Pappper
The canvas where your worksheets get solved.
What it does
Pappper is an AI workspace for worksheets and dossiers. Drop your files onto an infinite canvas, then write, draw, highlight, and annotate right on top. Chat with the AI assistant to explain tasks, solve exercises, and edit directly on the canvas. Folders, search, share links, version history, and export keep it all in one place. No download, everything synced. Markup that's actually nice to use.
Upload a worksheet or PDF, annotate right on top, and ask AI about any part of the page — or have it write the answer into the blank. Free, no account needed.
Upload anything, annotate right on top, and ask the AI about any part of the page. Pappper is a flexible workspace for worksheets, PDFs and notes. Upload a file, mark it up, and ask the AI for help with any part of it. You can also have it add a response directly to the page. Upload your worksheet, select the exercise, and ask for help. Pappper can explain a step, walk you through a solution, or add an answer to the page. You can always edit or undo it. Yes. Highlight, draw, type and add images to a PDF, then select any part of the page to ask a question about it. Yes. Pappper can add a response where it belongs on your worksheet, ready for you to review, edit or undo. It can also add…from pappper.com
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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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Launched alongside, August 2026
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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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