2026-06-09（内容获取于 06/09 06:19）

mvanhorn/last30days-skill

Python · ★ 34,336 · 🍴 2,811 · 📈 3,558 stars today

AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary

中文介绍 面向AI agent的技能模块，可自动搜索Reddit、X、YouTube、HN、Polymarket及全网话题，聚合多源信息后生成有据可依的摘要，适合舆情监测与快速调研场景。

RyanCodrai/turbovec

Python · ★ 8,729 · 🍴 807 · 📈 1,730 stars today

A vector index built on TurboQuant, written in Rust with Python bindings

中文介绍 基于TurboQuant构建的高性能向量索引，使用Rust编写并提供Python绑定，适用于大规模向量近似最近邻搜索，兼顾速度与内存效率。

google/skills

Python · ★ 12,342 · 🍴 966 · 📈 481 stars today

Agent Skills for Google products and technologies

中文介绍 Google官方发布的Agent技能集合，封装了Google产品与技术的API能力，供开发者构建基于Google生态的自主代理。

refactoringhq/tolaria

TypeScript · ★ 13,527 · 🍴 951 · 📈 649 stars today

Desktop app to manage markdown knowledge bases

中文介绍 桌面端知识管理应用，专注于Markdown格式的知识库，提供本地化管理与浏览功能，适合个人笔记与文档整理场景。

Panniantong/Agent-Reach

Python · ★ 24,020 · 🍴 2,026 · 📈 796 stars today

Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

中文介绍 赋予AI agent网页浏览能力的CLI工具，支持搜索和读取Twitter、Reddit、YouTube、GitHub、Bilibili、小红书等平台，无需API密钥，零费用。

danielmiessler/Personal_AI_Infrastructure

TypeScript · ★ 15,393 · 🍴 2,158 · 📈 121 stars today

Agentic AI Infrastructure for magnifying HUMAN capabilities.

中文介绍 个人AI基础设施框架，聚焦增强人类能力的自主Agent系统，提供可扩展的架构用于构建和管理个性化AI工作流。

santifer/career-ops

JavaScript · ★ 50,439 · 🍴 10,330 · 📈 477 stars today

AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.

中文介绍 基于Claude Code的AI求职系统，内置14种技能模式、Go语言仪表盘、PDF生成与批量处理功能，帮助用户自动化管理求职流程。

phuryn/pm-skills

★ 12,604 · 🍴 1,494 · 📈 112 stars today

PM Skills Marketplace: 100+ agentic skills, commands, and plugins — from discovery to strategy, execution, launch, and growth.

中文介绍 项目管理技能市场，提供100+ Agent技能、命令与插件，覆盖从发现、策略、执行到发布增长的全链路，帮助PM提升自动化能力。

openai/plugins

JavaScript · ★ 2,299 · 🍴 289 · 📈 296 stars today

OpenAI Plugins

中文介绍 OpenAI官方插件集合，为ChatGPT等模型提供扩展能力，允许连接第三方服务和工具，增强模型在具体场景中的实用功能。

Andyyyy64/whichllm

Python · ★ 3,406 · 🍴 200 · 📈 103 stars today

Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.

中文介绍 一键运行的本地LLM评测工具，基于真实基准而非参数量，为你的硬件推荐运行效果最佳的模型，支持即时比较。

MemPalace/mempalace

Python · ★ 54,888 · 🍴 7,158 · 📈 237 stars today

The best-benchmarked open-source AI memory system. And it's free.

中文介绍 开源AI记忆系统，在基准测试中表现优异，免费使用，为Agent提供持久化、可检索的上下文记忆能力，提升长期对话连贯性。

roboflow/supervision

Python · ★ 42,304 · 🍴 3,781 · 📈 1,140 stars today

We write your reusable computer vision tools. 💜

中文介绍 可复用的计算机视觉工具库，封装了目标检测、跟踪、标注等常见CV流水线模块，简化从模型输出到可视化分析的开发流程。

CopilotKit/CopilotKit

TypeScript · ★ 34,095 · 🍴 4,303 · 📈 398 stars today

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

中文介绍 面向Agent与生成式UI的前端框架，支持React、Angular、移动端和Slack等平台，实现了AG-UI协议，帮助开发者快速构建内嵌AI能力的界面。

TapXWorld/ChinaTextbook

Roff · ★ 72,953 · 🍴 16,330 · 📈 593 stars today

所有小初高、大学PDF教材。

中文介绍 收录中国小学、初中、高中及大学全学科PDF教材的公开资源库，供学习与参考使用。

luongnv89/claude-howto

Python · ★ 35,724 · 🍴 4,342 · 📈 393 stars today

A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.

