2026-06-08（内容获取于 06/08 17:22）

mvanhorn/last30days-skill

Python · ★ 32,560 · 🍴 2,687 · 📈 1,111 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 为AI智能体添加跨平台调研能力的技能模块，能自动抓取Reddit、X、YouTube、HN、Polymarket及网页上关于任意话题的最新内容，并生成有依据的摘要。适用于需要实时舆情分析、市场调研或内容聚合的场景。

opencv/opencv

C++ · ★ 88,282 · 🍴 56,608 · 📈 65 stars today

Open Source Computer Vision Library

中文介绍 开源计算机视觉库，提供数百种图像处理和机器学习算法，支持C++、Python、Java等语言。广泛应用于人脸识别、物体检测、图像分割、视频分析等场景，是计算机视觉领域的标准工具。

Leonxlnx/taste-skill

Shell · ★ 37,741 · 🍴 2,695 · 📈 1,103 stars today

Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop

中文介绍 赋予AI审美品味的技能，通过特定机制阻止模型生成乏味、套话式的内容。适用于写作辅助、创意生成、对话系统等需要高质量输出的场景，提升AI内容的新颖性和吸引力。

NousResearch/hermes-agent

Python · ★ 186,629 · 🍴 32,100 · 📈 1,112 stars today

The agent that grows with you

中文介绍 一个与用户共同成长的AI智能体，核心设计强调持续学习和适应。通过长期交互，逐步匹配用户偏好与需求，适用于个性化助手、长期陪伴或定制化任务执行的场景。

lfnovo/open-notebook

TypeScript · ★ 27,657 · 🍴 3,129 · 📈 554 stars today

An Open Source implementation of Notebook LM with more flexibility and features

中文介绍 Notebook LM的开源替代品，提供更灵活的功能扩展，支持多文档交互、知识整合与智能问答。适合研究人员、学生和知识工作者用于整理资料、生成摘要或构建个人知识库。

yikart/AiToEarn

TypeScript · ★ 19,181 · 🍴 2,949 · 📈 183 stars today

Let's use AI to Earn!

中文介绍 利用AI技术实现变现的项目，可能涉及自动化创作、数据标注、内容生成等方向。目标用户是希望借助AI工具获取收入的个人或小团队。

aaif-goose/goose

Rust · ★ 47,769 · 🍴 5,033 · 📈 322 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智能体，超越代码补全功能，支持安装、执行、编辑和测试任务，并可接入任意大语言模型。面向开发者，用于自动化工作流、环境管理和软件测试。

Crosstalk-Solutions/project-nomad

TypeScript · ★ 29,913 · 🍴 2,963 · 📈 309 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，集成关键工具、知识和AI功能，适应无网络环境。适用于野外探险、灾难应急或偏远地区工作，提供信息访问和决策支持。

ggml-org/llama.cpp

C++ · ★ 115,515 · 🍴 19,331 · 📈 158 stars today

LLM inference in C/C++

中文介绍 用C/C++实现的高性能LLM推理引擎，支持在CPU和混合架构上运行Llama等模型。适合本地部署、资源受限设备或需要低延迟推理的场景，是个人开发者和边缘计算的热门选择。

RyanCodrai/turbovec

Python · ★ 7,736 · 🍴 738 · 📈 1,554 stars today

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

中文介绍 基于TurboQuant技术的向量索引库，使用Rust编写并提供Python绑定。专注于高效向量检索与存储，适用于推荐系统、语义搜索或大模型知识库的近似最近邻搜索。

