2026-05-31（内容获取于 05/31 14:42）

microsoft/markitdown

Python · ★ 133,010 · 🍴 9,103 · 📈 2,470 stars today

Python tool for converting files and office documents to Markdown.

中文介绍 微软开源的 Python 工具，用于将各类文件（Word、Excel、PDF 等）转换为 Markdown 格式。适合需要批量处理文档、提取文本内容的开发者，典型场景包括文档迁移、数据预处理或构建知识库。

harry0703/MoneyPrinterTurbo

Python · ★ 72,449 · 🍴 10,377 · 📈 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 利用 AI 大模型一键生成高清短视频的工具。用户只需输入主题，即可自动完成脚本撰写、配音、剪辑和字幕生成，适合自媒体创作者快速制作营销或娱乐短视频。

anthropics/claude-code

Python · ★ 128,501 · 🍴 20,954 · 📈 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 Anthropic 推出的终端智能编程助手，能理解整个代码库，帮助执行日常任务、解释复杂代码、管理 git 工作流。适合开发者直接通过命令交互来加速编码、调试和版本控制。

cursor/plugins

TypeScript · ★ 1,506 · 🍴 121 · 📈 205 stars today

Cursor plugin specification and official plugins

中文介绍 Cursor 官方插件仓库，定义了插件规范并提供一系列官方插件。开发者可以基于此扩展 Cursor 编辑器的功能，实现自定义代码补全、lint 检查等增强体验。

revfactory/harness

HTML · ★ 4,342 · 🍴 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 一个元技能框架，用于设计领域特定的 Agent 团队，定义专业 Agent 并生成它们使用的技能。适合需要构建多 Agent 协作系统的 AI 工程师，简化复杂任务编排。

EveryInc/compound-engineering-plugin

TypeScript · ★ 18,467 · 🍴 1,394 · 📈 349 stars today

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

中文介绍 Compound Engineering 官方插件，支持 Claude Code、Codex、Cursor 等主流 AI 编程工具。提供复合工程能力，帮助开发者更高效地进行多步骤、多智能体的代码生成与重构。

affaan-m/ECC

JavaScript · ★ 199,526 · 🍴 30,632 · 📈 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 Agent 性能优化系统，涵盖技能、本能、记忆、安全和研究优先开发。专为 Claude Code、Codex、Cursor 等工具设计，提升 Agent 在复杂任务中的稳定性和效率。

OpenBMB/VoxCPM

Python · ★ 22,922 · 🍴 2,684 · 📈 779 stars today

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

中文介绍 VoxCPM2 免分词器的 TTS 模型，支持多语言语音生成、创意声音设计和逼真语音克隆。适合需要高质量语音合成的应用，如语音助手、有声书制作或虚拟角色配音。

galilai-group/stable-worldmodel

Python · ★ 1,499 · 🍴 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，提供标准化的训练、测试和对比流程。适合强化学习和机器人领域的研究者，用于构建和验证能预测环境动态的世界模型。

Crosstalk-Solutions/project-nomad

TypeScript · ★ 27,417 · 🍴 2,691 · 📈 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 自包含的离线生存计算机，集成了关键工具、知识库和 AI，可在无网络环境下提供信息和辅助决策。适合野外探险、应急救灾或偏远地区使用，确保随时随地都能访问智能支持。

run-llama/liteparse

Rust · ★ 8,027 · 🍴 474 · 📈 925 stars today

A fast, helpful, and open-source document parser

中文介绍 快速、开源、轻量的文档解析器。能高效提取 PDF、Word 等文档中的文本和结构化信息，适合 RAG 管道或数据提取场景，尤其注重速度和易用性。

chen08209/FlClash

Dart · ★ 40,432 · 🍴 2,532 · 📈 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，界面简洁，易用且开源无广告。支持多种代理协议，适合需要科学上网的用户在 Windows、macOS、Android 等设备上管理代理规则。

FareedKhan-dev/train-llm-from-scratch

Jupyter Notebook · ★ 2,394 · 🍴 382 · 📈 327 stars today

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

中文介绍 提供从数据下载到文本生成的端到端 LLM 训练方法，流程清晰、步骤直接。适合希望深入理解 LLM 训练过程的学习者或需要定制小模型的研究者。

ruvnet/RuView

Rust · ★ 69,068 · 🍴 9,213 · 📈 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 利用商用 WiFi 信号实现实时空间感知、生命体征监测和存在检测，无需摄像头。适合隐私敏感场景的智能家居、老人看护或安防监控等。