中文介绍 Claude Code的可视化实战指南，从基础概念到高级Agent用法，附带可直接复制使用的模板，提供即学即用的价值。

aaif-goose/goose

Rust · ★ 48,063 · 🍴 5,062 · 📈 699 stars today

an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM

中文介绍 开源可扩展AI Agent，超越代码建议，能安装、执行、编辑和测试任务，支持对接任意LLM，适用于自动化开发与运维场景。

Empirical Study on the Characteristics and Evolution of AI-usage in GitHub Repositories: Evidence from Code Comments

👍 0

06/05 08:00

Developers increasingly use AI tools such as ChatGPT, Copilot, and Claude in everyday software workflows, but prior studies often evaluate LLM outputs in isolation rather than examining how developers adapt them in real projects. We analyze 35,361 GitHub code comments that explicitly reference AI us

中文介绍 一项研究通过分析35,361条GitHub代码注释，探讨开发者在实际项目中如何适应ChatGPT、Copilot、Claude等AI工具，而非仅在孤立环境下评估LLM输出。

ECI_{sem}: Semantic Residual Effective Contrastive Information for Evaluating Hard Negatives

👍 1

06/05 08:00

Hard-negative source selection for dense retrieval is usually decided only after fine-tuning and downstream evaluation. We propose ECI_{sem}, a semantic residual variant of Effective Contrastive Information (ECI) that ranks candidate negative sources using frozen target-encoder embeddings. ECI_{sem}

中文介绍 研究提出ECI_sem，一种语义残差变体的有效对比信息方法，可在冻结目标编码器的情况下对难负例源进行排序，用于稠密检索中的难负例选择。

Towards Retrieving Interaction Spaces for Agentic Search

👍 1

06/05 08:00

Retrieval for search agents is still inherited from non-agentic information retrieval: a retriever ranks the corpus and the agent reads a small set of returned documents. Recent direct corpus interaction (DCI) work shows that agents can instead interact with the raw corpus through shell tools such a

中文介绍 针对代理搜索的检索提出新方向，指出代理可直接与原始语料交互而非仅读取返回文档，以拓展交互空间。

AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization

👍 24

06/05 08:00

Despite being a pivotal frontier, interactive world modeling remains underexplored in terms of the versatile controllability required by practical scenarios. To bridge this gap, we present AnchorWorld, a framework that advances egocentric simulation through enhanced interaction integrity and a flexi

中文介绍 提出AnchorWorld框架，通过增强交互控制能力推动体感仿真中的世界建模，实现基于视图演化的自定义交互。

MMAE: A Massive Multitask Audio Editing Benchmark

👍 39

06/05 08:00

We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation testbed designed for general-purpose instruction-based audio editing. Spurred by the shift toward intelligent creation, interactive editing has rapidly expanded from visual domains, pioneere

中文介绍 推出MMAE基准，首个面向通用指令音频编辑的大规模多任务评估平台，覆盖从视觉到音频的交互编辑扩展。

Stream3D-VLM: Online 3D Spatial Understanding with Incremental Geometry Priors

👍 4

06/05 08:00

Despite advances in 3D scene understanding, existing 3D Large Multimodal Models operate in offline settings, requiring complete scene observations or predefined video clips. In this paper, we present an online 3D vision-language model that enables real-time spatial understanding from streaming video

