Am I Recommended?
See if AI recommends your business—or your competitors
What it does
Am I Recommended? checks whether OpenAI and Gemini surface your business when customers ask real buyer-style questions. See when your business appears, which competitors are recommended instead, where AI providers disagree, and the exact questions tested. Start with a free 3-question visibility check, then unlock a deeper 10-question report.
Check whether OpenAI and Gemini surface your Australian business when buyers ask who to choose. See competitors, evidence and AI visibility gaps.
Run a point-in-time visibility check across buyer-style questions in OpenAI and Gemini and see whether your Australian business appears when customers ask AI who to choose. The paid report is designed so you can see what was tested, what each AI provider surfaced, who appeared instead, and what observable public-evidence differences are worthfrom amirecommended.com.au
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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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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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