2026-06-25（内容获取于 06/25 15:08）

calesthio/OpenMontage

Python · ★ 20,430 · 🍴 2,298 · 📈 3,719 stars today

World's first open-source, agentic video production system. 12 pipelines, 52 tools, 500+ agent skills. Turn your AI coding assistant into a full video production studio.

中文介绍 OpenMontage是首个开源的代理式视频制作系统，通过12条生产线、52种工具和500多个AI代理技能，将AI编码助手转化为完整的视频制作工作室。它旨在自动化视频内容生成，解决传统视频制作的复杂性和耗时性问题。内容创作者和开发者可利用该系统，通过AI驱动高效产出各类视频，极大提升工作流效率。

ZhuLinsen/daily_stock_analysis

Python · ★ 48,995 · 🍴 43,167 · 📈 1,468 stars today

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.

中文介绍 ZhuLinsen/daily_stock_analysis是一个由LLM驱动的多市场股票智能分析系统。它整合多源行情数据、实时新闻，提供直观的决策看板，并支持自动推送关键信息，旨在为投资者和分析师提供便捷、智能的股票市场洞察。该系统特色在于支持零成本定时运行，有效解决了传统市场分析耗时耗力的问题，助力用户高效把握市场动态、辅助投资决策。

apple/container

Swift · ★ 42,601 · 🍴 1,252 · 📈 1,838 stars today

A tool for creating and running Linux containers using lightweight virtual machines on a Mac. It is written in Swift, and optimized for Apple silicon.

中文介绍 Apple/container是一个专为Mac用户设计的工具，它能通过轻量级虚拟机创建并运行Linux容器。该项目采用Swift语言开发，并针对Apple silicon进行了优化，旨在提供高效、原生的容器化体验。它解决了在macOS上运行Linux容器的性能和兼容性挑战，使得开发者能够更便捷地在Mac设备上进行跨平台开发、测试和部署，尤其适合需要高性能容器环境的专业人士。

interviewstreet/hiring-agent

Python · ★ 2,459 · 🍴 620 · 📈 203 stars today

AI agent to evaluate and score resumes.

中文介绍 Interviewstreet/hiring-agent是一个利用AI代理技术，自动化评估和评分候选人简历的项目。它旨在解决招聘流程中简历筛选耗时耗力的问题，通过智能分析简历内容，提供客观的评分，从而帮助招聘人员和HR团队快速识别最符合职位要求的候选人。该工具能够显著提高招聘效率，减少人工筛选的偏差，使企业能够更有效地进行人才招募。

JCodesMore/ai-website-cloner-template

TypeScript · ★ 19,646 · 🍴 2,912 · 📈 692 stars today

Clone any website with one command using AI coding agents

中文介绍 JCodesMore/ai-website-cloner-template是一个利用AI编码代理实现网站克隆的工具。它允许用户通过一条命令，快速复制任何网站的结构和样式，旨在简化网页设计和前端开发流程。该项目解决了从零开始构建网站的耗时问题，为开发者、设计师和产品经理提供了快速获取网站模板、分析设计模式或进行原型开发的便利，极大提升了工作效率。

revfactory/harness

HTML · ★ 7,849 · 🍴 1,066 · 📈 277 stars today

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

中文介绍 Revfactory/harness是一个“元技能”项目，专注于AI代理系统的设计与构建。它能够设计领域特定的代理团队，定义专业的AI代理，并自动生成这些代理所需的技能。该项目旨在简化复杂AI代理应用的开发流程，解决从头构建多代理协作系统的高门槛问题。AI系统开发者和研究员可利用Harness，高效地定制和部署高性能的AI代理解决方案，加速智能应用的创新与落地。

flutter/flutter

Dart · ★ 177,486 · 🍴 30,554 · 📈 73 stars today

Flutter makes it easy and fast to build beautiful apps for mobile and beyond

中文介绍 Flutter是一个由Google开发的开源UI工具包，旨在帮助开发者快速、轻松地为移动、Web、桌面等多个平台构建美观的原生编译应用。它通过一套代码库解决跨平台开发中的兼容性和效率问题，提供了丰富的预构建组件和响应式框架，显著缩短了开发周期并降低了维护成本。移动开发者和企业团队可利用Flutter高效交付高性能、高保真的多平台应用。

andreknieriem/headunit-revived

Kotlin · ★ 1,479 · 🍴 115 · 📈 41 stars today

Headunit App for displaying Android Auto

中文介绍 Andreknieriem/headunit-revived是一个专为显示Android Auto界面而设计的Headunit应用程序。它解决了部分车载信息娱乐系统或自定义设备无法原生支持Android Auto的问题，使用户能够在非官方兼容的硬件上体验Google的智能车载系统。汽车爱好者和改装车主可利用此应用，将旧款车辆或特定平板设备变身为Android Auto显示屏，极大提升驾驶的智能互联体验。

stablyai/orca

TypeScript · ★ 7,027 · 🍴 506 · 📈 331 stars today

Orca is the ADE for working with a fleet of parallel agents. Run any coding agent with your own subscription. Available on desktop and mobile.