TapXWorld/ChinaTextbook

Roff · ★ 72,780 · 🍴 16,297 · 📈 350 stars today

所有小初高、大学PDF教材。

中文介绍 收集中国小学至大学全学科的PDF教材资源，涵盖各年级与版本。服务于学生、教师或自学者，方便电子化查阅和离线学习。

openai/plugins

JavaScript · ★ 2,157 · 🍴 277 · 📈 262 stars today

OpenAI Plugins

中文介绍 OpenAI官方插件集合，用于扩展ChatGPT等模型的功能，如联网搜索、代码执行等。开发者可通过插件将外部API和工具无缝集成到AI对话中。

refactoringhq/tolaria

TypeScript · ★ 13,130 · 🍴 924 · 📈 245 stars today

Desktop app to manage markdown knowledge bases

中文介绍 桌面端Markdown知识库管理应用，提供笔记组织、搜索和编辑功能。面向注重本地优先、纯文本格式的知识工作者或开发者，用于个人知识管理或写作。

HunxByts/GhostTrack

Python · ★ 13,886 · 🍴 1,850 · 📈 28 stars today

Useful tool to track location or mobile number

中文介绍 手机号或位置追踪工具，利用公开信息或技术手段获取定位。常用于安全测试或个人查找，需注意隐私与法律合规性。

microsoft/pg_durable

Rust · ★ 1,591 · 🍴 37 · 📈 316 stars today

PostgreSQL in-database durable execution

中文介绍 PostgreSQL的数据库内持久化执行引擎，允许用户定义的任务可靠执行并自动恢复。适用于需要事务性工作流、定时任务或数据管道处理的场景。

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

👍 22

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 AnchorWorld 提出一个框架，通过基于视角演化的定制，推进具身第一人称世界模拟，提升交互式世界建模的灵活性。

MMAE: A Massive Multitask Audio Editing Benchmark

👍 33

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 MMAE 是一个大规模多任务音频编辑基准，首个专为通用指令式音频编辑设计的综合评估平台。

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

👍 2

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 Stream3D-VLM 提出在线3D视觉语言模型，通过增量几何先验实现实时空间理解，不同于传统需要完整场景的离线方法。

Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings

👍 50

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视为文本嵌入的特征透镜，有助于提升其作为嵌入模型的零样本性能。

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 论文探讨多模态大语言模型在人类视角视频理解中的能力，处理长视频中的稀疏证据和长程依赖关系。

Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills

👍 1

06/05 08:00

LLM-driven software engineering agents have become a central testbed for real-world language-model capability, yet their training remains limited by the availability of high-quality SWE tasks. Existing synthetic data methods typically create tasks through fixed mutation or bug-injection procedures,

中文介绍 Socratic-SWE 提出自演化编码智能体，通过轨迹派生技能生成高质量软件工程任务，突破合成数据瓶颈。

dots.tts Technical Report

👍 10

06/05 08:00

We present dots.tts, a 2B-parameter continuous autoregressive text-to-speech (TTS) foundation model that models speech in a continuous latent space. Compared with existing continuous autoregressive models, our key innovations are threefold. First, we train an AudioVAE with multiple objectives to bui

中文介绍 dots.tts 发布20亿参数连续自回归文本转语音基础模型，在连续潜在空间中建模语音，创新点包括多粒 AudioVAE 训练。

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

👍 30

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

中文介绍 SoCRATES 提出跨领域与社会认知变化的主动式大模型调解自动评估方法，克服传统测试场依赖专家域的局限。

LLM Explainability with Counterfactual Chains and Causal Graphs

👍 8

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

中文介绍 论文使用因果图建模大语言模型自身推理过程，结合反事实链提供可解释性，帮助利益相关者理解机制。

Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators

👍 10

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

中文介绍 Thinking with Imagination 利用世界模拟器增强视觉语言模型的空间推理，使其能够推断未观察布局并保持跨视图一致性。

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

👍 15

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

中文介绍 SubtleMemory 基准测试长期AI智能体对细粒度关系记忆的辨别能力，应对记忆增长中的冲突与分化。

When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents

👍 14

06/04 08:00

Existing benchmarks evaluate Tool-Integrated Reasoning (TIR) in LLMs on idealized ''happy paths'', largely overlooking real-world tool failures. We introduce ToolMaze, a benchmark for dynamic path discovery and error recovery in TIR agents. To separate systematic replanning from blind trial-and-erro

中文介绍 ToolMaze 基准测试大语言模型在工具失败时的动态重规划和异常恢复能力，区别于仅评估理想路径的现有基准。

WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark

👍 0

06/04 08:00

In real-world applications, models are expected to perform reliably across diverse settings. Yet, many existing multimodal benchmarks expand task types without capturing the visual diversity needed to handle open-ended visual inputs. We present WorldBench, a challenging and visually diverse reasonin

