Apple's machine learning researcher, Awni Hannun, described MLX Data as a "framework agnostic, efficient, and flexible package for data loading" that works with MLX, PyTorch, or Jax frameworks. Despite Apple's conservative approach to AI, the company has been embedding AI technology into its products for years, focusing on machine learning rather than the generative AI applications pursued by competitors like Microsoft and Google.
Key takeaways:
- Apple has released MLX, a machine learning framework, and MLX Data, a deep learning model library, designed to run efficiently on Apple Silicon and bring generative AI apps to MacBooks.
- Both MLX and MLX Data are available through open-source repositories like GitHub and PyPI, and are inspired by frameworks like PyTorch, Jax, and ArrayFire.
- MLX is designed to be easy for developers to use and powerful enough to train AI models like Meta’s Llama and Stable Diffusion.
- Despite having embedded AI technology into its products for years, Apple has traditionally focused on machine learning rather than the popular generative AI applications pursued by competitors like Microsoft and Google.