📦 ashhart/mcdma

MCDMA: Connect Your Mac to NVIDIA GPUs

MCDMA lets you wire your Mac directly into an NVIDIA GPU cluster, creating a raw data highway between Apple silicon and Linux hardware. It solves a messy problem where moving data between different computer chips usually requires slow, complicated software steps. By using a special network card, this tool moves large chunks of memory instantly, skipping the usual traffic jams. The real magic happens when you split a big AI task between machines, letting one system handle the heavy lifting while another manages the final output. It is experimental and needs specific hardware, but it shows how far we can push cross-platform speed.

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📦 cobanov/awesome-jev

Awesome Jev: Typed Decisions for AI

Build software that makes fast, confident decisions without generating endless text. Awesome Jev curates the entire ecosystem around Jev, a model from TypeSafe AI designed for typed, probabilistic choices like classification and routing. Instead of chatting, it takes your program's state and returns constrained answers with probabilities, letting your code handle the logic. The most surprising part? People are using it to pilot drones, rank coding agents, and even play Mario, proving it works way beyond simple data filters. It is not about replacing large language models, but about giving your apps a reliable, structured brain for high-speed logic.

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📦 expo/skills

Expo Skills: The Missing Brain for Your AI Coder

The Expo team built a cheat code for your AI coding assistant that teaches it how to actually build real mobile apps. This is not just another list of generic tips; it is a curated set of official instructions that tells your AI exactly how to handle the tricky parts of mobile development, like native animations, offline data fetching, and the specific quirks of iOS and Android. If you have ever watched your AI hallucinate a non-existent function or write web code that simply does not work on a phone, this is the fix.

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📦 0xsero/harness-bridge

Harness Bridge: One Tool for All Coding Agents

Harness Bridge is the local launcher that instantly connects any coding assistant to your own private model server without touching your existing files. The project solves the friction of manually editing configuration files or pasting API keys into command lines by handling the entire connection through environment variables that vanish when you are done. You simply pick a model from your local server, choose your favorite coding agent like Claude Code or Codex, and the tool opens a terminal already ready to work. This means your keys stay secure, your setup stays clean, and switching between different AI providers takes just one click.

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📦 dimentary/llm-robotics-playground

LLM Robotics Playground: AI Built These Robots

The LLM Robotics Playground is the collection that proves a frontier language model can engineer working robot controllers for delicate physical tasks. This library documents how a human guided an AI to build simulations where robots untangle headphone cables, carry objects on six legs, and even write code on a whiteboard with a marker. The most striking experiment features a robotic hand holding a pencil to draw a detailed dove, matching the intended path to within a fraction of a millimeter. It is a fascinating look at how language models are moving beyond text generation to actually solve complex, real-world mechanical problems.

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📦 jianglongye/dexterous-astra

Dexterous Astra: A Hand That Spins a Pen

A robot hand can spin a pen and twist a Rubik's cube. This project, called dexterous Astra, shows how simulated robot hands master these dexterous tricks. It provides ready-to-run environments and trained policies. You can run a zero-shot script that simply tells the hand to spin the pen. Or you can load a trained policy to see complex moves. The goal is to study how hands interact with objects. It is a clean way to test manipulation skills. You don't need to build the physics engine yourself. The code is set up for easy experimentation. This is a great resource for anyone studying robot hands. It makes complex dexterity accessible.

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📦 blader/humanizer

Humanizer: Make AI Text Sound Human

Take your AI generated prose and make it sound like a real person actually wrote it. Humanizer strips away the robotic habits that make text feel artificial, like forced lists or dramatic pauses, without changing your facts. It spots twenty five specific tells where language models slip up. The coolest part? It matches your unique voice if you paste a sample of your own writing. No more sounding like a chatbot. Just clean, natural prose that is actually yours. Give it a try.

📰 https://news.ycombinator.com/item?id=47362115

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📦 mutonby/vibetube

VibeTube: Record, Edit, and Publish with AI

VibeTube is the Mac app that turns raw multicam recordings into finished, publish-ready videos using AI. It records your screen and webcam in perfect sync, then hands the footage to an AI agent that edits the final cut, adds subtitles, and writes the description. You never have to touch a timeline or open a browser again. The AI even publishes the video directly to YouTube and TikTok for you. It is the closest thing to a fully automated video production pipeline available right now. Stop spending hours on editing and let the machine do the heavy lifting.

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📦 andrezaiats/snes9x-z

Snes9x-Z: The SNES Emulator That Runs 60% Faster

Snes9x-Z, a tweaked SNES emulator, squeezes out over sixty percent more speed from your computer without changing a single pixel of the output. This is not a magic trick; it is a carefully built fork that takes the standard emulator and rearranges the internal work so the graphics engine uses two CPU cores instead of one. The result is a massive performance boost that still produces bit-for-bit identical results to the original. Why does this matter? Because those extra cycles let you run shader filters, record gameplay, or play demanding games on weak hardware like old handhelds without lagging.

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📦 steadfastasart/geoscience-skills

Geoscience Skills: The AI Tool For Earth Data

Geoscience Skills is the open-source toolkit that finally makes coding agents actually understand the messy reality of earth science data. Most AI tools stumble when they encounter specialized formats like seismic files or well logs, but this project fixes that by teaching them exactly how to handle thirty different scientific libraries. Instead of guessing, your coding assistant learns to properly read a seismic file or calculate rock properties using the right formulas. It turns generic chatbots into genuine geological assistants capable of real analysis. If you work with earth data, this is your shortcut to having a smart partner who actually gets the science.

