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2026-05-31 · 内容获取于 05/31 13:37

Microsoft 开源文件转 Markdown 工具 MarkItDown

GitHub Trending

微软开源 Python 工具,可将 PDF、Office 文档等转换为 Markdown 格式,适合文档处理和 LLM 数据预处理场景。

推荐理由:开源且可即用,对文档管道构建和预训练数据处理极具实操价值。

Claude Code 推出动态工作流功能

Claude Blog

Anthropic 在 Claude Code 中引入动态工作流,允许开发者定义多步骤任务自动编排,提升 Agent 复杂任务的执行能力。

推荐理由:了解 Agent 工作流最新演进方向,对使用 Claude Code 的开发者有直接启发。

PyTorch 官方入门指南:torch.profiler 使用教程

Hugging Face Blog

Hugging Face 博客发布 PyTorch Profiler 系列教学(Part 1),帮助开发者定位模型训练和推理的性能瓶颈。

推荐理由:实战性强的性能调优教程,深度学习工程团队可直接采用。

Anthropic 分享跨产品安全隔离工程实践

Anthropic Engineering

Anthropic 详解如何在 claude.ai、Claude Code 和 Cowork 中实施安全隔离,防止 Agent 越权操作。

推荐理由:大型 Agent 系统的安全设计范本,架构师和安全性负责人必读。

Opus 4.8 上线:协作和代码能力小幅提升

Smol AI News

Anthropic 发布 Claude Opus 4.8,合作行为和代码生成能力有改进,但文档解析部分出现退化,整体为小版本迭代。

推荐理由:关注模型迭代动态,但对开发者无可直接上手的行动点。

LangGraph 管道用于生产级数据工程

Hacker News

一篇实践博客,演示如何使用 LangGraph 构建生产数据工程管道,涵盖状态管理与多步骤编排。

推荐理由:面向数据工程师的 LangGraph 落地参考,可直接套用模式。

Boston Children’s 用 AI 辅助诊断 40 余种罕见病

OpenAI News

波士顿儿童医院利用 OpenAI 技术改进患者护理,减少运营负担,并帮助确诊超过 40 例罕见疾病。

推荐理由:典型案例说明 AI 在垂直医疗领域的落地效果,有参考价值。

高中生用智能体拿下粤港澳科创大赛冠军

LinuxDo

一位高中生利用 AI 智能体参赛并夺得粤港澳学生科创大赛智能体赛道冠军,并发 vlog 分享速通经验。

推荐理由:社群案例证明 AI 工具降低了创作和参赛门槛,激励更多人动手。

Anthropic 研究:将编码 Agent 用于社会科学

Anthropic Research

Anthropic 发表研究论文,探索使用编码 Agent 辅助社会科学研究中的数据分析、模拟与假设检验。

推荐理由:跨学科应用思路有新意,对社科学者或跨领域研究者有启发。

VLM 空间表征研究:远看不代表真理解

HuggingFace Trending Papers

论文探讨视觉语言模型在空间推理任务中的表现是否源于真正的 3D 理解,发现模型可能依赖统计捷径而非表征。

推荐理由:对 VLM 空间认知能力的批判性分析,适合关注模型可解释性的研究者。

microsoft/markitdown

Python · ★ 132,881 · 🍴 9,092 · 📈 2,470 stars today

Python tool for converting files and office documents to Markdown.

中文介绍 用 Python 将各类文件(包括 Office 文档)快速转换为 Markdown 格式,解决了内容提取和格式统一问题,适合需要批量处理文档或生成结构化文本的开发者和数据工作者。

harry0703/MoneyPrinterTurbo

Python · ★ 72,327 · 🍴 10,368 · 📈 2,768 stars today

利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.

中文介绍 基于 AI 大模型一键生成高清短视频,自动化完成文案、配音、画面合成,解决内容创作者制作过程中的重复劳动问题,适用于社交媒体营销和个人创作者。

anthropics/claude-code

Python · ★ 128,480 · 🍴 20,952 · 📈 592 stars today

Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.

