Benchmarq
See if AI can actually read your website
What it does
You can't get cited by AI that can't read you. Most brands have never checked whether it can. Benchmarq scans a URL and scores it across 200 signals, best-practices and standards: crawler access, structured data, and whether agents can complete tasks and transactions on your site. You get a score, and a fix list. The premium version includes competitive benchmarking. We're not a citation tracker. We benchmark your AIO, AEO and GEO technical audit.
Run GEO, AIO, and AEO audits with weighted scoring and clear diagnostics for teams building for AI search.
Benchmarq audits over 200 signals, best practices, and standards that determine how AI finds, understands, and cites your brand and then shows you exactly what to fix. Ready to benchmark your AI search performance? Start running audits now → AI is changing how brands get found. Most teams don't have a clear picture of where they stand or who owns fixing it. You are tracking Share of Voice, or Share of Authority and monitor citation and adapt content diligently but still feel that things are underperforming. Benchmarq audits one step before and scans your site for the technical blockers that hold back your potential. Enter any public URL. Optionally enable specialist modules for e-commerce…from benchmarq.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 · 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 · 16d ago · simedw.com