中文介绍 Stablyai/orca是一个Agent开发环境（ADE），专注于管理并运行并行AI代理组成的“舰队”。它解决了多AI代理系统在开发、部署和扩展中的复杂性问题，允许用户通过自己的订阅运行任何编码代理。Orca在桌面和移动端均可用，为开发者和企业提供了一个统一、高效的平台，用于构建、测试和部署复杂的AI代理解决方案，加速智能应用的落地。

google-labs-code/design.md

TypeScript · ★ 17,693 · 🍴 1,580 · 📈 619 stars today

A format specification for describing a visual identity to coding agents. DESIGN.md gives agents a persistent, structured understanding of a design system.

中文介绍 Google-labs-code/design.md是一个创新性的格式规范，旨在为AI编码代理提供一种描述视觉标识的方法。通过使用DESIGN.md，编码代理能够持久且结构化地理解一个设计系统，解决了AI在理解和实现设计意图时的挑战。这使得设计师和开发者能以标准化方式，将设计语言精确传达给AI，从而自动化和优化从设计到代码的转换流程，加速UI/UX开发效率。

Flowseal/zapret-discord-youtube

Batchfile · ★ 30,054 · 🍴 2,344 · 📈 61 stars today

中文介绍 Flowseal/zapret-discord-youtube项目名称暗示其与Discord和YouTube平台的内容访问或管理有关，特别是涉及"zapret"（俄语，意为禁止或审查）的场景。尽管没有详细描述，它可能旨在解决用户在特定区域访问Discord或YouTube内容时遇到的限制问题，或提供相关的规避、管理工具。目标用户可能是需要应对内容审查或希望自由访问社交媒体和视频平台的用户群体。

kunchenguid/no-mistakes

Go · ★ 2,490 · 🍴 159 · 📈 110 stars today

git push no-mistakes

中文介绍 Kunchenguid/no-mistakes是一个旨在通过`git push no-mistakes`命令，帮助开发者避免在代码提交过程中犯错的项目。它可能通过集成Git hooks或预提交检查等机制，在代码推送前执行一系列验证，如代码规范、单元测试通过、敏感信息检查等。该工具解决了团队协作中因代码质量问题或疏忽而导致的潜在风险，确保了代码库的整洁和稳定性，提升了整体开发效率。

NousResearch/hermes-agent

Python · ★ 202,387 · 🍴 36,166 · 📈 1,178 stars today

The agent that grows with you

中文介绍 NousResearch/hermes-agent是一个名为Hermes的AI代理项目，其核心理念是“与你共同成长”。它旨在解决传统AI代理缺乏长期学习和个性化适应能力的问题，通过某种机制使其能够根据用户的交互和反馈不断进化，更好地理解和满足个性化需求。该项目为开发者和研究员提供了一个探索可学习、自适应AI代理的框架，也为寻求长期智能助力的个人用户提供了可能性。

ShutterMuse: Capture-Time Photography Guidance with MLLMs

👍 9

06/24 08:00

Real-world photography requires capture-time guidance for both camera framing and subject pose. Yet existing aesthetic cropping benchmarks mainly evaluate post-hoc crop prediction and overlook subject-side recommendations, leaving the capture-time guidance capabilities of multimodal large language m

V-Zero: Answer-Label-Free On-Policy Distillation with Contrastive Evidence Gating for Fine-Grained Visual Reasoning

👍 7

06/24 08:00

Fine-grained visual reasoning requires multimodal large language models (MLLMs) to identify task-relevant visual evidence and ground their reasoning in local image regions. Existing agentic methods typically rely on reinforcement learning with verifiable rewards or supervised fine-tuning on large-sc

TryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy

👍 5

06/24 08:00

While Video Virtual Try-on (VVT) has achieved remarkable progress in synthesizing realistic garment overlays on dynamic subjects, existing paradigms remains fundamentally constrained by a passive dependency on source camera trajectories, failing to accommodate the requisite interactive freedom for o

Autodata: An agentic data scientist to create high quality synthetic data

👍 5

06/24 08:00

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data. We show how to train (meta-optimize) such a data scientist agent, so that it learns to create even stronger data. We describe the overall formulation, and a s

CAVEWOMAN: How Large Language Models Behave Under Linguistic Input and Output Compression

👍 2

06/23 08:00

"Talk short. Drop grammar. Save token." This caveman style is widely promoted as a way to cut inference cost, but whether it actually saves anything depends on which channel (the user's prompt or the model's response) is being compressed. We present Cavewoman, a two-channel evaluation protocol that

Are We Ready For An Agent-Native Memory System?

