Chartbuddy
Business charts that stay editable on every surface
What it does
Chartbuddy makes the charts finance and strategy teams need: waterfalls, mekkos, stacked bars and combo charts, 14 types in all, with smart annotations, smart axes, number formats and brand styling. Build a chart in the HTML your AI generates, in the Hub desktop editor, or natively inside Google Slides. It travels like an image and opens fully editable in the next tool. Embed is free. Hub is free for the first 1,000 users in 2026. Google Slides gives you 10 free sessions, no card.
The default charting layer for strategy and finance in the AI era. Business charts that stay alive and editable across every surface.
The default charting layer for the AI era. Turn your data into business charts that stay alive and editable across every surface. Build and edit charts natively in Google Slides, synced to your Google Sheets data. The Chartbuddy desktop editor for Mac and Windows, connected to Claude Code, Codex or Cursor. Prompt your way to the chart you want, refine it in the app, then drag it into Google Slides, PowerPoint, Slack or Notion. Pull any chart back whenever the numbers change. Generate an HTML deck or dashboard with Claude or ChatGPT and every chart inside it is an editable Chartbuddy chart. Edit them in the HTML, then drag them into Google Slides, PowerPoint, Slack or Notion without…from chartbuddy.io
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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.
AI · 16d ago · simedw.com
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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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Life & fun · 9d ago · louisabraham.github.io


- SA
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.
AI · 16d ago · simedw.com