中文介绍 提出Stream3D-VLM在线3D视觉语言模型，支持实时空间理解，无需完整场景观测或预定义视频片段。

Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings

👍 69

06/05 08:00

Large language models exhibit impressive zero-shot capabilities across a wide range of downstream tasks. However, they struggle to function as off-the-shelf embedding models, leading to suboptimal performance on massive text embedding benchmarks. In this paper, we identify a potential cause underlyi

中文介绍 研究发现大语言模型的解嵌入矩阵可充当文本嵌入的特征透镜，提升其作为嵌入模型在零样本任务上的表现。

Watch, Remember, Reason: Human-View Video Understanding with MLLMs

👍 12

06/05 08:00

Video understanding is being rapidly transformed by multimodal large language models (MLLMs), as research moves from short clips to long, multimodal, and knowledge-intensive video scenarios. These scenarios require models to handle sparse evidence, long-range dependencies, multimodal alignment, and

中文介绍 多模态大语言模型推动视频理解从短片段向长视频、多模态、知识密集型场景发展，需处理稀疏证据和长程依赖。

Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models

👍 4

06/04 08:00

Despite the rapid progress of Vision-Language Models (VLMs), the field lacks benchmarks that rigorously diagnose their true reasoning abilities and chart meaningful progress toward human-like multimodal intelligence. Most existing evaluations focus on piecemeal or disconnected tasks, obscuring criti

中文介绍 构建Almieyar-Oryx-BloomBench双语多模态基准，用于认知启发下严格评估视觉语言模型的推理能力。

UnpredictaBench: A Benchmark for Evaluating Distributional Randomness in LLMs

👍 12

06/04 08:00

We introduce UnpredictaBench, an evaluation that tests the ability of large language models (LLMs) to capture true underlying distributions. As LLMs are increasingly used as substitutes for other entities (e.g., for humans in economic simulations), the tendency of many models to collapse towards a s

中文介绍 推出UnpredictaBench基准，评估大语言模型捕获真实底层分布的能力，尤其针对其在经济模拟等替代人使用场景中的分布随机性。

Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation

👍 1

06/04 08:00

We study the transformation of autoregressive models (ARLMs) into diffusion language models (DLMs). Rather than pretraining from scratch, prior work replaces the causal attention in ARLMs with bidirectional attention and then trains the resulting model using a DLM objective. However, these approache

中文介绍 研究将自回归语言模型转换为扩散语言模型的有效蒸馏方法，通过在线策略蒸馏提升数据效率。

Compress-Distill: Reasoning Trace Compression for Efficient Knowledge Distillation

👍 1

06/04 08:00

Reasoning models produce long chain-of-thought traces that are costly to distill and encourage verbose student outputs. We study post-hoc compression of such traces before knowledge distillation. Two teachers, Qwen3.5-397B-A17B and gpt-oss-120B, generate about 283k correct traces each; two instructi

中文介绍 提出压缩蒸馏方法，在知识蒸馏前对推理模型的长思维链轨迹进行后处理压缩，减少学生模型输出冗长问题。

Robots Need More than VLA and World Models

👍 20

06/04 08:00

Generalist robot intelligence is often framed as a policy-scaling problem: collect more robot demonstrations, train larger Vision-Language-Action (VLA) models, and expect broader generalisation. In this position paper, we argue that this framing is incomplete. The central bottleneck is not only poli

Physics in 2-Steps: Locking Motion Priors Before Visual Refinement Erases Them

👍 12

06/04 08:00

Image-to-Video diffusion models leverage input images to generate visually stunning content, yet frequently produce motion that violates physical laws. We reveal a surprising finding: a 2-step generation often exhibits better physical consistency than a 50-step output from the same model. Through sp

SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations

👍 42

06/04 08:00

Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by disputants' shifting emotions, intentions, and context. Existing testbeds rely on a few expert-authored domains, vary mainly strategic posture, and score every turn against every topic, introducing

LLM Explainability with Counterfactual Chains and Causal Graphs

👍 12

06/04 08:00

Causal graphs provide a high-level language for making mechanisms transparent. Recent work uses Large Language Models (LLMs) to recover causal graphs of external-world processes. Instead, in this paper, we use causal graphs to model LLM inference itself, providing stakeholders with a transparent vie

Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators

👍 12

06/04 08:00

While Vision-Language Models (VLMs) have shown strong visual reasoning capabilities, their spatial reasoning abilities remain largely constrained to the observed images and text-oriented chain-of-thought. They often struggle to infer unobserved layouts, maintain cross-view consistency, and reason fr

SubtleMemory: A Benchmark for Fine-Grained Relational Memory Discrimination in Long-Horizon AI Agents

👍 17

06/04 08:00

Persistent AI assistants, such as OpenClaw, accumulate large collections of related memories over long-term interactions. As these memories grow, they may reinforce one another, diverge across contexts, or directly conflict, making correct assistance depend on memory relations rather than isolated r

Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models

👍 1

06/03 08:00

Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical information is not directly observable. Many such problems require imaginative perception: inferring what would be seen from an unseen viewpoint, tracing paths through occluded spaces, or integr

Reinforcement Learning from Rich Feedback with Distributional DAgger

👍 3

06/03 08:00

Reasoning models have advanced rapidly, but the dominant reinforcement learning from verifiable rewards (RLVR) recipe remains surprisingly narrow: sample many responses and reward each with a single bit indicating whether the final answer is correct. Yet many settings provide rich feedback, includin

GENEB: Why Genomic Models Are Hard to Compare

👍 42

06/03 08:00

Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reporting. As a result, claims of superiority or generality across models are often not directly comparable. We introduce GENEB, a large-scale diagnostic be

A Cookbook of 3D Vision: Data, Learning Paradigms, and Application

👍 2

06/02 08:00

3D vision has rapidly evolved, driven by increasingly diverse data representations, learning paradigms, and modeling strategies. Yet the field remains fragmented across representations and benchmarks, making it difficult to develop unified perspectives on efficiency, fidelity, and scalability. This

HarnessForge: Joint Harness and Policy Evolution for Adaptive Agent Systems

👍 4

06/01 15:00

LLM agents are increasingly expected to operate across heterogeneous task regimes that require distinct execution paradigms. This challenges fixed agent systems and motivates system-level meta-adaptation beyond isolated component updates. While existing works have adapted external harness or trained

LayerRoute: Input-Conditioned Adaptive Layer Skipping via LoRA Fine-Tuning for Agentic Language Models

👍 2

06/01 08:00

Agentic language model systems alternate between two structurally distinct step types: structured tool calls (short, deterministic, low perplexity) and open-ended planning/reasoning steps (long, complex, high perplexity). Despite this heterogeneity, current inference systems apply identical compute

Parametric Social Identity Injection and Diversification in Public Opinion Simulation

👍 1

06/01 08:00

Large language models (LLMs) have recently been adopted as synthetic agents for public opinion simulation, offering a promising alternative to costly and slow human surveys. Despite their scalability, current LLM-based simulation methods fail to capture social diversity, producing flattened inter-gr

Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback

👍 0

05/30 08:00

Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for agentic search remains challenging, often requiring heavy co-training or gold-standard annotations that limit real-world applicability. We propose Crit

Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation

👍 1

05/28 08:00

Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly important front-end for LLM-based assistants and agents. However, most current ASR systems still follow a single-pass paradigm, which is poorly aligned with human communication, where misunderst

CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning

👍 1

05/27 08:00

Language models can use verifiable rewards to improve at a wide variety of reasoning tasks. However, both parametric (e.g. RLVR) and non-parametric (e.g. prompt optimization) approaches to doing so typically require hundreds of training samples and thousands of model rollouts, making them expensive

SIA: Self Improving AI with Harness & Weight Updates

👍 8

05/26 08:00

Humans are the bottleneck in building and improving AI. Both the models and the agents that wrap them are written, tuned, and corrected by people. The long-horizon goal of an AI that can figure out how to improve itself remains open. Two largely disjoint research lines attack this bottleneck. The ha

SPACENUM: Revisiting Spatial Numerical Understanding in VLMs

👍 5

05/22 08:00

Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce numerical outputs such as action magnitudes and spatial coordinates. Although these numbers appear meaningful, it remains unclear whether these numerical outputs are genuinely grounded in spatia

Context as Topology: Why Your Agent's Memory Forgets, and How Structure Escapes It

@elpresidank · 116 粉丝 · 2.9M 阅 · 543 赞 · 35 转

06/02 19:14

Most AI agent memory is built on embeddings. And there's now a proof that this entire class of system is going to forget what you stored in it — and confidently make up things you never stored at all.

