Authmor
The reverse citation for authorship in the AI era.
What it does
Authmor by RAS. Free/Donation It’s 2026—who doesn't have concerns about authorship and prompt honesty? SOLUTION: AuthMor, the reverse citation for the AI era. It delivers seamless prompt capture and export, and automatically generating an AI-powered summary that highlights your exact core contributions, iterative steering, and critical corrections. Replace failed detection tools and messy logs with clean, verifiable proof of genuine human ownership. Visit ROMAN applied Sciences to read more
Roman Applied Sciences — innovation, enablement, and music.
RANGES is a compact, shape-preserving naming system for code built around a simple idea: AI does not always need more language. Often, it needs clearer structure. Modern frontend code often accumulates names such as main-navigation-container-wrapper-inner . Each name may sound reasonable in isolation, yet repeated across HTML, CSS, scripts, prompts, diffs, and AI responses, descriptive naming can become a second layer of code that the system must continually interpret. That extra language has a cost. It increases character count, consumes context, creates more opportunities for inconsistent naming, and makes targeted changes harder when several identifiers sound almost—but not quite—the…from nodarama.com
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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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