Haha, but what's not April's fools is that ollama finally got MLX support the other day
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OpenClaude Reaches 1.4K Stars on GitHub
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repo link → https://
github.com/Gitlawb/opencl
aude
… Already at 1.4k+ on GitHub for a reason. -
CaP-X: Open-Source Framework for Coding Agents in Robotics
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Robotics: coding agents’ next frontier.
— Max Fu (@letian_fu) 1 avril 2026
So how good are they?
We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve… pic.twitter.com/P547voL0NvRobotics: coding agents’ next frontier. So how good are they? We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve code reliability. From @NVIDIA @Berkeley_AI @CMU_Robotics @StanfordAILab capgym.github.io 🧵
→ View original post on X — @berkeley_ai, 2026-04-01 14:00 UTC
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Claude Code Leaked: Open-Source Community Releases OpenClaude
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THE biggest AI leak of the year happened yesterday. Claude Code’s proprietary source leaked via npm. In under 24 hours, the open-source community reverse-engineered it, stripped the vendor lock-in… …and released `OpenClaude` They literally turned the leaked Claude
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AGI Achievement: AI Influencing Political Decisions Through Code
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Quand on sera arrivé a "Madame Claude" et qu'ils auront developpé une maison close pour le code, et qu'elle maintiendra du code sexy, ainsi que des infos persos sur les politiques pour influencer leurs decisions, on aura atteint l'AGI.
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Build a Large Language Model from Scratch Repository
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If you found it useful, reshare it with your network Follow me → @Sumanth_077 for more insights and tutorials on AI Engineering! nitter.net/Sumanth_077/status/203… Sumanth (@Sumanth_077) Build a Large Language Model from scratch! This repository contains the code examples for developing, pretraining, and finetuning a LLM from scratch. It is the official codebase for the book Build a Large Language Model (From Scratch). Notebook examples are included for each chapter: Chapter 1: Understanding Large Language Models Chapter 2: Working with Text Data Chapter 3: Coding Attention Mechanisms Chapter 4: Implementing a GPT Model from Scratch Chapter 5: Pretraining on Unlabeled Data Chapter 6: Finetuning for Text Classification Chapter 7: Finetuning to Follow Instructions Link to the repo in the comments! — https://nitter.net/Sumanth_077/status/2039332313910383043#m
→ View original post on X — @sumanth_077, 2026-04-01 13:22 UTC
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GitHub Repository: LLMs from Scratch by Sebastian Raschka
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Github Repo: github.com/rasbt/LLMs-from-s…
→ View original post on X — @sumanth_077, 2026-04-01 13:21 UTC
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Build Large Language Models from Scratch: Complete Book Repository
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Build a Large Language Model from scratch! This repository contains the code examples for developing, pretraining, and finetuning a LLM from scratch. It is the official codebase for the book Build a Large Language Model (From Scratch). Notebook examples are included for each chapter: Chapter 1: Understanding Large Language Models Chapter 2: Working with Text Data Chapter 3: Coding Attention Mechanisms Chapter 4: Implementing a GPT Model from Scratch Chapter 5: Pretraining on Unlabeled Data Chapter 6: Finetuning for Text Classification Chapter 7: Finetuning to Follow Instructions Link to the repo in the comments!
→ View original post on X — @sumanth_077, 2026-04-01 13:21 UTC
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Open Source Project Receives Design Improvements
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it's open source! i will add better design too 🙂
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Neural Cartography: Real-time Mapping Engine with Distributed Agents
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Neural Cartography – a real-time city mapping engine powered by distributed rendering agents
— SHAHNAB AHMED (@AhmedShahnab) 1 avril 2026
Agents work in parallel. City name gets drawn in the center. Urban fabric assembles around it.
The idea behind Neural Cartography – a WebGL visualization where 7 specialized agents are… pic.twitter.com/5L7NYhvTFENeural Cartography – a real-time city mapping engine powered by distributed rendering agents Agents work in parallel. City name gets drawn in the center. Urban fabric assembles around it. The idea behind Neural Cartography – a WebGL visualization where 7 specialized agents are dispatched simultaneously to reconstruct any city from raw geospatial data, tracing roads, waterways, railways, and city boundaries in real-time – right in your browser. #CreativeCoding #ThreeJS #ReactThreeFiber #DataVisualization #Geospatial #AgenticAI @reactthreefiber @threejs #builders [Translated from EN to English]