OpenSkill: Open-World Self-Evolution for LLM Agents

👍 6

06/04 08:00

Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning loop, such as curated skills, successful trajectories, or verifier signals. Real open-world deployments may provide none of these, offering only a task prompt. In this work, we study open-worl

Regret Minimization with Adaptive Opponents in Repeated Games

👍 1

06/04 08:00

In this paper, we study regret minimization in repeated games with adaptive opponents who can respond based on histories of play. The standard metric of external regret in online learning is known to fail to capture such adaptivity. To account for players' counterfactual reasoning, we introduce {\tt

Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models

👍 3

06/04 08:00

Multimodal Large Language Models (MLLMs) excel at 2D semantic understanding but lack intrinsic 3D awareness, resulting in representations that fail to maintain geometric and spatial consistency across video frames. Given the scarcity of large-scale 3D data, we present GeoVR, a novel framework that l

AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding

👍 10

06/04 08:00

Vision-Language-Action (VLA) models leverage the rich world knowledge of pretrained vision-language models (VLMs) to enable instruction-following robotic manipulation. However, the structural mismatch between VLM semantic spaces and embodied control policies often hinders the learning of precise per

Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution

👍 73

06/04 08:00

Code language models need repository-level context to resolve imports, APIs, and project conventions. Existing methods inject this knowledge as long inputs (retrieved through RAG or dependency analysis) or through per-repository fine-tuning and LoRA -- costly at repository scale and brittle to evolv

AURA: Intent-Directed Probing for Implicit-Need Surfacing in Situated LLM Agents

👍 1

06/04 08:00

A situated query like "where is Lin Wei?" often encodes more than its literal content: the user may also want to know whether Lin Wei is free, in a good mood, or worth interrupting now. Standard tool-use agents answer the literal question and stop. AURA inserts an inference step between scene percep

Benchmark Everything Everywhere All at Once

👍 2

06/04 08:00

Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit measures of performance. However, their construction is labor-intensive and hard to reuse, raising concerns about sustainability and scalability. Moreover, existing benchmarks often quickly

MAOAM: Unified Object and Material Selection with Vision-Language Models

👍 9

06/02 08:00

Selection is a core operation in interactive image editing. To be practical, a user should be able to specify and disambiguate the desired selection region through either text or click-based interactions, and the system should support selecting not only objects but also other criteria, such as mater

HarnessForge: Joint Harness and Policy Evolution for Adaptive Agent Systems

👍 1

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

Parametric Social Identity Injection and Diversification in Public Opinion Simulation

👍 0

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

LLM Anonymization Against Agentic Re-Identification

👍 1

06/01 08:00

Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-identification, yet those same details also carry downstream analytic value of the text. Existing defenses either remove explicit identifiers, perturb text

SABER: Benchmarking Operational Safety of LLM Coding Agents in Stateful Project Workspaces

👍 0

05/31 08:00

Large language models are increasingly deployed as coding agents, shifting safety from individual responses to action sequences. Existing benchmarks, however, primarily assess whether models refuse unsafe prompts, leaving impacts on stateful workspaces largely unexamined. We present SABER, a benchma

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

The Shape of Addition: Geometric Structures of Arithmetic in Large Language Models

👍 4

05/29 08:00

Large Language Models exhibit paradoxical fragility in fundamental arithmetic, implying a disconnect between internal computation and discrete output. By analyzing the residual stream geometry during multi-operand addition, we identify the Iso-Raw-Sum Trajectory (IRST), a geometric structure where r

SIA: Self Improving AI with Harness & Weight Updates

👍 1

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

Trust Region Q Adjoint Matching

👍 3

05/26 08:00

Off-policy reinforcement learning of pretrained flow policies remains challenging due to the instability of optimization arising from the multi-step sampling process. Recently, Q-learning with Adjoint Matching (QAM) addressed this issue by reformulating into a memoryless stochastic optimal control (

When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges

👍 3

05/25 08:00

Customizing an LLM judge to a specific task or domain often involves optimizing its prompt across multiple evaluation criteria simultaneously. Textual gradient methods automate this for a single judge criterion, however they produce natural-language critiques, not numerical vectors. Thus, the confli

