Signal Zero
Production-Grade AI Agents & Real-Time Data Architecture
What it does
Signal Zero is an integrated AI & systems engineering agency. We architect and deploy production-grade intelligent systems that turn complex data into competitive advantage. What we build: • Custom AI Agents & Enterprise RAG Pipelines • Real-Time Data Streaming & Automated ETL (Kafka/Spark) • FinTech Analytics (<200ms latency, 84% ML accuracy) • Full-Stack & 3D WebGL Visualization Platforms Led by IEEE researchers and NASA award-winning architects. Explore: wearesignalzero.tech
Signal Zero is an integrated AI & systems engineering agency. We architect custom AI agents, enterprise RAG pipelines, real-time data, and fintech platforms.
We engineer intelligent systems that transform raw data into competitive advantage. From custom AI agents to real-time analytics — we build what others can't. Signal Zero creates its own products and helps startups and businesses grow with strong software solutions. We focus on clean design, reliable execution, and friendly communication. Our goal is simple. Build tools that solve real problems and support companies that want to scale with technology. From concept to deployment, we deliver end-to-end solutions across the full technology spectrum. Interactive 3D experiences that captivate users with immersive product visualizations and virtual environments. Custom-built web applications with…from wearesignalzero.tech
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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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Life & fun · 10d ago · louisabraham.github.io
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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