👍 42

06/23 08:00

Memory for large language model (LLM) agents has rapidly evolved from simple retrieval-augmented mechanisms into a data management system that supports persistent information storage, retrieval, update, consolidation, and dynamic lifecycle governance throughout agent execution. Despite this evolutio

RoPE-Aware Bit Allocation for KV-Cache Quantization

👍 2

06/23 08:00

Existing low-bit KV-cache quantizers often treat each cached key as a flat vector. Under RoPE, however, a key's contribution to a future attention logit decomposes into a position-dependent sum over two-dimensional frequency blocks. This makes key-cache quantization a block-wise bit-allocation probl

IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation

👍 11

06/23 08:00

Unified multi-modal large language models (MLLMs) have achieved strong text-to-image generation quality, but still struggle with structure-aware prompt following, where object counts, spatial relations, attribute bindings, and coarse layouts must be preserved. We attribute this limitation in part to

Advancing WordArt-Oriented Scene Text Recognition: Datasets and Methods

👍 4

06/23 08:00

WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially more challenging than general Scene Text Recognition (STR). Existing STR datasets and methods, typically built around regular scene text and fixed-tem

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

👍 25

06/23 08:00

We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction. Wan-Streamer seamlessly models language, audio, and video as both input and output within a single Transformer, where the

MEMPROBE: Probing Long-Term Agent Memory via Hidden User-State Recovery

👍 1

06/23 08:00

Long-term memory promises LLM agents that grow more capable across sessions, maintaining an accurate, evolving understanding of the user that interaction forms. In practice, however, this memory is evaluated mostly through downstream behavior, such as later answers, personalization quality, or task

AGORA: An Archive-Grounded Benchmark for Agentic Workplace Document Reasoning

👍 0

06/23 08:00

Large language models are increasingly deployed as agents that reason over documents rather than answer from parametric knowledge. We study archive-grounded reasoning: locating sparse evidence across a large, messy collection of workplace files, reconciling inconsistent terminology, units, and time

FLAT: Feedforward Latent Triangle Splatting for Geometrically Accurate Scene Generation

👍 14

06/23 08:00

Generating explorable 3D scenes from a single image requires strong generative priors and accurate geometric representations suitable for downstream use. Current video diffusion models offer high-quality generation and implicitly encode multi-view geometric structure in latent space. However, existi

Escaping the Self-Confirmation Trap: An Execute-Distill-Verify Paradigm for Agentic Experience Learning

👍 8

06/23 08:00

Experience-driven self-evolution is critical for large language model (LLM) agents to improve through open-world interaction. However, existing experience learning methods mostly rely on single-agent loops, where the same agent executes tasks, summarizes outcomes, and determines memory content. This

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems

👍 6

06/22 08:00

The Hitchhiker's Guide to Agentic AI is a comprehensive practitioner's reference for building autonomous AI systems. The book covers the full stack from first principles to production deployment, organized around a central thesis: building great agentic systems requires understanding every layer of

VeriEvol: Scaling Multimodal Mathematical Reasoning via Verifiable Evol-Instruct

👍 4

06/22 08:00

Scaling reinforcement learning for visual mathematical reasoning requires more than generating harder questions: as data volume grows, the reward labels themselves must remain reliable. Yet existing data pipelines scale supervision while trusting the labeller, and policy-side methods assume the unde

Critique of Agent Model

👍 15

06/22 08:00

What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and other ``agentic" tools that promise to drive up productivity, and at the same time, ``existential" concerns such as AI escaping human control with d

Semantic Browsing: Controllable Diversity for Image Generation

👍 14

06/22 08:00

Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adherence comes at the cost of diversity: generated samples tend to collapse into a single visual interpretation. Existing methods to improve diversity produce outputs driven by incidental variations rath

ChartWalker: Benchmarking the Cross-Chart RAG Task

👍 2

06/22 08:00

Cross-Chart Retrieval-Augmented Generation (RAG) is critical for complex multi-modal analytical tasks in scientific, business, and political domains. However, existing benchmarks either focus on tables, which are well-structured and textualized, or generate cross-chart questions by simply extracting

AOHP: An Open-Source OS-Level Agent Harness for Personalized, Efficient and Secure Interaction