中文介绍 运行在终端中的 AI 编码代理,能理解整个代码库,自动执行日常任务、解释复杂代码并处理 Git 工作流,显著提升开发效率,适合需要智能代码助手的软件工程师。

cursor/plugins

TypeScript · ★ 1,495 · 🍴 121 · 📈 205 stars today

Cursor plugin specification and official plugins

中文介绍 提供 Cursor 编辑器的插件规范与官方插件库,使开发者可以扩展 Cursor 的功能,解决编辑器个性化扩展需求,适用于希望在 AI 编程环境中添加自定义能力的用户。

revfactory/harness

HTML · ★ 4,329 · 🍴 630 · 📈 55 stars today

A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.

中文介绍 一种元技能系统,用于设计领域特定智能体团队、定义专用智能体并生成其所需技能,解决了多智能体协作的编排问题,适合构建复杂 AI 工作流的开发者。

EveryInc/compound-engineering-plugin

TypeScript · ★ 18,457 · 🍴 1,393 · 📈 349 stars today

Official Compound Engineering plugin for Claude Code, Codex, Cursor, and more

中文介绍 Compound Engineering 官方插件,为 Claude Code、Codex、Cursor 等编码助手提供复合工程能力,增强多步骤代码生成和调试流程,适合需要高级代码编排的开发者。

affaan-m/ECC

JavaScript · ★ 199,481 · 🍴 30,624 · 📈 908 stars today

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

中文介绍 智能体性能优化系统,为 Claude Code、Codex 等编码工具提供技能、本能、记忆、安全和研究优先的开发支持,解决智能体高效运行与资源管理问题,适合 AI Agent 开发者。

OpenBMB/VoxCPM

Python · ★ 22,892 · 🍴 2,677 · 📈 779 stars today

VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning

中文介绍 无需分词器的多语言语音生成模型,支持创意声音设计和逼真声音克隆,解决了传统 TTS 系统依赖分词器的局限,适合语音合成研究和多媒体制作。

galilai-group/stable-worldmodel

Python · ★ 1,489 · 🍴 169 · 📈 318 stars today

A platform for reproducible world model research and evaluation

中文介绍 可复现世界模型研究与评估平台,提供标准化训练和评测流程,解决了世界模型领域缺乏统一基准的问题,适合 AI 研究员和强化学习开发者。

Crosstalk-Solutions/project-nomad

TypeScript · ★ 27,401 · 🍴 2,688 · 📈 469 stars today

Project N.O.M.A.D, is a self-contained, offline survival computer packed with critical tools, knowledge, and AI to keep you informed and empowered—anytime, anywhere.

中文介绍 自包含离线生存计算机,集成关键工具、知识库和 AI,确保在无网络环境下仍能获得信息和支持,解决了极端场景下的计算需求,适合户外探险、应急响应和离线工作。

run-llama/liteparse

Rust · ★ 7,998 · 🍴 473 · 📈 925 stars today

A fast, helpful, and open-source document parser

中文介绍 快速、开源、易用的文档解析器,从 PDF、Word 等文档中提取结构化内容,解决了非结构化文档解析繁琐的问题,适用于信息提取、RAG 系统等场景。

chen08209/FlClash

Dart · ★ 40,420 · 🍴 2,530 · 📈 187 stars today

A multi-platform proxy client based on ClashMeta,simple and easy to use, open-source and ad-free.

中文介绍 基于 ClashMeta 的多平台代理客户端,简单易用、开源无广告,解决了跨设备网络代理配置复杂的问题,适用于需要科学上网和流量管理的用户。

FareedKhan-dev/train-llm-from-scratch

Jupyter Notebook · ★ 2,369 · 🍴 379 · 📈 327 stars today

A straightforward method for training your LLM, from downloading data to generating text.

中文介绍 从数据下载到文本生成,手把手教你从头训练大语言模型,方法直接清晰,解决了缺乏系统性 LLM 训练教程的问题,适合想深入理解 LLM 原理的开发者和研究人员。

ruvnet/RuView

Rust · ★ 69,027 · 🍴 9,209 · 📈 655 stars today

π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.

