Sanbi.ai
Don't just track AI citations, act on them.
What it does
Don't just track AI citations, act on them. Sanbi.ai is a Generative Engine Optimization platform that monitors your brand visibility across ChatGPT, Gemini, Perplexity, and Claude. Track your AI Visibility Score, map exact citation sources, and analyze your Share of Voice against competitors. We go beyond reporting to help you identify citation gaps and optimize your content. Own your category and become the brand AI recommends as search shifts from links to answers.
Track how your brand appears across ChatGPT, Gemini, Perplexity & Claude. Monitor AI citations, optimize content, and grow your share of voice in AI search.
Track your AI search visibility across ChatGPT, Gemini, Perplexity & Claude. Become the brand AI recommends. Sanbi surfaces the exact threads AI cites about your category — then helps you craft and post the reply that shapes the next answer. Surface threads across Reddit, Quora, Wikipedia, and blog sites — filtered by relevance and AI citation potential. Been trying “Design Tool” lately, pretty amazing!!! Write your own or let AI generate a reply matched to context. Spot emerging threads in real time. Get in before AI picks them up. From audit to ongoing management — we find the platforms that move your AI answers, build warmed-up accounts, and run them so you never risk a ban.…from sanbi.ai
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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 · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


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…
AI · 26d ago · cactuscompute.com


Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d 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 · 17d ago · simedw.com