🆔 @hackernewsgithubprojects

📦 shadcn-labs/pdfcn

Turn React Code into Polished PDFs with pdfcn

Turn your standard React components into polished, downloadable PDF documents with just a single command. This free, open-source tool from the shadcn team solves the common headache of making complex web layouts look professional on paper. It uses two distinct rendering engines, allowing you to generate clean invoices, reports, or data tables without wrestling with obscure formatting settings. Because it follows the same familiar workflow as other popular UI libraries, developers can copy, paste, and ship high-quality documents immediately. You own the code, meaning you can fully customize every detail to match your brand.

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📦 xingchen-agi/xing4.0-29b-a4b

Xing 4.0: The Open Source AI Trained on Chinese Chips

Xing 4.0 is the open source model that proves domestic hardware can rival global giants. It is a massive language model built by China Telecom, featuring a design that activates only a fraction of its brain to process huge documents efficiently. The standout feature is that it was trained entirely on Ascend processors, offering a real alternative to traditional silicon. This makes it a powerful tool for developers needing strong coding and reasoning skills without relying on imported chips. You get a high performance engine that runs natively on this new platform, ensuring stability for complex tasks.

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📦 alibaba-damo-academy/damo-radar

RADAR: AI that reads CT scans

Diagnose abdominal conditions directly from CT scans using RADAR, a generalist AI model. This project solves the problem of needing separate tools for different diagnoses by learning directly from over forty thousand clinical reports without manual labels. It identifies twenty specific conditions, like aortic aneurysms or kidney cysts, with expert-level accuracy. The standout feature is its ability to understand anatomy-aware image-text pairs, bridging the gap between visual data and clinical language. This open-source framework provides a scalable path for radiology AI, offering researchers and developers a robust foundation for building next-generation diagnostic tools that work across complex clinical tasks.

📰 https://news.ycombinator.com/item?id=49761981

🆔 @hackernewsgithubprojects

📦 standardagents/jevpilot

JevPilot: The AI Driving Demo

This browser-based driving simulator lets an AI drive a Tesla Model Y through a realistic 3D city by sampling dozens of potential steering paths every fraction of a second. Built with Three.js and powered by Jev, it visualizes the exact moment the algorithm chooses its route, painting the selected path in bright blue while ghosting the rejected options in cyan and amber. The coolest part is that you can flip a switch to see every possible lane change and collision prediction before the car commits to a move.

🆔 @hackernewsgithubprojects

📦 dartnative/dartnative

DartNative: Real Native Apps Written in Dart

DartNative is the mobile framework that writes your app in Dart while using the phone’s actual built-in buttons instead of drawing fake ones on a screen. Usually, cross-platform tools paint their own graphics, making apps feel slightly off or slow to touch. DartNative skips that middleman entirely. Your code talks directly to the operating system’s real interface parts on a single, fast track. This means your app looks exactly like it belongs on the device, moves with the system’s natural speed, and feels instantly responsive. It’s the same coding style you know from Flutter, but the result is a true native application without the extra rendering weight.

🆔 @hackernewsgithubprojects

📦 openbmb/simplememvla

SimpleMemVLA: Robots That Remember Like Humans

A real dual-arm robot can now look back at its own video feed to remember exactly where it picked up a block, a capability called SimpleMemVLA. Instead of using complex memory modules that might lose details, this system treats the robot's past footage as a native video. It feeds this timestamped history directly to the brain of the robot, allowing it to figure out what happened minutes ago. This simple approach lets the robot succeed at tricky tasks like covering blocks in a specific order, achieving high success rates in real-world tests. By keeping the raw video intact, the robot makes faster and more accurate decisions without confusing similar objects.

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📦 0xsero/qwen38-3090-sglang

Run Qwen 3.8 on a Single GPU

A single consumer graphics card can now run a massive multimodal AI model that understands both images and videos at speeds that rival expensive professional hardware. This repository provides a ready to use Docker container that packages the Qwen 3.8 twenty seven billion parameter model specifically for NVIDIA RTX 3090 graphics cards. It solves the complex problem of making this large model run efficiently on standard PC hardware by using specialized quantization and a unique decoding technique called DSpark. The container handles all the difficult software setup automatically, so you just need to run one simple command to start serving requests locally.

🆔 @hackernewsgithubprojects

📦 chetaslua/jevmeter

Jevmeter: The BS Meter for Any Video

Jevmeter is the video tool that turns every sentence into a live scorecard. It uses an AI model to analyze your footage and render a cool, sixteen-by-nine edit that flags evasive answers and hype in real time. The best part is that it costs just five cents to process an entire debate. You drop in a file, pick a preset like debate or sales pitch, and it handles the rest. It is the perfect way to turn any talk into a shareable highlight reel. Give it a spin and see who dodges the most questions.

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📦 tamaratran/fast-jev-compaction

How fast-jev-compaction saves your code context

Shrink your coding bot’s memory without losing the details that matter. Fast Jev Compaction fixes the annoying habit of AI tools forgetting file paths or exact errors just to fit more text into the window. Instead of summarizing your chat, it asks a second model to look at your entire history and decide exactly which old tool results to drop. Anything it keeps stays word for word, so you never lose a critical command. This plugin turns messy, bloated conversations into a clean, precise record. Your bot remembers the important stuff, not just a vague summary. It’s a simple swap that keeps your coding sessions sharp and accurate.

🆔 @hackernewsgithubprojects

📦 arahim3/cachebeat

Cachebeat: Stop Paying Full Price

Cachebeat is the tiny Claude Code skill that stops your conversation from paying full price just because you stepped away. It solves a sneaky billing trap where long AI sessions lose their memory discount after an hour of silence, causing the entire chat history to be re-processed at ten times the normal cost. The surprising part is that it uses a simple inactivity timer to send a few words of text, like saying "still here," which resets the clock and keeps the cache warm. This means your next message reads from the cheap cache instead of triggering an expensive rebuild, saving you real money or protecting your subscription quota.

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