SetRise
Your Climb, Made Visibile
What it does
Customers now ask ChatGPT and Claude who to hire, and those answers pick winners. EchoCheck shows you where you stand. It asks both AIs the real questions your buyers ask, counts how often your business appears, names the competitors recommended instead, and shows which sources the AIs actually read. It also runs 13 instant technical checks: AI crawler access, schema, llms.txt. Built by an AEO company that ranks itself using the same playbook. The instant site check is free, no signup.
SetRise is an AEO company in New Jersey. We get businesses recommended by ChatGPT, Claude, and Gemini with measured AI visibility audits and builds.
SetRise is an AEO (Answer Engine Optimization) company in New Jersey. Customers are asking AI who to hire. We turn your business into the answer: auditable data, credible citations, and websites machines can understand. We make sure the answer is you. By the time someone clicks through from an AI answer, the research is already done. They arrive ready to act. Strategy and craft from the same shop: we find out what the machines say about you, then build everything it takes to change the answer. Our engine, EchoCheck, asks the exact questions your buyers ask across ChatGPT, Claude, and Gemini, then shows you where you stand, who gets recommended instead, and which sources the machines read.…from setrise.io
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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 · 16d ago · simedw.com
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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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Launched alongside, August 2026
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Life & fun · 9d 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 · 16d ago · simedw.com