MLX is a lot bigger deal for the machine learning community than most people think. Let’s understand what it is and what it means, and let’s even

Why MLX is Important for the ML Community

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2024-05-07 19:00:09

MLX is a lot bigger deal for the machine learning community than most people think. Let’s understand what it is and what it means, and let’s even get it up-and-running on your Mac.

MLX is a machine learning framework built specifically for Apple Silicon. This gives researchers (including individuals and hobbyists) the ability to train and run machine learning models on their Mac. MLX uses syntax similar to NumPy to make it feel intuitive for anyone already performing computation with Python.

MLX greatly increases the accessibility of machine learning. I know I mention ML accessibility a lot, but isn’t mentioned enough. Accessibility is important from a consumer standpoint so we can get more people using ML in their daily lives, but it’s also important from a research and development standpoint. More ML researchers and engineers is good for everyone.

Up until recently, running ML models locally required a windows PC with a Nvidia graphics card for a proper out-of-the-box solution. I know many researchers who have both a Mac for generally purpose development and a PC specifically for their ML workflows. The necessity of a PC and purpose-built graphics card has created a huge barrier of entry to machine learning, especially for researchers in developing countries. This barrier of entry increases as the demand for Nvidia GPUs increases (think about how hard it was to get one during the crypto boom). Making ML accessible on more hardware (especially hardware many interested in machine learning may already have) is a huge win.