
SEO Miner
AI-powered SEO intelligence to outrank your competitors
What it does
SEO Miner is an AI-powered SEO tool built to help you outrank competitors with ease. Discover high-impact keyword opportunities, evaluate technical site performance, analyze rival strategies, and monitor real-time rankings. Crafted for creators, marketers, and developers who want fast, intelligent SEO insights without complex dashboards or enterprise subscriptions.
Enter a URL to extract page keywords, compare competitor language, and export a tidy report for content planning. A focused research loop: crawl, compare, export, and plan the next content move. Add any public URL and the app normalizes the address for analysis. Competitor pages are checked for related keyword language and gaps. Download CSV or JSON for briefs, docs, or your internal workflow. A cleaner surface for content creators, SEO specialists, and small teams that need answers quickly. Pull practical keyword signals from any public page in seconds. Compare your page against ranking competitors and spot missing opportunities. Surface pages that matter for your topic and use them as…from seominer.vercel.app
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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…
AI · 26d ago · cactuscompute.com


Launched alongside, August 2026
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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 · 16d ago · simedw.com