ReplyReviews
AI-powered review & social media management
What it does
ReplyReviews helps local businesses manage their online reputation and social presence from one place. Automatically reply to Google reviews, publish and schedule social media posts, manage Google Business Profile content, and track performance—all from a single dashboard. Built for restaurants, cafes, salons, and other local businesses that want to save time, stay active online, and turn customer feedback into growth.
All-in-one marketing platform for restaurants: AI review replies, social posting & scheduling, content insights, local rank tracking, and email + WhatsApp marketing — one dashboard.
ReplyReviews replies to your Google reviews with AI, creates and schedules content for Instagram, Facebook, YouTube, Threads and Google Business Profile, shows insights and local rankings across every channel, and runs your email & WhatsApp marketing — one dashboard instead of five tools. ReplyReviews puts your Google reviews, posts, and local SEO on autopilot — three simple steps to more local customers. Link your Google Business Profile and social accounts in a couple of clicks — no technical setup, no code, and no agency required. Let AI reply to Google reviews in your brand voice, publish posts across Google and social, and generate content — all on autopilot from one dashboard. Track…from replyreviews.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.
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