Vega
AI-native research, human-level judgment.
What it does
Vega is an AI-native research platform built on decades of behavioral organizational science. Unlike legacy consulting (slow, expensive) or AI tools alone (no judgment), Vega pairs AI-native depth with senior human judgment — delivering the speed and accuracy today's leaders need. What used to take months of consulting now takes days, backed by a proprietary behavioral science ontology.
Discover Vega by Agency 150: A meaning engine capturing the human voice at scale to surface truth, align leaders, and navigate change with clarity.
The future of your organization is in the hands of stakeholders you don’t fully understand. Vega gives you the insights and the confidence to make the decisions that matter. Agency 150 is an AI-native advisory built to help organizations execute and evolve. Powered by Vega, our proprietary platform for behavioral and organizational research, we give leaders the depth of understanding to see what lies beneath the surface of their employees, members, and customers, so they can act with the clarity and conviction this era demands. Two ways to understand what people think, need, and are ready to do. Scenario: You’re experiencing a drive for AI adoption inside your company. The executive team…from agency150.com
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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