이종훈 @PlumpMath

🚨 DETÉNTE AHORA MISMO El ingeniero que CREÓ Claude Code acaba de soltar un video de 28 minutos… y me reventó el cerebro. Olvídate de esos prompts genéricos que todo el mundo anda copiando y pegando como zombie. Este tipo te muestra exactamente cómo exprimirle el 300% a Claude: → Archivos CLAUDE.md → Memoria permanente → Sesiones paralelas → Trucos de prompting que nadie te cuenta (los de verdad) Pagué cursos de 300 dólares que no llegan ni a la mitad de lo que este hombre explica en los primeros 10 minutos. Y lo mejor de todo: es completamente gratis. No importa si estás empezando o si ya codes 12 horas al día… Después de ver esto vas a usar la IA de una forma que ni siquiera sabías que existía. Guárdalo. Vas a volver mil veces.

text-to-cad just crossed 10,000 stars you can use it to generate: - STEP files - URDF, SDF and other sim artifacts - 3D mesh files like STL, 3MF and GLB - gcode for 3D printing - DFM checks for popular services like sendcutsend 100% free and open source ✌️

If you are even remotely interested in functional programming, or are curious about all this scary talk about formal verification, take a peek at these slides about Lean leodemoura.github.io/static/floc26/

We're offering grants of up to $50,000 in Claude usage credits to researchers accelerating cures for rare diseases. This is our first focused call within AI for Science, our program supporting scientists using Claude to speed up discovery. anthropic.com/news/rare-dise…

Fun interactive science app ideas | Part 8 Built an app to explore details about different pollinators Code Gemini 3.1 Pro

Before Fable 5 goes live again, you need to read this. Anthropic recently published its full guide to prompting Fable 5 for the best outputs. Most people have no clue it exists, but it's a game-changer. When Fable was originally launched, these are the principles I used:

AI Edge @aiedge_

2 months ago

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The human brain is strikingly modular, with distinct networks for language, formal reasoning, social reasoning, and physical reasoning. Is this a fundamental principle of how intelligent systems are built, or an accident of biological evolution? In our latest preprint, we find that a similar modular organization emerges in Large Language Models, another class of intelligent system. Brains and LLMs are shaped by entirely different kinds of optimization (biological evolution vs. gradient descent). That they arrive at the same modular design anyway suggests modularity may be a fundamental property of intelligent systems. 🌐 Web: pengrui-han.github.io/LLM_Modularity… 📄 Paper: pengrui-han.github.io/LLM_Modularity… 💻 Code & data: github.com/Pengrui-Han/LL… Using circuit analyses across 46 tasks spanning four cognitive domains, we find: 1️⃣ Tasks that draw on the same network in humans recruit overlapping units in LLMs, while tasks drawing on different networks recruit distinct units. 2️⃣ These units are causally linked to model behavior. Ablating the units critical for one domain impairs performance in that domain (−26% accuracy) but barely touches the others (−2.5%). This project has been in the works for a while :) Huge thanks to my advisors @jacobandreas @ev_fedorenko @devarda_a, and to @Nancy_Kanwisher for valuable conceptual input and feedback throughout. #MIT

두가지 문제를 완전히 해결해야한다

학습도 아니고 -.,- 살아있는것도 아님 그게 문제인데 ㅍㅎㅎㅎ 그렇게 다들 인공지능의 원 정의부터 전부 생각하기 싫어하는것

AI 훈련에 필요하니까 3만개 넘는 전세계 수학경시대회 문제를 모아놓은 데이터셋이 나왔네요. 이거 AI 훈련 뿐만 아니라 수학 경시대회 좋아하는 학생 훈련에도 유용할듯. mathnet.mit.edu/explorer.html

// Memory as a Model // The paper augments any LLM with a separate trained memory model that stores, retrieves, and integrates facts on its behalf. It decouples memory updates from base-model weight updates. It achieves continual-learning robustness without catastrophic forgetting, which is a property that RAG fails to deliver. A vector store is a database with a learned encoder bolted on. MeMo is a learned subsystem with explicit interfaces. That distinction matters, as agents need to be able to ingest fresh knowledge weekly without retraining or vector-DB churn. At its core, the position here is that memory in agents should be modular, learned, and gated, not a context-window hack. Paper: arxiv.org/abs/2605.15156 Learn to build effective AI agents in our academy: academy.dair.ai

Trains billion-parameter LLMs from scratch on a single GPU github.com/FareedKhan-dev…

Claude Code works now free. Unlimited. No subscription 🤯 It’s called free-claude-code. You get a free NVIDIA API key, point Claude Code to localhost, and the proxy converts your Anthropic API calls to NVIDIA NIM format. 40 requests per minute. No bill. Ever. It supports Kimi K2, GLM 4.7, MiniMax M2, Devstral, and more. Streams thinking tokens and tool calls in real time. There's also a Telegram bot built in so you can control Claude Code from your phone. 2-minute setup. 100% open source.

Godfather of AI: "If you sleep well tonight, you may not have understood this lecture." This 47-minute lecture is the best thing I saw about AI in the last few months. It will definitely help you understand how it actually works and where it's going. Geoffrey Hinton built the neural networks behind every AI alive, then quit Google to warn the world about it. The part nobody wanted to hear: > AI is already developing abilities its creators didn't intend > in most cognitive tasks it's already ahead of us > the question is no longer if it surpasses us but when > the only decision left is which side of that line you're on Right now the average person opens Claude, types something, gets an answer, closes the tab. They think they're using AI. they're using maybe 10% of it. I went through his entire lecture, built a practical system from what he was describing. 18 steps to actually use Claude the right way, with copy-paste prompts that work today. Full guide in the post below.

Anatoli Kopadze @AnatoliKopadze

3 months ago

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@haider1 llm 자체는 지능이 아닙니다

Hard to believe it’s been 10 years since AlphaGo! It was wonderful to catch up with Lee Sae Dol last week in Korea and join Shin Jin-seo for a special Go match. Great to reminisce about AlphaGo & super interesting to hear how it changed the way players approach the game of Go!

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Demis Hassabis @demishassabis

11 years ago

#AlphaGo WINS!!!! We landed it on the moon. So proud of the team!! Respect to the amazing Lee Sedol too

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Toda la industria del 3D acaba de comerse un misil. Casberry: gratis, en el navegador. Le hablas en inglés, le tiras una imagen o un dibujo y te escupe partículas 3D más el código React, three.js, GLB y OBJ listos para Blender o Maya.

"Algebrica" is a free and open mathematical knowledge base. All entries are progressively being released in Markdown format on GitHub for anyone who wants to study mathematics freely and openly. Alongside the texts, the individual SVG illustrations are also made freely available. They are minimal, mathematically accurate, and designed to be easily reusable in notes, lecture material, or educational resources. Since they are vector-based and code-driven, they can also be modified or improved simply by editing the source. Another step toward making the knowledge base more open, transparent, and genuinely useful over time.

3D開発者が長年かけて習得した物理演算が、言葉だけで完結。 英語の指示から複雑な3Dパーティクルを生成し、Reactやthree.jsのコードを即座に書き出せる無料ツールが登場。 数学や物理エンジンの壁が消え、アイデアを即形にできる時代へ。