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 证明基于嵌入的 AI 智能体记忆系统存在根本缺陷：会遗忘存储内容，且会自信地捏造从未存储的信息。作者从拓扑学角度分析了这一问题的必然性。

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

中文介绍 2026 年成为 AI 工程师的路线图，无需 CS 学位或训练营。企业实际招聘的是能解决特定问题的选手，而不需要懂 Transformer 原理。

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

中文介绍 揭秘 Claude Code 的动态工作流：6 种模式、14 个步骤，由 Anthropic 工程师实践。指出 9 成开发者仍手动链式提示，未尝试动态工作流。

What an Enterprise Context Layer Actually Is

@prukalpa · 23.1K 粉丝 · 583.2K 阅 · 506 赞 · 80 转

06/02 02:17

A field guide to what it is, what it is not, and where it fits in your AI architecture. I have had some version of the same conversation with a CIO almost every day this year. Their team has read

中文介绍 企业上下文层（Enterprise Context Layer）的实战指南：它是什么、不是什么，以及在 AI 架构中的位置。作者与 CIO 多次讨论此话题。

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

中文介绍 Harness Engineering 是 2026 年 AI 工程师必备技能：举例 OpenAI 团队靠 AI 代理写出百万行代码，人类只负责设计系统。

hacking pewdiepie's AI agent harness using an evil cocomelon website (then helping protect it)

@theonejvo · 22.1K 粉丝 · 504.3K 阅 · 861 赞 · 1 转

06/02 02:01

Over the past year, @pewdiepie, has been turning into one of the most visible champions of private, self-hosted computing, and it has been a genuine pleasure to watch. What began in late 2025 as an

中文介绍 利用邪恶儿童网站 hack 了 PewDiePie 的 AI 代理系统，并协助加固防护。PewDiePie 是私有自托管计算的知名倡导者。

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,

中文介绍 2026 年的前端界面由代理实时生成，不再固定。设计师画、工程师建的旧模式结束，生成式 UI 成为新范式。

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

中文介绍 自动化 YouTube 频道达到 125k 订阅，零人工视频制作。作者将此策略用于成为首个全自动应用。

Stop building Foxconn factories for your agents

@garrytan · 853.3K 粉丝 · 180.6K 阅 · 503 赞 · 43 转

06/01 22:26

In January I got back into coding and I built Garry's List. Over five hundred thousand lines of Rails and the tests to police it. I was proud of it. I shouldn't have been. The thing worth being proud

中文介绍 作者亲手构建 50 万行 Rails 代码后反思应‘停止为代理搭建富士康工厂’。强调核心是让代理自主运行，而非重复造轮子。

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

中文介绍 构建云原生代理基础设施的经验：现有框架假定本地桌面环境（单机单用户），而云环境需要不同的架构设计。

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

中文介绍 Codex 的/goal 模式指南：设定目标后，Codex 会持续工作直至达成，无论耗时长短。适合驱动具体成果的场景。

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

中文介绍 调研 Cursor、Devin、Claude Code、Codex 等代理系统的内存管理现状。这些环境正越来越多地集成上下文与记忆功能。

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,

中文介绍 Claude Code 动态工作流发布：Claude 能自行编写即时工作任务定制的 harness。默认 harness 专注于编程，新特性扩展了适用场景。

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

中文介绍 提出世界模型的功能分类法。引用维特根斯坦开篇，强调空间智能是当前 AI 的缺口，并构建了系统性分类框架。

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

中文介绍 构建自定义代理 harness 的教程：核心是连接模型到正确上下文、数据与环境。代理本质是调用工具的模型。

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.

中文介绍 进入前沿 AI 实验室的笔记：关键在于‘已证实的科研能力’和‘战壕工程能力’，两者正融合为一。

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

06/07 04:10

中文介绍 Hermes Agent 发布新型超级应用，同时 DeepSeek v4 性能接近 Opus 4.8。

ChatGPT And Codex Are Merging (This Changes Everything)

06/04 06:17

中文介绍 ChatGPT 与 Codex 合并，将带来重大改变。

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

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

05/03 04:35

Amazing Digital Dentures (a failed project)

Hugging Face Blog · 06/08 03:44

中文介绍 Hugging Face博客发布了一个名为“Amazing Digital Dentures”的项目回顾，该项目最终以失败告终。

[AINews] not much happened today

Latent Space · 06/06 12:34

a quiet day of RSI.