中文介绍 利用普通 WiFi 信号实现实时空间感知、生命体征监测和存在检测,无需任何摄像头,解决了隐私敏感的传感需求,适用于智能家居、健康监护和安防场景。

DataTalksClub/data-engineering-zoomcamp

Jupyter Notebook · ★ 41,813 · 🍴 8,289 · 📈 274 stars today

Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼

中文介绍 免费 9 周速成课,教授构建生产级数据管道,涵盖数据工程核心技能,解决了系统学习数据工程缺乏免费优质资源的问题,适合转行或进阶的数据从业者。

OpenMOSS/MOSS-TTS

Python · ★ 2,677 · 🍴 240 · 📈 62 stars today

MOSS‑TTS Family is an open‑source speech and sound generation model family from MOSI.AI and the OpenMOSS team. It is designed for high‑fidelity, high‑expressiveness, and complex real‑world scenarios, covering stable long‑form speech, multi‑speaker dialogue, voice/character design, environmental soun

中文介绍 开源语音与声音生成模型家族,专注于高保真、高表现力并适配复杂现实场景,解决了 TTS 在真实环境中表现不足的问题,适合语音应用开发和 AI 研究。

dreammis/social-auto-upload

Python · ★ 11,870 · 🍴 2,097 · 📈 73 stars today

自动化上传视频到社交媒体:抖音、小红书、视频号、tiktok、youtube、bilibili

中文介绍 自动将视频上传到抖音、小红书、视频号、TikTok、YouTube、Bilibili 等主流平台,解决跨平台发布视频耗时重复的问题,适合内容创作者和营销人员。

anthropics/skills

Python · ★ 144,267 · 🍴 17,000 · 📈 454 stars today

Public repository for Agent Skills

中文介绍 Anthropic 官方智能体技能公开仓库,提供可供 AI Agent 调用的技能模块,解决 Agent 能力扩展问题,适合使用 Claude 等模型的开发者构建复杂工作流。

codecrafters-io/build-your-own-x

Markdown · ★ 508,383 · 🍴 48,250 · 📈 817 stars today

Master programming by recreating your favorite technologies from scratch.

中文介绍 通过从零复现各种技术(如数据库、编译器、Git 等)来深入学习编程,解决了理论学习与实践脱节的问题,适合希望提升底层理解能力的各水平开发者。

Why Far Looks Up: Probing Spatial Representation in Vision-Language Models

👍 37

Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D understanding or reliance on statistical shortcuts in natural images. We introduce a representation-level analysis framework that constructs minimal co

中文介绍 论文提出表示级分析框架,研究视觉语言模型是否具备结构化3D理解能力,或仅依赖自然图像中的统计捷径。

DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation

👍 7

Robot manipulation critically depends on perception that preserves the action-relevant aspects of a scene. Yet most robot learning pipelines are built upon visual encoders pre-trained for static recognition or vision-language alignment, leaving motion understanding to downstream policies. We introdu

中文介绍 DynaFLIP提出三模态动态引导表示方法,用于机器人操作感知,解决视觉编码器缺乏运动理解的问题。

Tiny but Trusted: Efficient Vision-Language Reasoning for Time-Series Anomaly Detection

👍 0

Recent advances in Vision-Language Models (VLMs) have achieved impressive performance across many tasks, yet prior studies report unsatisfactory performance when applying large language or multimodal models to finding abnormal patterns in sequential data. Public anomaly detection benchmarks typicall

中文介绍 研究利用小尺寸视觉语言模型进行时序异常检测,提升效率与可信度,克服大模型在序列数据中表现不佳的问题。

Reducing Political Manipulation with Consistency Training

👍 0

Large language models (LLMs) exhibit systematic political bias across a variety of sensitive contexts. We find that LLMs handle counterpart topics from opposing political sides asymmetrically. We refer to this phenomenon as covert political bias and identify 7 categories of techniques through which

