Three Way Finish.
Build. Prove. Finish. Automation that closes the job.
What it does
Three-Way Finish is APN’s core end-to-end finishing system: three coordinated planes and 12+ controlled stages that take an idea, workflow, unfinished project or half-built platform through planning, build, verification, correction, deployment and handover. The method is proven across real software and operational cases, with a simple guided path or thousands of possible control combinations. We are now extending the same governed model into structured medical-research and scientific workflows.
One Australian front door for privacy help, data removal, automation, evidence, verification, finishing, APIs, research and trusted external pathways.
APN connects people and organisations with practical help, professional services, useful technology, research and appropriate Australian specialists—without making you decode the whole system first. Start at “What do you need help with?” or browse every service directly. Optional text files stay on this device and are not uploaded. The wider APN network can carry hundreds of products without making the front door feel like a warehouse. Start with the outcome; the deeper registry stays available when you want it. A bounded private validation of one real workflow, its control points, evidence requirements and next build decision. Five focused local-first instruments for privacy actions,…from australianprivacynetwork.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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