i mainly focused on just the things i need: - wisprflow-like UIUX for dictation - youtube transcription & export<p>(it runs on parakeet so only english + european languages are supported)<p>i'm sure there are many other apps already with much wider features (handy is a great example!), but in the spirit of mario (pi creator), "there are many voice transcription apps, but this one is mine."
Dear HN,Wordbird is an open-source voice dictation app for macOS, powered by Nvidia Parakeet running locally on Apple Silicon via MLX. You can teach it project-specific terms like brand names or frameworks using a project-level WORDBIRD.md file.Run it via `uvx wordbird`.Press a hotkey, speak, and your words are transcribed and pasted into whatever app is focused. A small LLM, also running locally, post-processes the transcription to fix errors. If you use apps like VS Code, Zed, Terminal.app or
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whatever generative ai is up to now – week 1i cloned the ml5.js repository (git clone https://github.com/ml5js/ml5-library.git) to understand how a machine learning library designed for creative coding is structured under the hood. ml5 sits on top of TensorFlow.js but wraps complex machine learning workflows into simpler JavaScript functions that artists and designers can use in the browser. looking through the repo, the src/ folder contains the core library code, where different model int
DietPi is a lightweight Debian based Linux distribution for SBCs and server systems, with the option to install desktop environments, too. It ships as minimal image but allows to install complete and ready-to-use software stacks with a set of console based shell dialogs and scripts.The source code is hosted on GitHub: https://github.com/MichaIng/DietPi The main website can be found at: https://dietpi.com/ Wikipedia: https://de.wikipedia.org/wiki&
Hi all, I'm Peter at Staff Engineer and Mozilla.ai and I want to share our idea for a standard for shared agent learning, conceptually it seemed to fit easily in my mental model as a Stack Overflow for agents.The project is trying to see if we can get agents (any agent, any model) to propose 'knowledge units' (KUs) as a standard schema based on gotchas it runs into during use, and proactively query for existing KUs in order to get insights which it can verify and confirm if they p
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