RESTfender – Connect and secure your IoT devices
Hi HN, I'm Jay and my cofounder and I have been working on RESTfender to help connect and secure IoT devices. Would love to hear feedback. While there are some IoT platforms out there, we're focusing primarily on the problem of botnets and managing devices. We use machine learning to track and automatically categorize bots. The app: https://app.restfender.com Website: https://restfender.com IoT Camera example: https://iot-cam.restfender.com (the goal is to find a place to attract more attention like a bird nest, hamster on a wheel, hummingbird feeder, etc.)
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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 · 26d ago · cactuscompute.com
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