How worried are you about AI taking over music?

This page summarizes the projects mentioned and recommended in the original post on /r/WeAreTheMusicMakers

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  • PyTorch 2,600 contributors

  • fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  • Fairseq 1.1k contributors

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • tensorflow

    An Open Source Machine Learning Framework for Everyone

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  • fastText

    Discontinued Library for fast text representation and classification.

  • fasttext 50

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  • Vue.js

    This is the repo for Vue 2. For Vue 3, go to https://github.com/vuejs/core

  • Vue 356 contributors 202k stars

  • React

    The library for web and native user interfaces.

  • React(also FB) 1.6k contributors 201k stars

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Bootstrap

    The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

  • Bootstrap 1.3k contributors 162k stars

  • ohmyzsh

    🙃 A delightful community-driven (with 2,300+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python, etc), 140+ themes to spice up your morning, and an auto-update tool so that makes it easy to keep up with the latest updates from the community.

  • Ohmyzsh 2.1k contributors 155k stars

  • TheAlgorithms

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  • Python 940 contributors 152k stars

  • Flutter

    Flutter makes it easy and fast to build beautiful apps for mobile and beyond

  • Flutter (Google) 1.1k contributors 150k stars

  • linux

    Linux kernel source tree

  • Linux 18k contributors 146k stars

  • Opus-MT

    Open neural machine translation models and web services

  • Yes, most models these days, except the exceptionally large ones, are possible to train on a laptop. Of course it helps if your laptop has Nvidia CUDA GPU, but even if it doesn't you can rent an AWS 4 core/16GB GPU instance for 0.5 cents an hour. 24 hours of training time would be quite a lot for most models, unless you're trying to train a FB any to any language type model, but typically the big huge models are not the most interesting ones, and you can get very good results, and interesting models with substantially smaller sets of data. Opus MT models are only one language to one language, but they're about 300MB a model, and the quality rivals FB's models, and the speed is substantially faster. I don't have as many examples from the music space, as it's still a fairly under explored area, but Google has released Magenta which is a pretrained Tensorflow music model(actually a group of 3-4 models).

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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