
Slate AI
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What it does
I built Slate AI because I was wasting 30 min every night picking a movie on Netflix and ending up on YouTube instead. It's a custom recommendation engine that learns your taste through ratings - no generative AI, built from scratch. What's different: - Recs get smarter with every rating - Letterboxd sync to import existing ratings - Add friends, see what they're watching - Franchise watch orders (MCU, Star Wars) Free on iOS. Built by a solo dev.
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Movie Deep Search by AI Keytalk2023 · ▲259Use recommendation AI that knows every movies ever created

- RARecommendarr – AI Driven Recommendations Based on Sonarr/Radarr Media2025 · github.com · ▲88
Hello HN! I've built a web app that helps you discover new shows and movies you'll actually enjoy by: - Connecting to your Sonarr/Radarr/Plex instances to understand your media library - Leveraging your Plex watch history for personalized recommendations - Using the LLM of your choice to generate intelligent suggestions - Simple setup: Easy integration with your existing media stack - Flexible AI options: Works with OpenAI-compatible APIs like OpenRouter, or run locally via LM Studio, Ollama, etc. - Personalized recommendations: Based on what you actually watch. While it's still a…

- NFNetflix for AI movies – built with Cursor in 2 days2024 · watch.withbento.com · ▲12
We feel the new narrative-style content made with AI tools deserves a familiar home apart from the concept demos and tutorial videos cluttering Reddit and YouTube. It's what's next!
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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.
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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 · 27d ago · cactuscompute.com