中文介绍 研究发现大语言模型存在系统性政治偏见,提出一致性训练减少操纵,识别出七类隐性偏见技术。

REPOT: Recoverable Program-of-Thought via Checkpoint Repair

👍 6

One-shot Program-of-Thought (PoT) emits a Python program that prints a primitive-action plan; a single invalid action silently invalidates the trajectory. We introduce RePoT (Recoverable PoT): a deterministic verified replay that walks the plan through the environment to its first invalid transition

中文介绍 REPOT提出可恢复程序式思考方法,通过检查点修复解决一步式PoT中无效动作导致轨迹失效的问题。

Xetrieval: Mechanistically Explaining Dense Retrieval

👍 17

Explaining why dense retrievers assign high relevance scores remains challenging because retrieval decisions are made through opaque high-dimensional embeddings. Existing explanations often focus on surface signals, such as lexical matches, token alignments, or post-hoc textual rationales, and thus

中文介绍 Xetrieval通过机制解释揭示密集检索器高分分配原因,针对高维嵌入的透明性挑战提出新方法。

CoHyDE: Iterative Co-Training of LLM Rewriter & Dense Encoder for Tool Retrieval

👍 4

Tool retrieval over large API catalogs is a core bottleneck for LLM agents: user queries arrive in colloquial, often underspecified language, while the catalog uses technical API vocabulary that no fixed encoder can bridge on its own. The two dominant training approaches, contrastive encoder fine-tu

中文介绍 CoHyDE提出迭代共训练大模型改写器与密集编码器的方法,解决工具检索中用户查询与API技术词汇的语义鸿沟。

EarlyTom: Early Token Compression Completes Fast Video Understanding

👍 25

Video large language models (Video-LLMs) have demonstrated strong capabilities in video understanding tasks. However, their practical deployment is still hindered by the inefficiency introduced by processing massive amounts of visual tokens. Although recent approaches achieve extremely low token ret

中文介绍 EarlyTom通过早期token压缩完成快速视频理解,减少视频大语言模型中大量视觉token的处理瓶颈。

When Cloud Agents Meet Device Agents: Lessons from Hybrid Multi-Agent Systems

👍 11

The design space of agentic AI inference spans two extremes: frontier large language models (LLMs), typically hosted in the cloud and offering strong performance across a wide range of tasks at substantially high cost, and more cost-efficient small language models (SLMs), which are amenable to on-de

中文介绍 研究混合多智能体系统中云端大模型与设备端小模型的协作设计空间,探讨性能与成本权衡。

Thinking Before Constraining: A Unified Decoding Framework for Large Language Models

👍 6

Natural generation allows Large Language Models (LLMs) to produce free-form responses with rich reasoning, yet the lack of structure makes outputs difficult to verify. Conversely, constrained decoding ensures standardized formats but can inadvertently restrict reasoning capabilities by imposing cons

中文介绍 提出统一解码框架,在自然生成与约束解码之间平衡,让大语言模型先思考再约束,兼顾推理与可验证性。

PhyGenHOI: Physically-Aware 4D Generation of Dynamic Human-Object Interactions

👍 8

We address the task of generating physically accurate and visually faithful 4D Human-Object Interaction (HOI). Given a static 3D human and target object represented as 3D Gaussian Splats (3DGS), our goal is to synthesize dynamic scenes where the human actively engages with the object through actions

中文介绍 PhyGenHOI实现物理感知的4D人-物交互生成,基于静态3DGS目标合成动态交互场景。

UniSteer: Text-Guided Flow Matching in Activation Space for Versatile LLM Steering

👍 21

Activation-based control steers large language models (LLMs) by intervening on their internal representations during inference, and has emerged as an effective paradigm for controlling behaviors such as persona and style. However, existing methods often rely on fixed steering directions or task-spec

中文介绍 UniSteer提出文本引导的激活空间流匹配方法,实现大语言模型的多样化行为控制,如风格和人物设定。

Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas

👍 1

We study two-level autoresearch for cooperation: an outer-loop AI agent autonomously redesigns the inner-loop pipeline of an LLM policy-synthesis system for multi-agent Sequential Social Dilemmas (SSDs). A researcher agent R (run as a coding agent) reads the inner-loop source code, edits system prom

Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering

👍 6

Applying reinforcement learning to improve factual accuracy in knowledge-intensive question answering faces a reward design dilemma. Response-level rewards provide only coarse supervision and cannot distinguish correct from incorrect statements within a reasoning trace. Sentence-level alternatives o

Colored Noise Diffusion Sampling

👍 17

Diffusion models achieve state-of-the-art image synthesis, with their generative trajectories fundamentally exhibiting a spectral bias, resolving low-frequency global structures early and high-frequency fine details later. Conventional stochastic differential equation (SDE) solvers fail to account f

CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists

👍 10

We introduce CausaLab, a scalable environment for evaluating interactive causal discovery by LLM agents. Unlike prior evaluations, CausaLab evaluates both whether an agent can solve a problem using causal evidence and whether its answer is grounded in a faithful recovered causal mechanism. Each epis

YoCausal: How Far is Video Generation from World Model? A Causality Perspective

👍 38

As video diffusion models (VDMs) advance toward world models, a key question arises: do they truly understand causality, or merely overfit to statistical temporal patterns? Existing benchmarks mostly rely on synthetic data, limiting real-world generalization due to the sim-to-real gap. We present Yo

PhoneWorld: Scaling Phone-Use Agent Environments

👍 0

A central bottleneck for phone-use agents is that controllable, reproducible environments covering real mobile behavior are hard to build at scale. Existing mobile-agent benchmarks have made important progress on evaluation, but they do not by themselves provide a scalable way to construct many new

WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction

👍 7

Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stale, and surface the right evidence at decision time. Existing benchmarks measure recall over static dialogue, collapse me

PRISM: A Multi-Dimensional Benchmark for Evaluating LLM Peer Reviewers

👍 10

The rapid growth in submissions to machine learning venues has strained the scientific peer-review system and intensified interest in LLM-based automated peer reviewers. However, how good these systems are actually, especially compared to human reviewers at catching scientific gaps, remains poorly u

Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning

👍 21

Equipping large language models with explicit skills has emerged as a promising paradigm for enabling autonomous agents to solve complex tasks. Agent skills can be inherently divided into general skills for broad cognitive transfer and task-specific skills for dynamic execution. However, existing sk

PANDO: Efficient Multimodal AI Agents via Online Skill Distillation

👍 5

Recent advances in multimodal web agents often rely on increased inference-time computation, including rollout search, verifier passes, offline skill discovery, and specialist model stacks. This raises a central question: can a web agent become more efficient as it accumulates experience, rather tha

Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases

👍 2

Reinforcement Learning from Human Feedback (RLHF) is the standard method to align Large Language Models (LLMs) with human preferences. In this work, we introduce alignment tampering, a potential vulnerability where the LLM undergoing alignment influences the preference dataset, causing RLHF to ampli

Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments

👍 5

Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches either overestimate risk based on reachable states or struggle to predict accurate trajectories under high occlusion uncertainty. To address these

Reflective Prompt Tuning through Language Model Function-Calling

👍 3

Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for adapting models without parameter updates. Yet prompt design remains labor-intensive and highly sensitive to formatting, phrasing, and instruction

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

👍 0

Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective intervention thus requires anticipating scams before the intent becomes explicit. This is inherently challenging, as decisions must rely on partial

How to Build a Software Factory with Claude Code That Ships Features While You Sleep

@sairahul1 · 106.0K 粉丝 · 2.8M 阅 · 1.5K 赞 · 204 转

I thought I was using AI to code. I was actually just typing faster. Here is the difference — and the 7-agent system that changed everything. Save this. It will save you months. THE PROBLEM NOBODY

中文介绍 博主拆解了用AI编程的错误认知:不是打字更快,而是构建了7个agent协作的系统,能自动完成需求分析、代码生成、测试部署等环节,实现无人值守发布功能。核心是「软件工厂」工作流,而非单个AI工具。

AI Agents: The Complete Course

@sairahul1 · 106.0K 粉丝 · 203.2K 阅 · 500 赞 · 82 转

Everyone is talking about AI agents in 2026. Most people have no idea how they actually work. This changes today. I spent weeks distilling everything: courses, books, real builds, production failures.