👍 26

06/22 08:00

AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data sources. Most existing end-user operating systems, however, are designed for application-centric workflows and offer litt

Look Light, Think Heavy: What Multimodal Chain-of-Thought Reasoning Can and Cannot Do

👍 5

06/21 08:00

Chain-of-Thought (CoT) has become a standard method for improving reasoning capabilities in large language models (LLMs) by eliciting step-by-step thinking, but its effectiveness in multimodal tasks remains unclear. In this paper, we aim to systematically investigate the key question: What can multi

Multi4D: High-Fidelity Dynamic Gaussian Splatting via Multi-Level Competitive Allocation

👍 0

06/20 08:00

Dynamic 3D Gaussian splatting faces a fundamental tension between motion consistency and visual fidelity. Deformation-based approaches preserve temporal correspondence but suffer from motion over-factorization, oversmoothing high-frequency dynamics. In contrast, 4D-primitive methods capture fine vis

UnityShots: Memory-Driven Multi-Shot Audio-Video Generation with Boundary-Aware Gating

👍 3

06/19 08:00

Generating a coherent multi-shot video requires structured cross-shot memory. Subject appearance, scene context, and speaker identity must persist across cuts. Existing approaches either train end-to-end over fixed-length sequences and cannot scale, generate shot-by-shot with memory banks that grow

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents

👍 2

06/18 08:00

As LLM agents increasingly select tools autonomously, their choices among tools with different privileges become safety-relevant. However, prior tool-selection studies focus on safety-agnostic metadata preferences, leaving privilege-sensitive choices underexplored. To address this gap, we study over

QG-MIL: A Gated Transformer Aggregator for Domain-Agnostic Multiple Instance Learning in Medical Imaging

👍 2

06/18 08:00

Attention-based Multiple Instance Learning aggregators in medical imaging are prone to attention concentration, producing overconfident and unstable predictions. We introduce QG-MIL, a gated transformer aggregator that addresses this through four synergistic architectural components: RMSNorm-based p

EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies

👍 2

06/18 08:00

Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-relevant cues become occluded or unobservable over time. While existing memory-augmented methods utilize historical context, they either suffer from seve

Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence

👍 21

06/16 08:00

While Large Language Models (LLMs) have substantially advanced text-to-code synthesis, many real programming tasks specify intent through visual artifacts such as screenshots, charts, vector drawings, videos, and interactive states. These tasks require models to connect visual perception to executab

RL-Index: Reinforcement Learning for Retrieval Index Reasoning

👍 1

06/15 08:00

Retrieving external knowledge is essential for solving real-world tasks, yet it remains challenging when the relationship between a query and its relevant knowledge involves implicit and complex reasoning beyond surface-level semantic or lexical matching (e.g., mathematical problems relying on the s

LingxiDiagBench: A Multi-Agent Framework for Benchmarking LLMs in Chinese Psychiatric Consultation and Diagnosis

👍 21

06/11 08:00

Mental disorders are highly prevalent worldwide, but the shortage of psychiatrists and the inherent subjectivity of interview-based diagnosis create substantial barriers to timely and consistent mental-health assessment. Progress in AI-assisted psychiatric diagnosis is constrained by the absence of

An Efficient Method for the Optimal Control of Microgrids Under Uncertainties using Local Reduction

👍 0

06/10 08:00

The problem of optimal sizing and power scheduling in microgrids subject to uncertainties is well known to the control community. Commonly, the optimal control problem is cast as a mixed-integer program to model the logical constraints arising in energy storage systems, and is then solved approximat

Figma Motion

06/25 13:23

Your Figma canvas now has a timeline

Paybond CLI

06/25 09:23

Safe agent spend from the terminal

Converge

06/25 05:40

Group Scheduling Simplified

Blop

06/25 02:41

Describe your app and Blop tests it and repairs broken tests

Papermark Agents

06/24 22:35

Let AI agents run your next deal, fundraise or data room

Sidegent

06/24 22:34

Learn to build AI agents by actually building them

Genspark Design

06/24 22:18

Generate UI prototypes, videos, and posters with AI

Zaro

06/24 21:54

Build agents & apps on top of your context with one prompt.

