The fastest way to absorb knowledge
TLDR: Meet Lilys AI—a YouTube summary web service that saves you significant time. It delivers summaries that avoid excessive simplification, preserving the original source material, allowing you to grasp the entirety of a video without needing to play it. Hello, everyone! In this age of information overload, our mission is to help you process information faster and more efficiently. Have you ever struggled to watch an overly long video? Or encountered a video in a foreign language that felt inaccessible? You're not alone; I've faced the same challenges. After trying dozens of video summary…
What it does
In the maker’s words, at launch
TLDR: Meet Lilys AI—a YouTube summary web service that saves you significant time. It delivers summaries that avoid excessive simplification, preserving the original source material, allowing you to grasp the entirety of a video without needing to play it. Hello, everyone! In this age of information overload, our mission is to help you process information faster and more efficiently. Have you ever struggled to watch an overly long video? Or encountered a video in a foreign language that felt inaccessible? You're not alone; I've faced the same challenges. After trying dozens of video summary services and finding none that met my expectations—due to their tendency to oversimplify or misrepresent content—I felt compelled to create a solution. Our solution : 1. Summaries are not overly simplified and are created in appropriate chunks. 2. If you're skeptical about a summary, you can instantly unfold the original script it's based on. 3. Offering explanations for any part of the summary note, including specific paragraphs or keywords, with just a single click—placing insights within the video's context. 4. It's also possible to chat directly with the video content.
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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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