中文介绍 一份浓缩多门课程、多本书籍及实际构建经验的AI agent教程,覆盖从理论到生产故障的全链路知识,适合希望真正理解agent机制而非空谈概念的学习者。

How to Build a Claude Research Agent That Reads the Internet Every Morning and Briefs You in 5 Mins

@cyrilXBT · 181.7K 粉丝 · 127.8K 阅 · 533 赞 · 80 转

Most people start their day the same way. They open Twitter and spend 20 minutes scrolling through noise looking for the three things that actually matter. They open their email and get pulled into

中文介绍 教你用Claude构建一个每天早晨自动抓取网络信息、5分钟内输出简报的研究agent,替代手动刷Twitter和邮件的低效流程,强调信息筛选而非被动接收。

How I Use Cursor

@poteto · 26.6K 粉丝 · 86.5K 阅 · 540 赞 · 48 转

I need to get something off my chest. Before my interview @cursor_ai, I had never actually used Cursor. At Meta, Claude Code was explosively taking off. I even paid for a personal $200 a month plan

中文介绍 一位Meta员工坦诚分享从未使用过Cursor,在面试前才临时上手,并对比了Claude Code在Meta内部的爆发式采用情况,包括自己的200美元个人订阅体验。

Step-By-Step LLM Engineering Projects (2026 Edition)

@TheAhmadOsman · 59.9K 粉丝 · 54.5K 阅 · 512 赞 · 65 转

At some point, reading about LLMs stops being enough. You need to build the stack yourself: Tokenizer first, then embeddings, position, attention, Transformer blocks, objectives, decoding, cache, long

中文介绍 2026版LLM工程实战项目路线图:从Tokenizer、嵌入、位置编码、注意力机制、Transformer模块,到解码、缓存、长上下文处理等,手把手构建完整模型栈。

THE DIFF THAT CHANGED EVERYTHING

@difflawb · 20.3K 粉丝 · 21.9K 阅 · 1.1K 赞 · 389 转

How a 40-line shell script became infrastructure In August 2024, Andrej Karpathy — co-founder of OpenAI, former AI Director at Tesla — published something unexpectedly small. Not a paper. Not a model.

中文介绍 追溯Karpathy在2024年8月发布的40行shell脚本如何演变为基础设施,剖析一个看似微小的diff如何改变运行模式,强调纯工程思维驱动而非大模型。

how i make AI videos (a beginner’s breakdown)

@0xileri · 7.3K 粉丝 · 12.2K 阅 · 533 赞 · 63 转

I’ve been getting a lot of DMs since I started posting AI videos, so I figured I’d just write it all out. Fair warning: I’m still learning too. This is just what’s been working for me. tools

中文介绍 一位AI视频新手分享自己从零起步的创作工作流,列出实用工具链条,并坦言仍在学习中,内容实在而非炫技,适合同样刚入门的人作为参考。

The Start of the End: AI Replacement Has Begun

@ActionModelAI · 57.1K 粉丝 · 5.8K 阅 · 505 赞 · 344 转

We are witnessing the beginning of the biggest economic shift in modern history. And most people still don’t realize it. AI replacement is no longer some distant sci-fi prediction. It has started.

中文介绍 断言AI替代已从科幻变成现实,正引发现代历史上最大的经济变革,但多数人仍未察觉,警示性观点而非具体产品或教程。

该源今日无内容。

Ship your first Managed Agent

中文介绍 Claude 平台推出 Managed Agent 功能,指导开发者部署和管理自主 AI 代理。

Ship your first Managed Agent

中文介绍 Claude 平台推出 Managed Agent 功能,指导开发者部署和管理自主 AI 代理。

[AINews] Founders and Forward Deployed Engineers

a quiet day lets us highlight the new AIE WF focuses

中文介绍 本期AI新闻聚焦创始人与前线部署工程师的角色,并介绍了AIE WF的新工作重点。

Boston Children’s uses AI to unlock new diagnoses

Boston Children’s Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases.