MeetPoint

06/24 21:38

Find the city where everyone's flights are cheapest

Heron

06/24 17:01

Wireshark for AI Agents: passive eBPF observability

How Quants Use Loop Engineering to Build Alpha (Full Framework)

@horizon_trade_x · 4.4K 粉丝 · 1.3M 阅 · 507 赞 · 59 转

06/18 23:58

Your backtest looked flawless. You went live. Two weeks later, the strategy was bleeding. Every quant has lived this. The answer is a loop: generate a strategy, test it, score it, feed the result

Loops explained: Claude, GPT, Mira and what actually works

@AnatoliKopadze · 83.0K 粉丝 · 1.3M 阅 · 584 赞 · 70 转

06/20 21:40

AI has been in everyone's hands for years. Most people who use it every day still use it the slowest way there is: type a request, wait, fix it, ask again, all by hand. Not because the faster way is

How to Build an AI Second Brain With Claude and Obsidian That Gets Smarter Every Day (Full Guide)

@undefinedKi · 3.9K 粉丝 · 1.0M 阅 · 601 赞 · 78 转

06/20 20:15

Your best ideas are scattered across a dozen places right now. Notes apps. Browser tabs. Old chats with Claude that you closed and will never find again. Every time you sit down to work, you rebuild

40 Claude Opus 4.8 Workflows That Make Money While You Sleep

@eng_khairallah1 · 69.3K 粉丝 · 678.7K 阅 · 506 赞 · 81 转

06/21 17:00

Most people are using Claude Opus 4.8 to answer questions. Save this :) A small group of people have it running businesses while they sleep. The difference is not the model. You both have access to

The efficiency gap: How do cells and GPUs compare when running the exact same algorithm?

@spandan_madan · 1.1K 粉丝 · 626.9K 阅 · 516 赞 · 28 转

06/24 02:13

AI hardware is having a moment. Hyperscaler capex on AI data centres is on track to clear $690 billion in 2026, and private equity has followed in scale — Blackstone alone reports a $55B+ data-centre

How To Learn Anything 10x Faster Using Claude

@sairahul1 · 120.1K 粉丝 · 581.3K 阅 · 516 赞 · 110 转

06/20 16:30

Learning anything today is easy and confusing at the same time. Easy because AI can explain almost anything in seconds. Confusing because most people just ask random questions, get random answers, and

The Agent Loop Architecture

@djfarrelly · 3.8K 粉丝 · 344.7K 阅 · 501 赞 · 61 转

06/19 02:33

Everyone's asking "WTF is a loop?" Here's the question nobody's asking: what runs the loop? The AI discourse has converged on loops as a core primitive of agentic systems. Matt Van Horn (@mvanhorn)

Introducing Engram: Scaling compute on your context

@EngramLab · 1.2K 粉丝 · 255.7K 阅 · 537 赞 · 76 转

06/24 01:01

We’re Engram. We’re building AI that learns from you and deeply understands your work. Today’s AI models don’t understand what you do. Not really. Everything models know comes from their training –

30 Core Agentic Engineering Concepts Every Developer Should Know

@sairahul1 · 120.1K 粉丝 · 249.0K 阅 · 502 赞 · 90 转

06/23 17:28

There are 8 billion people on the planet. Only a fraction of developers understand how AI agents actually work. Not the demos. Not the hype. The real engineering underneath. Every week a new agent

ORACLE: Official AI Agents Trade on Polymarket

@Oracle_Trade_ai · 39.9K 粉丝 · 197.8K 阅 · 2.8K 赞 · 580 转

06/22 16:52

In 2026, autonomous AI agents have become one of the most effective strategies on prediction markets. Over 30% of all activity on Polymarket now comes from algorithmic and AI-powered wallets. We

Why we're bullish on loops

@posthog · 21.8K 粉丝 · 162.4K 阅 · 512 赞 · 36 转

06/24 01:26

When the creators of both OpenClaw and Claude Code speak, people listen. And recently Peter Steinberger and Boris Cherny have both been talking about the same concept: loops. Their argument? You

ORACLE: Official AI Agents Trade on Polymarket

@OracAItrading · 31.8K 粉丝 · 141.6K 阅 · 2.8K 赞 · 576 转

06/22 16:52

In 2026, autonomous AI agents have become one of the most effective strategies on prediction markets. Over 30% of all activity on Polymarket now comes from algorithmic and AI-powered wallets. We

Interactions API: Our primary interface for Gemini models and agents

@GoogleAIStudio · 179.4K 粉丝 · 138.2K 阅 · 504 赞 · 42 转

06/23 01:21

Today we're announcing that the Interactions API has reached general availability and is now our primary API for interacting with Gemini models and agents. We launched its public beta in December

ORACLE: Official AI Agents Trade on Polymarket

@Oractrading · 33.9K 粉丝 · 109.2K 阅 · 2.8K 赞 · 585 转

06/22 16:20

In 2026, autonomous AI agents have become one of the most effective strategies on prediction markets. Over 30% of all activity on Polymarket now comes from algorithmic and AI-powered wallets. We