中文介绍 据Latent Space的AINews报道，当天AI领域较为平静，仅有RSI相关动态。

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 Latent Space文章探讨如何避免发布低质量的强化学习环境，指出有问题的环境会损害模型性能，并提供改进建议。

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 MIT Tech Review报道，攻击者利用Meta的AI客服代理窃取Instagram账户，通过要求代理将账户链接到攻击者控制的邮箱，代理竟然执行了该操作。

[AINews] not much happened today

Latent Space · 06/05 14:44

a quiet day

中文介绍 Latent Space的AINews指出当天AI领域较为平静。

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 Smol AI News报道，Anthropic的Mythos/Opus周期引发热议，Claude Mythos在一站式工作流中获赞，但Opus 4.8基准性能出现倒退；Opus 4.7在化学任务中表现强劲，Sakana AI推出RSI。

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 Claude博客介绍Anthropic一位销售代表如何利用Claude Code重构团队工作流程。

The Claude Cowork product guide

Claude Blog · 06/05 08:00

The Claude Cowork product guide

中文介绍 Claude博客发布了Claude Cowork产品指南。

Jun 5, 2026ScienceMaking Claude a chemist

Anthropic Research · 06/05 08:00

Jun 5, 2026ScienceMaking Claude a chemist

中文介绍 Anthropic研究团队发布报告，展示如何让Claude具备化学家能力。

Anthropic Oceanus leaks 🤖, ChatGPT Dreaming 💭, recursive self improvement 🚀

TLDR AI · 06/05 08:00

中文介绍 TLDR AI日报报道：Anthropic的Oceanus模型泄露、ChatGPT的Dreaming功能、以及递归自我改进等话题。

Reality: The Final Eval — Lukas Petersson and Axel Backlund of Andon Labs

Latent Space · 06/05 04:39

We talk with the VendingBench authors on evaling Claudes from Haiku to Mythos, and how they build leading, and lasting, frontier evals from scratch.

中文介绍 Latent Space与Andon Labs的Lukas Petersson和Axel Backlund讨论VendingBench评估，涵盖从Haiku到Mythos的Claude模型评估及前沿评估构建方法。

Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI

Hugging Face Blog · 06/05 02:57

中文介绍 NVIDIA发布Nemotron 3.5内容安全模型，提供可定制的多模态安全功能，适用于全球企业AI部署。

EVA-Bench Data 2.0: 3 Domains, 121 Tools, 213 Scenarios

Hugging Face Blog · 06/04 20:24

中文介绍 ServiceNow AI发布EVA-Bench Data 2.0，涵盖3个领域、121个工具和213个场景，用于AI代理评估。

How Endava is redesigning software delivery around AI agents

OpenAI News · 06/04 20:00

Learn how Endava is using AI agents, ChatGPT Enterprise, and Codex to accelerate software delivery, automate workflows, and build an AI-native culture across the enterprise.

中文介绍 OpenAI报道，Endava利用AI代理、ChatGPT Enterprise和Codex加速软件交付、自动化工作流，并构建AI原生文化。

How courts are coping with a flood of AI-generated lawsuits

MIT Tech Review AI · 06/04 18:50

Most days in her chambers, Judge Maritza Braswell, a federal magistrate judge in Colorado, sifts through stacks of documents written by people without a lawyer. Many of them can’t afford to hire a lawyer, and others have cases too weak or too small to interest one. She reads each one carefully, mind

中文介绍 MIT Tech Review报道，联邦治安法官Maritza Braswell等人发现，法院正面临大量由AI生成的诉讼文件，这些文件多由无力请律师的当事人提交。