DataTalksClub/data-engineering-zoomcamp

Jupyter Notebook · ★ 41,825 · 🍴 8,290 · 📈 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 周数据工程课程，教授构建生产级数据管道的技能。涵盖批处理、流处理、数据仓库等主题，适合想进入数据工程领域或系统学习最佳实践的开发者。

OpenMOSS/MOSS-TTS

Python · ★ 2,687 · 🍴 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 开源的语音和声音生成模型家族，专注于高保真、高表现力以及复杂真实场景。支持多语种、情感表达和声音克隆，适合语音交互应用和创意内容制作。

dreammis/social-auto-upload

Python · ★ 11,885 · 🍴 2,099 · 📈 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 自动化视频上传工具，支持抖音、小红书、视频号、YouTube、Bilibili 等主流平台。适合内容创作者快速分发视频，实现一键多平台发布，提升发布效率。

anthropics/skills

Python · ★ 144,301 · 🍴 17,003 · 📈 454 stars today

Public repository for Agent Skills

中文介绍 Anthropic 官方 Agent Skills 公共仓库，提供可复用的插件和技能模块。开发者可以基于这些技能扩展 Claude Code 等 AI 工具的功能，实现代码审查、文档生成等特定任务。

codecrafters-io/build-your-own-x

Markdown · ★ 508,443 · 🍴 48,252 · 📈 817 stars today

Master programming by recreating your favorite technologies from scratch.

中文介绍 通过从零重造流行技术（如 Git、Redis、Docker）来提升编程能力的教程合集。适合想要深入理解底层原理、动手实践的内向学习者或进阶开发者。

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

👍 37

05/28 08:00

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 视觉语言模型在空间推理基准上表现优异，但研究者通过表示层分析框架探究其是否真正具备结构化3D理解，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

05/28 08:00

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 机器人操作依赖保留场景动作相关方面的感知，但现有视觉编码器主要预训练于静态识别或视觉语言对齐，忽略了下游运动理解。DynaFLIP提出三模态动态引导表示方法。

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

👍 0

05/28 08:00

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 视觉语言模型在时序异常检测中面临挑战，现有模型在识别序列数据异常模式方面表现不佳。Tiny但可信的VLM推理方法被提出以提升效率与可靠性。

Reducing Political Manipulation with Consistency Training

👍 0

05/28 08:00

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 大型语言模型在敏感话题上表现出系统性政治偏见，对对立政治立场的话题处理不对称。研究识别出7类隐蔽政治偏见技术，并提出通过一致性训练减少操纵。

REPOT: Recoverable Program-of-Thought via Checkpoint Repair

👍 6

05/28 08:00

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 一次性程序思维（PoT）产生Python程序打印行动计划，但无效行动会使轨迹失效。RePoT通过检查点修复实现可恢复的确定性验证重放，确保轨迹有效性。

Xetrieval: Mechanistically Explaining Dense Retrieval

👍 17

05/28 08:00

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 解释密集检索器为何分配高相关性分数具有挑战性，因其决策基于不透明的高维嵌入。Xetrieval提出机械解释方法，超越表面词汇匹配。

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

👍 4

05/28 08:00

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 工具检索是LLM智能体的核心瓶颈：用户查询语言口语化，而API目录使用技术词汇。CoHyDE通过迭代共训练LLM改写器与密集编码器来弥合这一差距。

EarlyTom: Early Token Compression Completes Fast Video Understanding

👍 25

05/28 08:00

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 视频大语言模型在理解任务上表现出色，但处理大量视觉令牌导致效率低下。EarlyTom通过早期令牌压缩加速视频理解，同时保持性能。

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

👍 11

05/28 08:00

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 智能体AI推理设计空间包括云端大模型和本地小模型。研究探索混合多智能体系统，平衡强大性能与成本效益。

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

👍 6

05/28 08:00

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 自然生成允许自由响应但难以验证，约束解码确保格式但限制推理。提出统一解码框架「先思考后约束」，兼顾推理与结构。

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

👍 8

05/28 08:00

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 面向动态人-物交互的物理感知4D生成任务。给定静态3D人体和目标对象（3DGS表示），合成人体主动与物体互动的动态场景。