How To Use Loop Engineering To Build A Self-Improving Quant Trading System

@RohOnChain · 51.4K 粉丝 · 108.3K 阅 · 501 赞 · 65 转

06/22 21:54

I will break down exactly how to build the loops that run an entire quant trading system on their own. Let's get straight to it. Bookmark This - I'm Roan, a backend developer working on system

how to get Fable-level intelligence back:

@EXM7777 · 118.9K 粉丝 · 107.7K 阅 · 509 赞 · 44 转

06/18 23:10

for a few days, we had something that felt like AGI... Fable 5 showed up, effectively unlimited inside the plans, and the ceiling on what you could build lifted overnight but then Anthropic killed it,

WTF Is a Loop? Part 2: The 15 Loops People Are Actually Running (and the Commands to Steal Them)

@mvanhorn · 35.2K 粉丝 · 102.4K 阅 · 510 赞 · 56 转

06/21 04:09

Earlier this month I wrote WTF Is a Loop? Peter Steinberger vs. Boris Cherny, which did 3.6M views on what a loop even is. This is the sequel, and it answers the next question: which loops do people

From Prompting Agents to Loop Engineering

@omarsar0 · 308.0K 粉丝 · 90.2K 阅 · 504 赞 · 69 转

06/20 00:31

A claim has been circulating in AI coding circles: stop prompting your coding agents and start designing loops that prompt them for you. As with everything new, this stuff gets repeated often and

How GLM-5.2 Beat Fable 5 at Website Design

@Designarena · 13.9K 粉丝 · 80.4K 阅 · 518 赞 · 39 转

06/20 01:58

GLM 5.2 ranks 1st overall on Design Arena’s single-turn, HTML Web Design (Non-Agentic) evaluation, 5 places higher than its predecessor GLM-5.1. To do so, it beat Claude Fable 5, Opus 4.6, and Opus

Subnets mine TAO; TAO mines Subnets

@const_reborn · 29.7K 粉丝 · 79.8K 阅 · 503 赞 · 116 转

06/23 09:21

e_i \;\propto\; \underbrace{\rho_i \times \bar{p}_i}_{\text{linear (maximize)}} \times \underbrace{(1 - b_i)}_{\text{boolean gate}} Disclaimer: this upgrade only effects subnet owners and dynamic TAO

Poweful Agents inside Slack

06/25 06:39

AI Agents Just Changed Forever: GLM 5.2, Codex Skills, Claude & Cursor

06/21 21:30

9 AI Agent Skills To Get Ahead of 99% of People

06/18 10:27

How to build high quality internal tools with Retool

06/18 05:21

SpaceX Just Bought Cursor for $60B. It’s About to Take OVER.

06/17 05:31

Why the Government Just Killed Claude Fable 5

06/13 11:50

This is Why They Banned Claude Fable 5

06/13 02:28

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

06/07 04:10

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

[AINews] It's Meta-Harness Summer

Latent Space · 06/25 10:14

Move over, Harness Engineering, it is time for the harness of harnesses!

中文介绍 文章指出，AI领域正迎来「元连接器（Meta-Harness）」的时代，这意味着AI系统集成和管理框架将进入更高级阶段，超越了传统连接器工程的范畴，致力于构建更强大的AI能力。

Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks

Latent Space · 06/25 02:53

In a rare double-interview, the Databricks technical leaders riff on what it will take for every company to build Agent Clouds

中文介绍 Databricks技术领导者Matei Zaharia和Reynold Xin在采访中强调，为了让企业能够构建「智能体云（Agent Clouds）」，前沿AI生态系统必须保持开放性。

Introducing computer use in Gemini 3.5 Flash

DeepMind Blog · 06/25 00:30

中文介绍 Google DeepMind在其博客中宣布，已为Gemini 3.5 Flash模型引入了「计算机使用」功能，进一步增强了该模型与外部计算环境交互和执行任务的能力。

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

Hugging Face Blog · 06/25 00:00

中文介绍 Hugging Face博客介绍了如何利用NVIDIA NeMo AutoModel技术，显著加速Transformer模型的微调过程，从而提升开发效率和模型性能。

The emergence of the web data infrastructure layer for AI

MIT Tech Review AI · 06/24 19:59

AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstructured, which limits its use by AI models. To understand this challenge, consider the foundation of

中文介绍 麻省理工科技评论指出，随着AI蓬勃发展，企业需要大规模数据支持，但现有网络数据常受阻或非结构化。文章探讨了为解决此挑战而出现的「AI网络数据基础设施层」的重要性。

[AINews] Claude Tag: Multiplayer, Proactive, Persistent Agents in Slack

Latent Space · 06/24 15:14

Claude finally gets a Slackbot upgrade

中文介绍 Claude的Slackbot获得重大升级，引入了「Claude Tag」功能，使其智能体现在支持多玩家协作、主动式交互和持久化操作，进一步提升了其在团队沟通工具Slack中的应用能力。

OpenAI and Broadcom unveil LLM-optimized inference chip

OpenAI News · 06/24 14:00

OpenAI and Broadcom introduce Jalapeño, a custom AI chip built for LLM inference to improve performance, efficiency, and scale across AI systems.

