CUDA, SHMUDA: RUNNING ALPHAFOLD ON A MACBOOK AIR

Summary from the TLDR AI newsletter

Apple's MLX framework is great for science workloads because it was designed from the ground up to take advantage of Apple's unified memory architecture. Models like AlphaFold are memory-intensive, and almost all protein software is heavily optimized for CUDA. This post shows how a developer got AlphaFold to run on an Apple M chip machine. ARM chips like the Apple M are extremely fast and use only a fraction of the wattage that a single CUDA card needs, and getting a Mac device is a lot easier than getting a Blackwell GPU.