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

👍 21

05/28 08:00

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 基于激活的LLM控制通过干预内部表示来引导行为，但现有方法依赖固定方向。UniSteer提出文本引导的流匹配方法，实现灵活且可变的LLM引导。

Discovering Cooperative Pipelines: Autoresearch for Sequential Social Dilemmas

👍 1

05/28 08:00

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

05/28 08:00

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

Towards Verifiable Multimodal Deep Research: A Multi-Agent Harness for Interleaved Report Generation

👍 9

05/28 08:00

Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthesizes scattered evidence into long-form reports. However, verifiable multimodal deep research remains challenging due to open-ended synthesis without

Colored Noise Diffusion Sampling

👍 18

05/28 08:00

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

👍 11

05/28 08:00

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

Token-Level Generalization in LoRA Adapter Backdoors: Attack Characterization and Behavioral Detection

👍 3

05/28 08:00

We show that LoRA adapters, the dominant distribution format for fine-tuned LLMs, can be reliably backdoored through training data poisoning while preserving baseline task performance. On a Qwen 2.5 1.5B prompt-injection classifier, a small fraction of poisoned examples drives a clean-accuracy-prese

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

👍 38

05/28 08:00

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

05/28 08:00

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

05/28 08:00

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

05/27 08:00

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

RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains

👍 8

05/27 08:00

Pointwise reward modeling offers critical signals for LLM post-training, yet struggles with absolute scoring in subjective, non-verifiable settings. Rubric-based methods address this by decomposing evaluation into explicit criteria, but existing approaches typically depend on frontier LLMs and suffe

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

👍 21

05/27 08:00

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

05/26 08:00

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

05/26 08:00

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

CONF-KV: Confidence-Aware KV Cache Eviction with Mixed-Precision Storage for Long-Horizon LLM

👍 4

05/24 08:00

Long-horizon LLM inference turns the key--value (KV) cache into the dominant GPU memory consumer and makes per-token attention increasingly expensive. Many common eviction policies use static recency windows or historical attention, leaving unused a signal computed on every decoding step: the model'

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

👍 5

05/21 08:00

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

👍 4

05/20 08:00

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

05/09 08:00

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

05/25 16:46

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 分享一个由7个AI代理协作的「软件工厂」系统，能把功能开发流程自动化，让Claude Code在你睡觉时持续交付代码。作者认为多数人只是打字更快，而非真正用AI编程，这套架构可大幅节省数月开发时间。

AI Agents: The Complete Course

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

05/24 16:25

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 一份从课程、书籍到真实构建和投产失败案例中提炼的AI代理完整教程。作者花了数周整理，涵盖代理的工作原理，适合想从理论到实践系统学习的开发者。

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

05/25 11:16

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 搭建一个Claude研究代理，每天清晨自动浏览互联网，5分钟内整理出你关心的核心信息，避免在推特和邮件中无效刷信息。适合希望高效获取每日重点内容的用户。

How I Use Cursor

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

05/26 02:15

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 一位前Meta工程师坦诚分享自己使用Cursor的经历：在面试前从未用过Cursor，在Meta时Claude Code正爆发式流行，甚至自费购买每月200美元的套餐。从零开始、如何上手以及真实感受。

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

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

05/25 11:01

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 一套2026年版的LLM工程实践项目路线图：从Tokenizer、嵌入、位置编码、注意力机制、Transformer模块，到训练目标、解码、缓存、长上下文等模块，手把手教你从零搭建自己的LLM栈。

THE DIFF THAT CHANGED EVERYTHING

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

05/25 23:13

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 讲述一个仅有40行shell脚本如何从一个小技巧演变为基础设施的故事。源于2024年8月Karpathy的某个小的公开分享，揭示了极简代码的巨大杠杆效应。

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

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

05/25 02:10

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视频创作者面向初学者的完整拆解：工具链、工作流、操作细节。作者坦言自己仍在学习中，只分享当前对他有效的实践经验，适合想入门AI视频制作的人。

The Start of the End: AI Replacement Has Begun

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

05/25 19:29

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 观点类内容：称AI替代已不再是科幻预言，而是正在发生的最大的经济转型。强调多数人尚未意识到这一转变已经开始。

Browsers Are Dead. Codex Just Replaced Them.