中文介绍 OpenAI和博通（Broadcom）联合发布了一款名为「Jalapeño」的定制AI芯片。该芯片专为大型语言模型（LLM）推理设计，旨在显著提升AI系统的性能、效率和规模。

not much happened today

Smol AI News · 06/24 13:44

**OpenAI** announced **Jalapeño**, its first custom AI chip for LLM inference, built with **Broadcom**, aiming to control more of the AI stack and improve compute economics with a fast 9-month design cycle. Community analysis suggests Jalapeño features **216GB HBM3E**, **~7.1–7.4 TB/s bandwidth**, a

中文介绍 OpenAI与博通合作发布了其首款定制AI芯片「Jalapeño」，专为大型语言模型（LLM）推理设计。该芯片旨在提升AI计算经济性，并能在9个月内完成设计，社区分析显示其配备216GB HBM3E内存。

Agent identity in Claude Tag: a new access model for autonomous, team-wide AI

Claude Blog · 06/24 08:00

Agent identity in Claude Tag: a new access model for autonomous, team-wide AI

中文介绍 Claude官方博客宣布，在其「Claude Tag」功能中引入了全新的「智能体身份」访问模型。该模型旨在为团队提供更自主、更安全、更便捷的AI访问和协作方式，进一步推动AI在团队工作中的应用。

Building effective human-agent teams

Claude Blog · 06/24 08:00

Building effective human-agent teams

中文介绍 Claude官方博客发布文章，探讨了如何构建高效的「人类-智能体团队」。文章深入分析了人类与AI智能体之间协作的最佳实践，旨在最大化团队生产力并优化工作流程。

Introducing the FFASR Leaderboard: Benchmarking ASR in the Real World

Hugging Face Blog · 06/24 08:00

中文介绍 Hugging Face博客宣布推出了「FFASR 排行榜」，旨在为真实世界场景下的自动语音识别（ASR）模型提供全面的基准测试和性能评估，促进ASR技术的发展。

Claude Tag 💬, Seedance 2.5 🎥, Mistral OCR 4 🧠

TLDR AI · 06/24 08:00

中文介绍 TLDR AI总结了近期AI领域的多个重要更新，包括Claude Tag功能增强、Seedance 2.5版本发布以及Mistral OCR 4的推出，涵盖了智能体、多模态和光学字符识别等方向。

How GPT-5 helped immunologist Derya Unutmaz solve a 3-year-old mystery

OpenAI News · 06/24 01:00

GPT-5 Pro helped solve a 3-year-old immunology mystery, offering insights into T cell behavior. The breakthrough could support cancer and autoimmune research.

中文介绍 OpenAI报道称，GPT-5 Pro成功协助免疫学家Derya Unutmaz解决了困扰其3年的免疫学难题，深入揭示了T细胞行为。这项突破有望为癌症和自身免疫疾病的研究提供重要支持。

Helping build shared standards for advanced AI

OpenAI News · 06/23 21:00

OpenAI helps build shared standards for advanced AI, supporting evaluation frameworks, safety practices, and global cooperation through the Appia Foundation.

中文介绍 OpenAI正积极参与高级AI共享标准的建设，通过Appia基金会支持评估框架、安全实践和全球合作。此举旨在确保AI技术的负责任发展，并促进国际社会在AI治理方面的协调。

Build real agentic apps using CUGA: two dozen working examples on a lightweight harness

Hugging Face Blog · 06/23 20:51

中文介绍 Hugging Face博客与IBM Research合作，介绍了如何利用「CUGA」框架和轻量级连接器构建真正的智能体（agentic）应用程序，并提供了约24个实际可运行的示例，以加速AI应用开发。