中文介绍 证明基于嵌入向量的智能体记忆系统本质上会遗忘，并自信编造未存储的信息。提出用拓扑结构解决记忆失效问题，挑战当前主流方法。

SpaceX IPOs in 7 days. I Fed the S1 Doc Into Claude. Here Is What It Found Buried in 300 Pages.

@DamiDefi · 96.5K 粉丝 · 2.3M 阅 · 584 赞 · 80 转

06/04 17:31

The number that stopped me was not the $2 trillion valuation. It was $791 million. That is what SpaceX made in net income in 2024. A profitable, growing aerospace company with a genuine moat in launch

How To Become An AI Engineer in 2026 (Without a CS Degree)

@sairahul1 · 111.8K 粉丝 · 710.8K 阅 · 509 赞 · 97 转

06/05 16:10

How To Become An AI Engineer in 2026. Without a CS degree. Without a bootcamp. Without knowing what a transformer is today. Here's what nobody tells you: The companies hiring right now don't need

How to master Dynamic Workflows in Claude Code: 6 patterns and 14 steps Anthropic engineers actually

@0xCodez · 3.3K 粉丝 · 637.2K 阅 · 510 赞 · 59 转

06/03 19:00

Most Claude Code users still write their workflows by hand. They chain prompts, copy outputs, paste them into the next prompt, fix what went wrong, repeat. 9 out of 10 builders haven’t tried Dynamic

Harness Engineering: What Every AI Engineer Needs to Know in 2026

@sairahul1 · 111.8K 粉丝 · 546.4K 阅 · 536 赞 · 94 转

06/07 16:53

In February 2026, a small OpenAI team shipped 1 million lines of production code. They didn't write a single line by hand. The AI agents wrote it. The humans designed the system that made the agents

Generative UI Is the New Frontend

@Saboo_Shubham_ · 116.2K 粉丝 · 263.3K 阅 · 517 赞 · 74 转

06/04 01:12

The frontend used to be a fixed thing. Designers drew it. Engineers built it. Users got what shipped. That's over. The interfaces shipping in 2026 are drawn partly by the agent itself, in real time,

How to get 100k YouTube subscribers in 3 hours (The Complete Guide)

@maubaron · 16.9K 粉丝 · 233.8K 阅 · 506 赞 · 19 转

06/06 03:22

Our YouTube channel has 125k subscribers and we've never made or uploaded a single video ourselves. This is a completely automated system. It is this very same strategy that made us the first app

Building cloud agent infrastructure: what's different, and what we learned

@intuitiveml · 6.4K 粉丝 · 171.3K 阅 · 524 赞 · 70 转

06/05 08:55

Most agent frameworks today assume a desktop. One user, one machine, one process. The agent runs while the laptop is open, writes to a local filesystem, holds API keys in environment variables, and

A guide to /goal 🥅

@dkundel · 19.3K 粉丝 · 116.9K 阅 · 523 赞 · 40 转

06/05 05:39

We launched the goal mode (or /goal) as a way to help you have Codex drive towards a concrete outcome. When you set a goal Codex will continue to work until the goal is achieved, whether that takes

State of Memory in Agent Harness

@mem0ai · 17.6K 粉丝 · 82.8K 阅 · 520 赞 · 60 转

06/02 22:49

Agent harnesses are where AI software actually runs. Cursor, Devin, Claude Code, Codex: these environments handle context, orchestrate tools, coordinate agents, and increasingly, manage memory. The

A harness for every task: dynamic workflows in Claude Code

@trq212 · 263.1K 粉丝 · 75.7K 阅 · 542 赞 · 36 转

06/03 04:26

Last week, we released dynamic workflows in Claude Code. Claude can now write its own harness on the fly, custom-built for the task at hand. While the default Claude Code harness is built for coding,