05/28 22:56

中文介绍 Codex 被认为将取代传统浏览器，成为新的交互界面。

AI Agents: Every NEW Claude & Codex Feature Explained

05/24 06:29

中文介绍 详细解读 Claude 和 Codex 的所有新AI代理功能。

Codex: Build Your Full AI Marketing Team (Agents + Skills)

05/18 23:31

OpenAI just released Codex Mobile

05/16 02:58

Codex Mobile App Released (Complete Setup Guide)

05/15 09:35

Vibe Coding for Beginners (Full Course 2026)

05/08 03:28

Codex is The NEW Best AI Coding Tool (Here's Why)

05/03 04:35

7 Tools That Make Codex 10x MORE Powerful

04/30 09:19

Learn 95% of Codex in 30 minutes

04/29 10:08

With Codex and GPT 5.5 you can just do things.

04/26 07:48

[AINews] Founders and Forward Deployed Engineers

Latent Space · 05/30 09:57

a quiet day lets us highlight the new AIE WF focuses

中文介绍 Latent Space 的 AI 新闻简报关注创始人及一线部署工程师的动态，并介绍新的 AIE WF 重点方向。

Boston Children’s uses AI to unlock new diagnoses

OpenAI News · 05/29 20:00

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 波士顿儿童医院使用 OpenAI 技术改善患者护理、减轻运营负担，并已帮助诊断 40 多种罕见疾病。

How Braintrust turns customer requests into code with Codex

OpenAI News · 05/29 20:00

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

中文介绍 Braintrust 工程师利用 Codex 与 GPT-5.5 加速编码实验，将客户需求快速转化为代码。

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

MIT Tech Review AI · 05/29 18:00

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 教皇方济各发布通谕《伟大的人性》，指出“技术绝非中性”，呼吁个人以勇气应对人工智能时代。

not much happened today

Smol AI News · 05/29 13:44

**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，在协作和编码方面有所改进，但文档解析出现回归。平台新增对话中系统指令，提升长对话体验。

Strengthening societal resilience with Rosalind Biodefense

OpenAI News · 05/29 11:00

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 推出 Rosalind Biodefense，扩展 GPT-Rosalind 的可信访问，支持经审查的开发者及美国政府机构推进生物防御、公共卫生和疫情准备。

[AINews] Anthropic raises $965B Series H, releases Opus 4.8 and Dynamic Workflows/ultracode

Latent Space · 05/29 10:07

Total Anthropic victory!

中文介绍 Anthropic 完成 9650 亿美元 H 轮融资，并发布 Opus 4.8 及动态工作流/超编码功能。

A shared playbook for trustworthy third party evaluations

OpenAI News · 05/29 08:00

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，涵盖评估模型能力、安全措施及有效性等方面，旨在推动评估可信任。

Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler

Hugging Face Blog · 05/29 08:00

中文介绍 Hugging Face 发布 PyTorch 性能分析入门指南，介绍 torch.profiler 的使用方法。

Opus 4.8 🧠, Anthropic at $965B 💰, Microsoft’s coding model 👨‍💻

TLDR AI · 05/29 08:00

中文介绍 今日 AI 要闻：Opus 4.8 发布、Anthropic 估值 9650 亿美元、微软推出新编码模型。

The Age of Async Agents — Cognition's Walden Yan & OpenInspect's Cole Murray

Latent Space · 05/29 02:41

80% Devin Commits, Spec-to-PR Workflows, Full VMs, Agent Memory, and PMs Shipping Code

中文介绍 Cognition 与 OpenInspect 探讨异步代理时代：Devin 提交代码占 80%、规范到 PR 工作流、完整虚拟机、代理记忆，以及产品经理编写代码。

How Endava builds an agentic organization with Codex

OpenAI News · 05/28 20:00

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 构建代理型组织，将软件交付加速，需求分析从数周缩短至数小时。

The AI Hype Index: AI gets booed in graduation season

MIT Tech Review AI · 05/28 17:51

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 AI 炒作指数：毕业季 AI 遭嘘声。前谷歌 CEO 埃里克·施密特在亚利桑那大学毕业演讲中呼吁毕业生塑造 AI，却遭到全场嘘声。