大家都是怎么深度使用 Codex 的？我现在让它自己沉淀项目经验，但感觉还不够体系化

06/25 11:54

6 回复 · 程序员 节点

LinkedIn 创始人里德·霍夫曼炮轰： SpaceX 不是一家人工智能公司， xAI 是彻底的灾难

06/25 11:39

8 回复 · 程序员 节点

记录又一次被入侵的挖矿程序

06/25 10:56

6 回复 · 程序员 节点

十年没正经写代码后，我靠 AI 把公司工作流重新搭了一遍

06/25 08:57

29 回复 · 程序员 节点

iPhone 屏幕防油渍防指纹涂层

06/25 00:11

8 回复 · Apple 节点

似乎 apple.com 买礼品卡加了 ip 检测

06/24 20:03

6 回复 · Apple 节点

macos27 的 siri ai 怎么可以不报 problem 啊？

06/24 14:37

14 回复 · Apple 节点

apple notes 已经支持一次性全部导出了

06/24 14:13

6 回复 · Apple 节点

升级 iOS 和 macos27 的能帮忙试试 surge 可用不

06/23 14:12

7 回复 · Apple 节点

我被 iOS27 的原生中文输入法折磨疯了

06/23 11:31

42 回复 · Apple 节点

Half-Life 2 in a Browser

06/25 14:00

75 points · 16 comments

The Unbearable Cheapness of Open Weight Models

06/25 10:51

25 points · 4 comments

Medical students are using popular research tool to pump out misleading studies

06/25 10:30

27 points · 10 comments

Cloudflare launched self-managed OAuth for all

06/25 10:18

112 points · 42 comments

Zombie unicorns are haunting Silicon Valley

06/25 10:16

77 points · 29 comments

Exploring the internal representations of Pangram 3.3.2

06/25 09:36

23 points · 5 comments

Ending respiratory infections

06/25 09:14

134 points · 60 comments

Mixing Visual and Textual Code

06/25 09:11

43 points · 11 comments

LuaJIT 3.0 proposed syntax extensions

06/25 08:41

131 points · 75 comments

Blogging can just be stating the obvious

06/25 07:46

182 points · 62 comments

Anthropic says Alibaba illicitly extracted Claude AI model capabilities

06/25 03:48

311 points · 535 comments

OpenAI unveils its first custom chip, built by Broadcom

06/25 01:47

Announcement: https://openai.com/index/openai-broadcom-jalapeno-inference-...https://decrypt.co/371971/openai-broadcom-jalapeno-first-cus...https://www.cnn.com/2026/06/24/tech/openai-broadcom-jalapeno...

Computer use in Gemini 3.5 Flash

06/25 01:21

205 points · 129 comments

The Xteink X4 E-Ink Reader

06/25 00:35

218 points · 124 comments

RubyLLM: A Ruby framework for all major AI providers

06/24 22:41

375 points · 60 comments

PR spam today looks like email spam in the early 2000s

06/24 22:32

208 points · 121 comments

Show HN: Nub – A Bun-like all-in-one toolkit for Node.js

06/24 22:14

Colin here, creator of Nub. I’ve had the general shape of this in mind for years. Nub runs your code with stock `node`, augmented with a `--require` preload hook[0] that adds a transpiler (oxc-powered, packaged as a Node-API add-on), registers a module resolution hook[1], and injects polyfills as ne

45°C cooling design cuts data center water use to near zero

06/24 22:10

288 points · 183 comments

Qualcomm to Acquire Modular

06/24 21:49

https://investor.qualcomm.com/news-events/press-releases/new...https://www.modular.com/blog/qualcomm-to-acquire-modularhttps://x.com/clattner_llvm/status/2069769232477192354, https://xcancel.com/clattner_llvm/s

Krea 2: SOTA open-weights 12B image model

06/23 23:31

368 points · 40 comments

Markdy: Like Mermaid Diagrams, but for Motion

06/23 23:00

23 points · 1 comments

15 sorting algorithms in 6 minutes (2013) [video]

06/23 13:29

21 points · 2 comments

GLM-5.2 is a step change for open agents

06/23 11:23

200 points · 111 comments

Matt's Script Archive: The Scripts That Reshaped the Web

06/23 09:30

38 points · 10 comments

Bohemia Interactive: Cold War Assault Remastered Source Code on GitHub

06/23 05:52

4 points · 1 comments

Dostoyevsky isn't difficult

06/22 23:15

125 points · 104 comments

Crawling BitTorrent DHTs for Fun and Profit [pdf]

06/21 22:12

88 points · 34 comments

A Practical Guide to SSH Tunnels: Local and Remote Port Forwarding

06/20 11:55

310 points · 59 comments

Show HN: Brain Frog – Can you be random enough for 11 lines of JavaScript?

06/19 20:57

26 points · 23 comments

Show HN: Write SaaS apps where users control where their data is stored

06/19 15:37

Hello HN,I would like to share with you linkedrecords.com - an open source backend as a service I'm working on since some time now. You can think of it as an firebase/convex alternative with an interesting twist.In 2018 I needed to write large software requirements/architecture docume