A Functional Taxonomy of World Models

@drfeifei · 738.0K 粉丝 · 72.2K 阅 · 699 赞 · 144 转

06/04 02:57

“The world is everything that is the case.” — Ludwig Wittgenstein, Tractatus Logico-Philosophicus, 1921 The world is not made of words. In an earlier essay, we argued that spatial intelligence is AI’s

How to Build a Custom Agent Harness

@sydneyrunkle · 7.5K 粉丝 · 69.5K 阅 · 511 赞 · 74 转

06/04 00:57

Building useful agents is largely about customization: connecting your agent to the right context, data, and environment(s) for the task at hand. At its core, an agent is a model calling tools in a

some notes on getting into frontier ai labs

@itsreallyvivek · 3.6K 粉丝 · 65.8K 阅 · 521 赞 · 28 转

06/05 23:48

A few days ago I wrote that getting into a frontier AI lab mostly comes down to two things: proven research and trench engineering. The more I think about it, the less these feel like separate skills.

I Gave Claude David Ogilvy's Writing Rules And Built A Legendary AI Writing Coach

@dickiebush · 441.8K 粉丝 · 57.7K 阅 · 519 赞 · 45 转

06/05 20:35

Legendary marketer David Ogilvy generated over $864 million for his clients. He was a British advertiser known as "The Father of Advertising." And in 1982, Ogilvy sent this 1-page memo to his staff:

Every Agentic Engineering Hack I Know (June 2026)

@mvanhorn · 30.8K 粉丝 · 54.5K 阅 · 545 赞 · 44 转

06/03 02:28

Three months ago I posted "Every Claude Code Hack I Know." It hit 913K views. @kevinrose had asked what IDE to use, and my answer was: "No IDE. Just plan.md files and voice." This used to be called

Your token spend is an AI architecture problem, not just a model problem

@jainarvind · 9.3K 粉丝 · 53.7K 阅 · 505 赞 · 68 转

06/04 06:04

Enterprise AI token spend is scaling quickly, especially as the technology shifts from simple chat assistants into coding agents, AI coworkers, and long-running workflows. These systems do far more

Claude Code Responds to All my Texts (Here's How)

06/09 06:10

中文介绍 YouTube博主Riley Brown展示了如何配置Claude Code，使其能自动回复短信，实现AI助手的主动交互。

Hermes Agent NEW Super-App and DeepSeek v4 Catches Up To Opus 4.8?

06/07 04:10

中文介绍 讨论了Hermes Agent超级应用及DeepSeek v4在性能上接近Opus 4.8的最新进展。

ChatGPT And Codex Are Merging (This Changes Everything)

06/04 06:17

Claude Opus 4.8: Everything You Need to Know

06/01 06:27

Browsers Are Dead. Claude Just Replaced Them.

05/28 22:56

Every NEW Claude Feature Explained

05/24 06:29

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

Confidential submission of draft S-1 to the SEC

OpenAI News · 06/08 22:00

OpenAI confirms a confidential S-1 submission to the SEC and has not yet determined timing for further action.

中文介绍 OpenAI 向美国证券交易委员会（SEC）秘密提交了 S-1 表格草案，目前尚未确定下一步行动的时间。

Built to benefit everyone: our plan

OpenAI News · 06/08 09:30

A vision for the future of AI, focusing on access, safety, and shared prosperity as OpenAI works to ensure AGI benefits everyone.

中文介绍 OpenAI 公布未来规划，聚焦通用人工智能（AGI）的访问性、安全性及共享繁荣。

Introducing the OpenAI Economic Research Exchange

OpenAI News · 06/08 08:00

OpenAI launches the Economic Research Exchange to study AI’s impact on jobs, productivity, and the economy. Applications are now open for selected research projects.

