Mindfold — Elevate your understanding
Turn anything you're studying into an AI-powered workspace
What it does
Mindfold turns topics, PDFs, notes, and web content into interactive learning workspaces. Generate summaries, courses, quizzes, flashcards, glossaries, and use an AI study companion that understands what you're learning—all in one place.
Give Mindfold a topic, a PDF, or your own notes. It builds a focused hub with summaries, quizzes, flashcards, and Nova — your AI study companion — right there when you need them. A topic, a PDF, your own notes, or a photo of a textbook page — Mindfold takes it from there. Summaries, a short course, a glossary, and practice quizzes appear — structured and ready to study. Stuck on something? Ask Nova. It explains, quizzes, and adjusts to wherever you're at. Every topic gets its own workspace — summaries, a short course, and a glossary, all generated and organized automatically. Short courses come with practice quizzes built in. Flashcards handle the spaced review, so what you learn today is…from mindfold.fyi
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Life & fun · 10d ago · louisabraham.github.io
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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