AutoBI
Your autonomous AI agent for Power BI
What it does
AutoBI is an autonomous AI agent for Power BI. Give it a task in natural language and it breaks the work into steps, analyzes your semantic model, generates DAX, builds and modifies reports, and verifies the result. Specialized AI agents work together with shared memory to automate repetitive Power BI workflows—so analysts can spend less time building and more time making decisions
AutoBI is a team of specialist agents that inspects your semantic model, writes and tests the DAX, builds the report, and checks its own work — starting from one sentence. Even experienced developers burn hours on the same repetitive chain of steps for every request. AutoBI collapses that chain into a conversation. A Head Agent plans and delegates. Specialists handle the model, the DAX, and the analysis in parallel, then a Report Agent assembles the dashboard and a QA Agent verifies it before anything reaches you. Not people who like Power BI — people who spend real hours in it every week. Build dashboards and answer business questions through natural language. AutoBI acts as an engineering…from autobi-landing-waitlist.vercel.app
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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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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.
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