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

Latent Space · 05/28 15:26

coding is an uncapped TAM market

中文介绍 Cognition 在 D 轮融资中以 2600 亿美元估值融资 10 亿美元，聚焦编码市场不可限量的总规模。

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

Smol AI News · 05/28 13:44

**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），领投方包括 Altimeter、Dragoneer、Greenoaks 和 Sequoia，年化营收超 470 亿美元。同时发布 Claude Opus 4.8，具备“更精准判断”等改进。

美区 AppleID 有办法用中国教育优惠认证吗？

05/31 11:10

4 回复 · Apple 节点

AI 原生开发，大伙能分享一下经验吗？

05/31 08:51

5 回复 · 程序员 节点

AI 编程时代， MVP 思维已经失效了？

05/30 19:25

25 回复 · 程序员 节点

以防大家不知道怎么让 Agent 一直干活不停下来

05/30 18:05

10 回复 · 程序员 节点

大模型不听话咋整（skill）

05/30 17:29

4 回复 · 程序员 节点

Claude Code 团队计划，非中转站

05/30 17:18

11 回复 · 程序员 节点

大佬们 vibe coding 的项目怎么样了

05/30 17:17

70 回复 · 程序员 节点

关于 iPhone air 国行 esim 卡的一个想法

05/30 10:49

9 回复 · Apple 节点

美区礼品卡被连着砍单 3 次

05/29 17:40

17 回复 · Apple 节点

计划外，换机请教🙏

05/29 11:18

6 回复 · Apple 节点

Show HN: Komi-learn – continuous memory and self-improvement for coding agents

05/31 13:11

3 points · 0 comments

Ahoy, DECmate II the little PDP-8 that could

05/31 12:42

20 points · 1 comments

Building a LangGraph pipeline for production data engineering

05/31 12:38

10 points · 0 comments

Mechanical Pencin: A website about the hidden engineering in everyday objects

05/31 08:25

37 points · 6 comments

Microsoft Office 2019 and 2021 for Mac view-only conversion

05/31 07:26

777 points · 262 comments

Cheese Paper: a text editor specifically designed for writing

05/31 06:58

89 points · 21 comments

Shantell Sans (2023)

05/31 06:06

189 points · 16 comments

The AV2 Video Standard Has Released (Final v1.0 Specification)

05/31 05:46

131 points · 29 comments

Design Engineering Magazine

05/31 04:46

81 points · 9 comments

wolfSSL releases a new product; wolfCOSE a zero alloc C embbedded COSE stack

05/31 04:42

82 points · 14 comments

Domain expertise has always been the real moat

05/31 04:40

463 points · 281 comments

Dusklight – GC Twilight Princess Decompiled

05/31 04:24

88 points · 11 comments

Parallel Reconstruction of Lawful TLS Wiretapping

05/31 03:47

84 points · 38 comments

Jef Raskin, the Visionary Behind the Mac (2013)

05/31 03:42

96 points · 41 comments

Show HN: 500 years of Joseon court omens as an observability dashboard

05/31 03:23

108 points · 17 comments

Zig ELF Linker Improvements Devlog

05/31 01:29

192 points · 56 comments

OpenRouter raises $113M Series B

05/31 01:27

402 points · 195 comments

Microcode inside the Intel 8087 floating-point chip: register exchange

05/31 01:27

109 points · 18 comments

Accenture to acquire Ookla

05/31 00:28

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

Voxel Space (2017)

05/30 22:25

272 points · 58 comments

Openrsync: An implementation of rsync, by the OpenBSD team

05/30 18:51

361 points · 151 comments

Leo's first encyclical attacks technological messianism

05/30 18:30

208 points · 251 comments

Pandoc Templates

05/30 17:56

384 points · 50 comments

Zig: Build System Reworked

05/30 16:38

341 points · 223 comments

A Gentle Introduction to Lattice-Based Cryptography [pdf]

05/29 11:22

53 points · 0 comments

I found a seashell in the middle of the desert

05/29 10:49

291 points · 77 comments

Gustav Klimt and Egon Schiele in Conversation (2018)

05/29 06:29

34 points · 4 comments

Associative learning turns DEET from aversive to appetitive in Aedes aegypti

05/29 03:11

14 points · 0 comments

Racket v9.2 is now available

05/28 17:42

88 points · 12 comments

90% of the T Distribution

05/27 21:29

45 points · 12 comments