中文介绍 OpenAI 推出经济研究交流项目（Economic Research Exchange），研究 AI 对就业、生产力和经济的影响，现已开放研究项目申请。

Observability for developers building connectors

Claude Blog · 06/08 08:00

Observability for developers building connectors

中文介绍 面向构建连接器的开发者的可观测性指南。

Building intelligent apps for Apple platforms with Claude in the Foundation Models framework

Claude Blog · 06/08 08:00

Building intelligent apps for Apple platforms with Claude in the Foundation Models framework

中文介绍 介绍如何在苹果平台 Foundation Models 框架中利用 Claude 构建智能应用。

Jun 8, 2026SciencePaving the way for agents in biology

Anthropic Research · 06/08 08:00

Jun 8, 2026SciencePaving the way for agents in biology

中文介绍 Anthropic 发布新研究，探索 AI 智能体在生物学领域的应用。

The Open Source Community is backing OpenEnv for Agentic RL

Hugging Face Blog · 06/08 08:00

中文介绍 开源社区支持用于智能体强化学习的 OpenEnv 环境。

OpenAI govt stake 🇺🇸, Google compute deal 🚀, Microsoft Scout launch 🤖

TLDR AI · 06/08 08:00

中文介绍 当日 AI 要闻：OpenAI 政府持股、谷歌计算交易、微软推出 Scout。

[AINews] not much happened today

Latent Space · 06/06 12:34

a quiet day of RSI.

中文介绍 AI 新闻简报报道当日市场相对平静，RSI 指标较低。

How to Stop Shipping Low-Quality RL Environments (with Examples)

Latent Space · 06/06 02:49

Your broken harness is actively making the model worse. Here's what I keep seeing after years of eyeballing trajectories, and what you need to fix.

中文介绍 文章指出低质量强化学习环境会损害模型性能，并提供了改进建议。

The Meta hack shows there’s more to AI security than Mythos

MIT Tech Review AI · 06/05 17:00

On June 5, 404 Media reported that attackers had been using Meta’s AI customer support agent to steal Instagram accounts. Their approach was simple: They asked the agent to link the accounts to email addresses that they controlled, and the agent complied. One attacker broke into the dormant Obama Wh

中文介绍 2026年6月5日，攻击者利用 Meta 的 AI 客服助手窃取 Instagram 账户，暴露了 AI 安全漏洞。攻击方式简单：让 AI 将账户链接至攻击者控制的邮箱。

[AINews] not much happened today

Latent Space · 06/05 14:44

a quiet day

中文介绍 当日 AI 市场交易量清淡。

not much happened today

Smol AI News · 06/05 13:44

**Anthropic's Mythos/Opus cycle** sparked mixed reactions with praise for **Claude Mythos**'s one-shot workflows and concerns over **Opus 4.8** benchmark regressions. **Opus 4.7** showed strong chemistry task performance, "making Claude a chemist." **Sakana AI** launched an **RSI Lab** focusing on r

中文介绍 报道 Anthropic 的 Mythos/Opus 周期引发热议：Claude Mythos 的一次性工作流获好评，Opus 4.8 基准测试出现倒退，Opus 4.7 在化学任务上表现优异，Sakana AI 推出 RSI 技术。

