Ultron Live
Real-time Vision Infrastructure for AI Agents
What it does
Ultron Live gives your AI eyes. It watches any screen, camera, or video feed at up to 60fps and turns it into structured commentary, persistent memory, and voice narration. Three primitives: SEE, REMEMBER, SEARCH. Build screen-aware copilots, live video search, automated QA, and real-time monitoring, one SDK. Works with GPT-4o, Gemini, and 60+ models; swap per frame or session. REST or WebRTC for sub-second latency. Free tier, start in minutes. We are live with 2000+ active users now.
Ultron AI turns any screen into a live AI narrator powered by vision + voice intelligence. 60fps monitoring, local memory, 50+ LLM models. Not a chatbot — a live, thinking, reacting AI presence.
Ultron continuously observes your screens, cameras, and applications, transforming real-time inputs into a unified, structured memory layer and fully automated intelligence. Watch how Ultron turns live screen pixels into searchable, queryable context — in real time. If you saw it — Ultron can answer it. Works across native apps, browsers, dashboards, terminals, and legacy tools. Routes into GPT, Claude, Gemini. OS-level pixel access. Monitors live screen at 60fps across any app — native apps, video players, browsers, dashboards, legacy enterprise tools. Persistent local memory of meaningful frames, keyed to state changes instead of snapshots. Sub-900ms indexing. Forever searchable.…from live.ultronai.me
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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 · 17d 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…
AI · 27d ago · cactuscompute.com


Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
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 · 17d ago · simedw.com