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

7 回复 · 程序员 节点

我觉得当下 AI 取代程序员最大的拦路虎就是模型能力的飘忽不定

06/08 15:53

11 回复 · 程序员 节点

在中国推广无密码还有哪些阻力？

06/08 12:56

38 回复 · 程序员 节点

我有一计，送给二线 AI 厂商

06/08 12:13

19 回复 · 程序员 节点

我的 Apple AirPods 第一代，落下帷幕

06/08 11:55

16 回复 · Apple 节点

弄了个 intel 的 Macbook Air 拿来远程 vibe Coding

06/08 11:16

14 回复 · Apple 节点

我用 GiffGaff 卡注册谷歌账号，卡在验证码发送那一步，每次都发送失败。

06/08 10:41

20 回复 · 程序员 节点

阿里百炼 coding plan 上新模型了 qwen3.7 plus

06/08 09:55

17 回复 · 程序员 节点

今年 mac mini 会发新版本？ 想搞个 32G 的

06/08 09:38

7 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

38 回复 · Apple 节点

The Cypherpunk Library

06/08 16:32

22 points · 3 comments

OneDrive data now has an expiry date

06/08 16:11

9 points · 3 comments

Do agents.md files help coding agents?

06/08 13:21

https://xcancel.com/rasbt/status/2063649136323252397https://arxiv.org/abs/2602.11988

Richard Scolyer Has Died

06/08 12:10

50 points · 12 comments

1k Data Breaches Later, the Disclosure Lag Is Worse

06/08 11:17

139 points · 52 comments

Dopamine Fracking

06/08 10:42

283 points · 106 comments

Texas grid flags risks as data centers, crypto sites fail voltage tests

06/08 10:05

101 points · 73 comments

Algorithmic Monocultures in Hiring

06/08 09:54

90 points · 33 comments

New drug 'functionally cures' many hepatitis B virus infections

06/08 09:41

167 points · 25 comments

DeepSeek V4 Pro beats GPT-5.5 Pro on precision

06/08 09:39

255 points · 107 comments

1worldflag: A blue dot on a transparent background

06/08 09:37

114 points · 95 comments

APC–2 – A professional record cutter for producing original playback discs

06/08 09:27

202 points · 98 comments

The Smallest Brain You Can Build: A Perceptron in Python

06/08 08:28

189 points · 27 comments

A Matter Wi-Fi Light Bulb in Rust on the Raspberry Pi Pico 2 W

06/08 08:17

111 points · 13 comments

How's Linear so fast? A technical breakdown

06/08 03:01

404 points · 185 comments

Building from zero after addiction, prison, and a felony

06/08 02:33

626 points · 274 comments

Making peace with your unlived dreams (2023)

06/08 02:15

224 points · 127 comments

LLMs are eroding my software engineering career and I don't know what to do

06/07 20:49

958 points · 919 comments

Show HN: Lathe – Use LLMs to learn a new domain, not skip past it

06/07 19:16

Hey HN!Lathe is an experiment in using LLMs to teach me something new, instead of doing the work for me. It generates a hands-on, source-backed tutorial for any technical topic you want to learn. Then you work through it yourself by reading and typing the code by hand (gasp) in a local UI built for

The 29th International Obfuscated C Code Contest (IOCCC) 2025 Winners

06/07 13:47

392 points · 89 comments

Trusted Computing Frequently Asked Questions (2003)

06/07 12:45

11 points · 0 comments

Giant Floating Victorian Drydock

06/06 22:22

12 points · 4 comments

Tiny hackable CUDA language model implementation

06/06 01:41

26 points · 2 comments

Playing with Vision Embeddings

06/05 22:54

43 points · 4 comments

What is the purpose of the lost+found folder in Linux and Unix? (2014)

06/05 16:08

188 points · 67 comments

Show HN: I Derived a Pancake

06/05 14:42

After 25 years of making other people's pancake recipes - always yearning for more tang, more fluff, and more predictability - I decided to derive the pancake recipe from the chemistry.You mark checkboxes for what you have on hand (ricotta, sour cream, kefir, buttermilk, yogurt, cottage cheese,

Man-Computer Symbiosis J. C. R. Licklider (1960)

06/05 07:07

35 points · 3 comments

A discovery about GCC's unidirectional rotation algorithm

06/04 13:59

20 points · 9 comments

Spherical Voronoi Diagram

06/03 23:32

5 points · 0 comments

Do we fear the serializable isolation level more than we fear subtle bugs (2024)

06/03 22:21

79 points · 45 comments