01 · The noise
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02 · The brief
The single strongest signal from each feed right now — auto-compiled, refreshed all day.
03 · The research
What researchers are upvoting right now, via Hugging Face Daily Papers.
04 · Paper Playground
Pick a trending AI paper, understand its big idea in plain English, then turn it into a portfolio-ready project you can actually build.
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A kid-friendly guide to the paper's core idea.
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Scope the learning project for Starter, Intermediate, or Advanced.
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Get an MVP plan, portfolio bullet, and interview prompts.
05 · The toolbox
AI repos created in the last 30 days, ranked by stars.
06 · The agents
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07 · The evidence
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08 · The models
What's trending on the Hugging Face Hub right now.
09 · The launchpad
AI projects shown on Hacker News in the past two weeks.
10 · The conversation
Top AI stories on Hacker News from the past week.
11 · The labs
Fresh posts from OpenAI, Google DeepMind, Google AI, and Hugging Face.
12 · Lock on
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Today's read
Today's AI landscape reveals a critical shift toward practical agent deployment and evaluation, with papers like CRM-Agent-Bench highlighting the need for agents that handle complex, stateful enterprise environments beyond simple task completion. The rise of frameworks like ReGE and tools like OpenShell suggests practitioners are focusing on experience synthesis and secure agent execution as key differentiators for real-world applications. Meanwhile, the controversy around human-centric AI takes center stage in Hacker News discussions, reflecting growing concerns about AI's actual impact on employment despite technological advances in multimodal models like DeepSeek-V4.1 and Genie 4. Practitioners should prioritize robust verification mechanisms as outlined in "Rethinking Verification in Agent Harnesses" and focus on user-centric benchmarks like iPrefBench to ensure their solutions deliver tangible value beyond technical capabilities.
Agent harnesses enable large language models to act through tools, observe the results, and iteratively work toward a task goal. Verification checks and revises agents' work to improve output quality. Yet there is limit…
Repeated attempts at interactive tasks uncover facts, useful operations, and failures that can inform subsequent execution. We introduce ReGE, a framework for turning this recorded experience into guidance for a fresh a…
Deploying language agents in real applications demands more than the right answer: an agent must execute a multi-step business process correctly, follow domain-specific rules, and interact with a user across a dialogue,…
Existing interpretability tools do not test whether a representation keeps the same content when only the phrasing changes. We treat each paraphrase pair as a local witness that two activations should agree and build a…
一个自己找热点、自己写日报的网站框架。把信源和精选标准换成你的，它就是你的行业热点站。
AI API 中转站评测排行与切换工具：实测可用率、延迟与价格 · Open-source AI API relay benchmark, rankings & switcher for Claude Code / Codex
A design system for AI applications. Material, physical, tactile, technical.
Daily radar for new AI terms: names of new models, products and repos, caught on X, Hugging Face, GitHub and sitemaps before keyword tools list them.
Agent research
Frontier multimodal large language models (MLLMs) can control robots without robot-specific training, but how their capabilities compare and interact with post-trained vision-language-action (VLA) and world action model…
Agent research
A robot policy needs to understand what a task is asking for in a scene, and how to move the robot to accomplish that task. To achieve these two skills, we introduce Zero-real Agent Policy (ZAP), a recipe that teaches a…
Agent framework
Reverse engineer anything with agents, from app behavior down to native binaries.
Agent framework
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor…
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