中文介绍 波士顿儿童医院利用OpenAI技术改善患者护理、减轻运营负担,并协助诊断了40多种罕见疾病。

How Braintrust turns customer requests into code with Codex

How Braintrust engineers use Codex with GPT-5.5 to run experiments and code faster.

中文介绍 Braintrust的工程师使用GPT-5.5驱动的Codex,将客户请求快速转化为代码,加速实验与开发。

How the Pope’s Magnifica Humanitas offers a template for individuals to meet the AI moment

Pope Leo XIV’s new encyclical on artificial intelligence includes a statement that warrants serious attention from technologists and policymakers: “Technology is never neutral.” Magnifica Humanitas (“Magnificent Humanity”) is a clarion call to all people to act with courage and solidarity as we ente

中文介绍 教皇利奥十四世发布关于人工智能的通谕《崇高人性》,强调“技术绝非中立”,呼吁科技与政策界以勇气和智慧应对AI时代。

not much happened today

**Anthropic** rolled out **Claude Opus 4.8**, which shows incremental improvements but mixed benchmark results, including better cooperation and coding behavior but some regressions in document parsing. Platform updates include mid-conversation system instructions enhancing long agent sessions, thou

中文介绍 Anthropic发布Claude Opus 4.8,带来增量改进,包括更好的协作与编码行为,但文档解析出现回归;平台新增对话中系统指令功能。

Strengthening societal resilience with Rosalind Biodefense

OpenAI launches Rosalind Biodefense, expanding trusted access to GPT-Rosalind for vetted developers and U.S. government partners advancing biodefense, public health, and pandemic preparedness through frontier AI.

中文介绍 OpenAI启动Rosalind生物防御项目,向经过审查的开发者及美国政府合作伙伴提供GPT-Rosalind访问权限,以推进生物防御与公共卫生。

A shared playbook for trustworthy third party evaluations

OpenAI shares guidance on third-party AI evaluations, covering how to assess model capabilities, safeguards, and validity for frontier systems.

中文介绍 OpenAI发布第三方AI评估指南,涵盖如何评估前沿模型的能力、安全措施与有效性。

How Endava builds an agentic organization with Codex

Learn how Endava uses Codex to build an agentic organization, accelerating software delivery and reducing requirements analysis from weeks to hours.

中文介绍 Endava利用Codex构建智能体型组织,将软件交付中的需求分析从数周缩短至数小时。

The AI Hype Index: AI gets booed in graduation season

It is one thing to say AI will change the world. It is another to expect the class of 2026 to applaud it. In fact, when former Google CEO Eric Schmidt told University of Arizona graduates that their task is to help shape AI, he was met with a resounding chorus of boos. “I can…

中文介绍 前谷歌CEO埃里克·施密特在亚利桑那大学演讲中呼吁毕业生塑造AI,却遭遇嘘声,反映出公众对AI的怀疑情绪。

[AINews] Cognition raises $1B in $26B Series D

coding is an uncapped TAM market

中文介绍 Cognition以260亿美元估值完成10亿美元D轮融资,强调编码市场具有无限潜力。

Anthropic raises $65B in Series H at a $965B post-money valuation, releases Opus 4.8 and Dynamic Workflows

**Anthropic** announced a massive **$65B Series H financing** at a **$965B valuation**, led by **Altimeter, Dragoneer, Greenoaks, and Sequoia**, with run-rate revenue surpassing **$47B**. They launched **Claude Opus 4.8**, an update to Opus 4.7 featuring "sharper judgment," "more honesty," and longe

