Burla – Distributed computing framework for AI agents
Hi HN! Would love any thoughts on this, we built Burla to enable anyone, even total beginners to scale Python to thousands of computers in their cloud with zero hassle. In a world of coding agents, this means something different than it used to, specifically that Burla requires almost no cloud permissions to get started. Anyone who has permission to boot a VM in their cloud can simply pip install burla and scale Python to 1000's of VM's. Burla uses your local aws cli credentials to boot VM's and the dashboard runs locally for you to monitor resources and jobs. All together this creates a UX…
What it does
Burla is the world
In the maker’s words, at launch
Hi HN! Would love any thoughts on this, we built Burla to enable anyone, even total beginners to scale Python to thousands of computers in their cloud with zero hassle. In a world of coding agents, this means something different than it used to, specifically that Burla requires almost no cloud permissions to get started. Anyone who has permission to boot a VM in their cloud can simply pip install burla and scale Python to 1000's of VM's. Burla uses your local aws cli credentials to boot VM's and the dashboard runs locally for you to monitor resources and jobs. All together this creates a UX where you can simply ask your agent to do something like "Vector embed all of Wikipedia" and it will do it far faster and with less compute than it would have using any cloud service.
Does the same job
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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 · 16d ago · simedw.com