How one Anthropic seller rebuilt his team's workflows with Claude Code

Claude Blog · 06/05 08:00

How one Anthropic seller rebuilt his team's workflows with Claude Code

中文介绍 Anthropic 一位销售人员分享如何用 Claude Code 重建团队工作流程。

The Claude Cowork product guide

Claude Blog · 06/05 08:00

The Claude Cowork product guide

中文介绍 Claude Cowork 产品使用指南。

一年一度，苹果 wwdc 大会讨论帖

06/08 20:46

39 回复 · Apple 节点

关于敏感数据脱敏的一个方案

06/08 20:35

6 回复 · 程序员 节点

单兵作战的后端，如何在这种全员乱改代码的奇葩环境下做好免责

06/08 20:16

15 回复 · 程序员 节点

Cloudflare 优选 IP，收到 CF 的 DNS 验证邮件，是我没弄对吗？

06/08 18:01

6 回复 · 程序员 节点

我做的 NVR 软件今天收到了老外的感谢工单，非常开心

06/08 16:14

21 回复 · 程序员 节点

我的 Apple AirPods 第一代，落下帷幕

06/08 11:55

17 回复 · Apple 节点

弄了个 intel 的 Macbook Air 拿来远程 vibe Coding

06/08 11:16

20 回复 · Apple 节点

今年 mac mini 会发新版本？ 想搞个 32G 的

06/08 09:38

11 回复 · Apple 节点

话说 iOS 无法收到 X 和 Telegram 这件事是不是已成定局了？

06/07 21:59

48 回复 · Apple 节点

各位有什么“优雅”的旧版 app 下载方式分享下

06/07 21:03

13 回复 · Apple 节点

OpenAI Submits S-1 Draft to SEC

06/09 05:22

73 points · 23 comments

FrontierCode

06/09 04:45

37 points · 9 comments

I'm building a parallel internet, and it's called The Thinnernet

06/09 03:45

32 points · 30 comments

Surveillance Is Not Safety: A statement on the UK's latest threat to privacy [pdf]

06/09 03:42

223 points · 41 comments

Apple reveals new AI architecture built around Google Gemini models

06/09 03:14

275 points · 231 comments

Why are cells small?

06/09 03:10

83 points · 37 comments

Switzerland wil have a referendum to cap population at 10M

06/09 03:09

176 points · 377 comments

Apple Core AI Framework

06/09 02:47

84 points · 4 comments

Ask HN: What are tools you have made for yourself since the advent of AI?

06/09 02:22

81 points · 119 comments

Siri AI

06/09 02:17

284 points · 214 comments

Apple WWDC 2026

06/09 01:14

220 points · 415 comments

Massachusetts bans sale of precise location data in new privacy rights bill

06/09 01:07

196 points · 31 comments

Stop the Apple Music app from launching

06/09 01:01

533 points · 211 comments

Show HN: Gitdot – a better GitHub. Open-source, anti-AI, and written in Rust

06/09 00:52

What works now: user signups, org creations, private/public repos, and importing GitHub repositories (both as read-only mirrors and full migrations). So basically, you can create, push and pull to a repo, but we don't have many features quite yet (issues, PRs, CI).What is a bit unique is:

EU-banned pesticides found in rice, tea and spices

06/08 23:59

172 points · 65 comments

AI is slowing down

06/08 23:46

296 points · 337 comments

MiMo-v2.5-Pro-UltraSpeed: 1T model with 1000 tokens per second

06/08 23:27

443 points · 300 comments

xAI is looking more like a datacentre REIT than a frontier lab

06/08 23:13

328 points · 245 comments

Show HN: Performative-UI – A react component library of design tropes

06/08 22:05

hope you enjoy

Launch HN: Intuned (YC S22) – Build and run reliable browser automations as code

06/08 21:35

Hey HN, we're Faisal and Ahmad from Intuned (https://intunedhq.com). We’re building a platform for building, deploying, and maintaining browser automations.Customers primarily use the Intuned AI agent to automate websites that don't expose APIs. Common use-cases include scraping

Anti-social: It's fads, not friends, which now dominate social media feeds

06/08 19:58

493 points · 372 comments

The Cypherpunk Library

06/08 16:32

343 points · 94 comments

How much of Thermo Fisher's antibody data has been manipulated?

06/08 14:56

379 points · 81 comments

1worldflag: A blue dot on a transparent background

06/08 09:37

148 points · 128 comments

Fooling Go's X.509 Certificate Verification

06/06 21:52

19 points · 9 comments

120k Lines of Rust: Inside the Nosdesk Backend

06/06 21:34

25 points · 1 comments

Show HN: Courtside – TUI for NBA Games

06/06 07:43

Hi HN, I made this after seeing a few similar projects on the front page. NBA API endpoints are public and there’s a pretty robust python package ( https://github.com/swar/nba_api ) that I referenced for the endpoint structure to build an sdk in go. used BubbleTea and LipGloss fo

Doing Something That's Never Been Done Before

06/05 22:30

5 points · 0 comments

OCaml Onboarding: Introduction to the Dune build system

06/05 01:52

134 points · 16 comments

Using XDG-Compliant Config Files (2024)

06/04 20:54

25 points · 2 comments