中文介绍 Anthropic完成650亿美元H轮融资,投后估值9650亿美元,营收超470亿美元;同时发布Claude Opus 4.8及动态工作流功能。

【CHY公益站】庆祝GPT系列稳定一天

本帖使用社区公益推广,符合推广要求。我申明并遵循社区要求的以下内容: 我的项目是免费使用的,无收费(变相收费、赞助)部分: 是 我的帖子已经打上 公益推广 标签: 是 我的项目属于个人项目,与公司或商业机构无关: 是 我的项目不存在QQ、TG等群组引流: 是 我的项目不存在非运营必要的网站引流: 是 我的项目不存在为他人推广、AFF: 是 我的项目无关联的商业项目: 是 我的站点存在登录,并已接入 LINUX DO Connect: 是 我帖子内的项目介绍,AI生成、润色内容部分已截图发出: 是 以上选择我承诺是永久有效的,接受社区和佬友监督: 是 以下为项目介绍正文内容,AI生成、润色内容已

君の公益,一人一百刀

「慕鸢の公益站」 「君の公益」近况 君の公益站能用 LDC 吗,每天 25,半个小时就没了 大家的LDC还是留着交换别的服务吧,我这里不太需要,我直接免费送 希望大家天天开心 也希望小可怜天天开心 点击即领100刀兑换码 cdk.linux.do LINUX DO CDK Linux Do 社区 CDK 快速分享平台 - 让分享变得更简单 顺手展示下风控系统 315 个帖子 - 294 位参与者 阅读完整话题

【CHY公益站】新的主贴

本帖使用社区公益推广,符合推广要求。我申明并遵循社区要求的以下内容: 我的项目是免费使用的,无收费(变相收费、赞助)部分: 是 我的帖子已经打上 公益推广 标签: 是 我的项目属于个人项目,与公司或商业机构无关: 是 我的项目不存在QQ、TG等群组引流: 是 我的项目不存在非运营必要的网站引流: 是 我的项目不存在为他人推广、AFF: 是 我的项目无关联的商业项目: 是 我的站点存在登录,并已接入 LINUX DO Connect: 是 我帖子内的项目介绍,AI生成、润色内容部分已截图发出: 是 以上选择我承诺是永久有效的,接受社区和佬友监督: 是 以下为项目介绍正文内容,AI生成、润色内容已

麦当劳6.1免费领甜筒

麦当劳6.1有个活动,除了四岁一下都可以领一个不知道多大的甜筒 25 个帖子 - 22 位参与者 阅读完整话题

opus-4.8 怎么能难用成这个样子

根本没有办法跟 4.6 比,跑个任务罗里吧嗦奇奇怪怪的,还有各种语言表达,怎么能 der 成这样? 4.7 的"稳稳的接住你"就不说了。 4.8的"侦查清楚了"(怎么,去看个服务器去敌后侦查了是么?): 还有:“可还是被oom 打爆了”(啊OOM 好厉害哦,都打爆 swap 了啦): 还有:“决定性结论出来了”(咋的,上面那些废话自己也承认是非决定结论?): 还有决定性结论刚说完,下面又来了一个:“真正的结论”(我请问呢??你孙杨吗?): 决定性结论完了还有:“决定性证据”(哦,医生上线了): 还有:“它好好活着”“我刚才误报了” 还有非常非常非常的多,我真的懒得截图了。 佬友们用吧,反正我是

分享今天的西郊公园

由于最近才加入L站,还不能频繁回复。在此统一感谢喜欢照片的各位佬友,相机是富士中画幅gfx100s,镜头是GF20-35是超广角变焦镜头,等效全画幅的16-28mm,这个比例是传统的胶片相机中的XPAN画幅,在中画幅富士机身上有一个内置的65:24可以实现机内裁切出这比例的JPG(当然也可以后期裁切),照片的故事感一方面也可能来自于这一较为“陌生”的比例。今天去的时候其实比较阴凉,反而是蚊虫较多。佬友们去逛的话,可以从西郊宾馆的南门进入。 17 个帖子 - 16 位参与者 阅读完整话题

Accenture to acquire Ookla

https://www.theverge.com/tech/889234/downdetector-ookla-spee..., https://archive.ph/FR8NDhttps://arstechnica.com/information-technology/2026/03/downd...

Ask HN: Have you ever created a custom RISC-V ISA extension?

Curious about the real pain points, not the spec writing, but what came after: toolchain patches, simulator forks, getting someone else to reproduce your work.Building a registry for reproducible extension packages: www.extensilica.com/wizard