Talk: MLX Framework
This presentation covers MLX, Apple’s open-source framework for machine learning on Apple Silicon.
The problem it solves: most ML frameworks were built for NVIDIA GPUs. If you’re on a Mac, you’re often working against the grain. MLX was designed from the ground up for M-series chips, with a unified memory model that lets CPU and GPU share data efficiently.
The API feels familiar if you’ve used NumPy. You can run inference, fine-tune models, and train from scratch - all on-device. On my M2, inference typically completes in under 50 milliseconds.
What makes this interesting beyond the technical details: there are billions of Apple devices out there. MLX opens up a path for applications that process data locally instead of sending everything to cloud APIs. For anything involving private data - medical records, financial documents, personal notes - that matters.