Pao Ramen
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How we built our multi-agent research system
Jun 16 · www.anthropic.com ⎯ On the the engineering challenges and lessons learned from building Claude’s Research system
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Bayes For Everyone
Jun 15 · www.astralcodexten.com ⎯ A guest post by Brandon Hendrickson
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The Intelligence Curse
Jun 15 · intelligence-curse.ai ⎯ This series examines the incoming crisis of human irrelevance and provides a map towards a future where people remain the masters of their destiny.
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Weavy | AI-Powered Design Workflows, Built for Creative Pros
Jun 12 · www.weavy.ai ⎯ Transform your creative vision into scalable workflows with Weavy. Integrate AI models and editing tools in one seamless, node-based platform.
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Design Beyond Barriers
Jun 12 · designbeyondbarriers.com ⎯ What makes an interface accessible? And how can designers create experiences that work for all users? This guide answers all your burning questions about accessibility—like how to design for everyone, even those juggling a hot coffee and a pet hamster.
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GitHub - autoscrape-labs/pydoll: Pydoll is a library for automating chromium-based browsers without a WebDriver, offering realistic interactions.
Jun 11 · github.com ⎯ Comments
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Reinforcement Pre-Training
Jun 11 · arxiv.org ⎯ In this work, we introduce Reinforcement Pre-Training (RPT) as a new scaling paradigm for large language models and reinforcement learning (RL). Specifically, we reframe next-token prediction as a reasoning task trained using RL, where it receives verifiable rewards for correctly predicting the next token for a given context. RPT offers a scalable method to leverage vast amounts of text data for general-purpose RL, rather than relying on domain-specific annotated answers. By incentivizing the capability of next-token reasoning, RPT significantly improves the language modeling accuracy of predicting the next tokens. Moreover, RPT provides a strong pre-trained foundation for further reinforcement fine-tuning. The scaling curves show that increased training compute consistently improves the next-token prediction accuracy. The results position RPT as an effective and promising scaling paradigm to advance language model pre-training.
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Unblocked AI | Figma
Jun 11 · www.figma.com ⎯ AI Image Editor for Figma Unblocked is a Figma AI plugin for editing images without leaving Figma. Use AI-powered tools to enhance your visuals—no login or registration required. Follow me on X/Twitter for the latest updates. Image generation with Flux ⎯ Generate stunning, realistic images with…
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Introducing the Spreadsheet Agent, in private preview — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
Jun 10 · www.llamaindex.ai ⎯ LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
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A brief history of JavaScript | Deno
Jun 10 · deno.com ⎯ In 30 years, JavaScript went from being a little scripting language to one of the world’s most popular. Here are key moments to show how it has evolved and where it is headed.
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The illusion of "The Illusion of Thinking"
Jun 09 · www.seangoedecke.com ⎯ Very recently (early June 2025), Apple released a paper called The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the…
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Big Bets | Jack Danger
Jun 09 · jackdanger.com ⎯ A ‘Big Bet’ is a rapid push into a new market space, typically championed by an executive and led by experienced engineers. While the term ‘bet’ suggests a risk, these initiatives often fail and come with hidden costs, like draining morale and neglecting other key products. I witnessed multiple big bets at Square and had the misfortune of being part of a couple. I worked on the Square Wallet team, which was Square’s first attempt to create a B2C product. Later, I got picked to implement the doomed “Square 275” feature where we charged merchants a flat fee for unlimited credit card processing. Both were big bets mandated by the CEO, bypassing the best practices of product research.
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Fit Markdown - Crawl4AI Documentation (v0.6.x)
Jun 08 · docs.crawl4ai.com ⎯ 🚀🤖 Crawl4AI, Open-source LLM-Friendly Web Crawler & Scraper
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ASCII Diagrams
Jun 08 · asciidiagrams.github.io ⎯ chromium/android_webview/.../aw_metrics_service_client.h#L48-L111 // WebView metrics set up happens like so: // // startup // │ // ├────────────┐ // │ ▼ // │ query GMS for consent // ▼ │ // Initialize() │ // │ ▼ // │ SetHaveMetricsConsent() // │ │ // │ ┌──────────┘ // ▼ ▼ // MaybeStartMetrics() // │ // ▼ // MetricsService::Start() // // All the named functions in this diagram happen on the UI thread. Querying GMS // happens in the background, and the result is posted back to the UI thread, to // SetHaveMetricsConsent(). Querying GMS is slow, so SetHaveMetricsConsent() // typically happens after Initialize(), but it may happen before.
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The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity
Jun 08 · machinelearning.apple.com ⎯ Recent generations of frontier language models have introduced Large Reasoning Models (LRMs) that generate detailed thinking processes…
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Sharing everything I could understand about gradient noise
Jun 07 · blog.pkh.me ⎯ Comments
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Small Programs and Languages - ratfactor
Jun 07 · ratfactor.com ⎯ Comments
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GitHub - wimpysworld/faff: Drop the faff, dodge the judgment. Another bloody AI commit generator, but this one stays local 🦙
Jun 07 · github.com ⎯ Drop the faff, dodge the judgment. Another bloody AI commit generator, but this one stays local 🦙 - wimpysworld/faff
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A masochist's guide to web development
Jun 07 · sebastiano.tronto.net ⎯ I have recently worked on making a web application out of my latest Rubik’s cube optimal solver. This involved building a rather complex C code base (with multithreading, SIMD, callback functions and whatnot) to WebAssembly via Emscripten, and writing a minimal amount of JavaScript and HTML for the frontend.
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Odyc.js
Jun 07 · odyc.dev ⎯ Odyc.js is a simple JavaScript library to create interactive narrative games, even without coding experience.