AnswerStanding
Compare across platforms and take action on recommendations
What it does
See whether ChatGPT, Claude, Gemini, Perplexity, and Google AI recommend your brand, which competitors appear instead, and what to improve. View metrics, generate reports, and take actions on recommendations to improve your standing.
See whether ChatGPT, Claude, Gemini, Perplexity, and Google AI recommend your brand, which competitors appear instead, and what to improve.
AnswerStanding shows whether AI recommends your brand, who appears instead, which sources shape the answer, and what you can do to improve your standing. AI assistants often respond with a short recommendation list—not ten pages of links. If your business is absent, the customer may never know you were an option. Search rankings tell you where your website appears. AnswerStanding tells you where your brand appears in the answer. Are you mentioned or recommended for the questions that influence a purchase? Where do you appear, and which competitors are consistently placed ahead of you? How does each AI describe your strengths, weaknesses, and ideal customer? Monitor recommendation,…from answerstanding.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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Life & fun · 10d ago · louisabraham.github.io
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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.
AI · 17d ago · simedw.com