Nick Bostrom ，一位出生于瑞典，后来在牛津大学开启其重要学术生涯的哲学家。他生于 1973 年，早年似乎并不安于传统学校教育的束缚，甚至有 资料显示他高中最后一年是在家完成学业的。但这反而让他得以广泛涉猎人类学、艺术、文学乃至科学等多个领域，在伦敦求学期间还曾尝试过单口喜 剧。 2005年，Nick Bostrom 在牛津大学创办了人类未来研究所（Future of Human ...

整理 | 郑丽媛 回顾 上一次 I/O 大会至今，Sundar Pichai 表示 谷歌已发布了十多个新模型和研究突破，并推出了 20 多个重 大 AI 产品与新功能。 他解释道， " 我 们的目标很简单：让最优秀的模型和产品尽快触达用户， 因此 我们正以前所未有的速度推进发布节奏。 " 他指出 ，相比第一代 Gemini 1.0 Pro， 如今的 Gemini 2.5 Pro 几乎 发生了 "跃迁式"变化： 在 LMArena 榜单上横扫各大类别 、 在多项基准测试中 刷新 纪录； 在代码领域也取得 巨大进展， 登顶 WebArena 榜首。 出品 | CSDN（ID：CSDNnews） 昨天， 微软在 Build 大会上刚刚甩出"Windows 子系统"和"Copilot 开源"的重磅炸弹 ，整个开发者圈还没从热议中缓过劲来，转眼今天凌晨，谷歌就 在 I/O 大会上掏出了自己的"王炸"牌——一场 AI 盛宴，正式上演！ 从凌晨 1 点开始，这场 持续了 2 小时的发布会彻底印证了网友的预测： 曾经占据谷歌 I/O 大会中心的 Android 系统正在"靠边站"，C 位已经留给了 更具革命性的 AI。 无论 ...

Core Viewpoint - The article discusses the advancements and future potential of video generation models, emphasizing the need for deeper understanding capabilities in visual AI, moving beyond mere generation to true comprehension [1][5][4]. Group 1: Video Generation Models - The team at Jumpscale has open-sourced two significant video generation models: Step-Video-T2V and Step-Video-TI2V, both with 30 billion parameters, which have garnered considerable attention in the AI video generation field [1][12]. - Current diffusion video models, even at 30 billion parameters, show limited generalization capabilities compared to language models, but possess strong memory capabilities [5][26]. - The future of video generation models may involve a shift from mere generation to models that possess deep visual understanding, requiring a change in learning paradigms from mapping learning to causal prediction learning [5][20]. Group 2: Challenges and Innovations - The article outlines six major challenges in AI-generated content (AIGC), focusing on data quality, efficiency, controllability, and the need for high-quality data [39][32]. - The integration of autoregressive and diffusion models is seen as a promising direction for enhancing video generation and understanding capabilities [21][20]. - The importance of high-quality, diverse natural data is highlighted as a critical factor in building robust foundational models, rather than relying heavily on synthetic data [14][16]. Group 3: Future Predictions - Predictions indicate that foundational visual models with deeper understanding capabilities may emerge within the next 1-2 years, potentially leading to a "GPT-3 moment" in the visual domain [4][36]. - The convergence of video generation with embodied intelligence and robotics is anticipated, providing essential visual understanding capabilities for future AI applications [37][42]. - The article suggests that the future of AIGC will enable individuals to easily create high-quality content, democratizing content creation [38][48].

以下文章来源于CSDN ，作者CSDN CSDN . 成就一亿技术人 整理 | 屠敏 出品 | CSDN（ID：CSDNnews） 每年初夏，科技圈总会迎来一波"新品大秀"，尤其是 5 月和 6 月几乎成了开发者的"小春晚"的热闹时刻——微软 Build、Google I/O、苹果 WWDC 轮 番登场，带来一大波新技术、新工具，想方设法吸引开发者的注意。今年是微软打头阵，Build 2025 大会于 5 月 20 日凌晨 12:05 率先登场。 这场大会上，微软 CEO 纳德拉和 CTO Kevin Scott 亲自上阵，令人意外的是，一直不太对付的 OpenAI CEO Sam Altman 和特斯拉 CEO 马斯克，还 有英伟达 CEO 黄仁勋，也都"出现"在这场大会上，只是以线上视频接入的形式，分别与纳德拉来了场关于合作、大模型、芯片等维度的简短对话。 整体来看，AI 无疑是微软最重要的战略方向。不过，今年「开源」也成了另一大贯穿全场的关键词，其不仅将 VS Code 上 Copilot 的核心功能开放了 出 来，就连 适 用于 Linux 的 Windows 子系统（ WSL）也重磅开源了，实属令人 ...