LessonOrca
Intelligence infrastructure for personalized learning
What it does
A student learns A at school, does B at home, and C during tutoring. He gets an F. Nobody captures the full picture, so nobody knows how to help. LessonOrca builds a persistent model of how each student thinks and learns. We take in raw actions like chats/audio transcripts/grades, and create a comprehensive profile that compounds with every student interaction. This living profile currently powers automated lesson plans, homework, and parent reports for tutoring centers.
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nFactorial AI2025 · nfactorialai.com · ▲678Video calls with world's best minds as your personal tutors




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Ask an AI mentor any question and get tutorials adapted to your knowledge and goals. Each question updates your skills, shows the best career match and knowledge you miss. The more questions you ask — the more evident skill gaps.
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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…
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Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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