Machine Learning12 min reading time

From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

BAIR Blog
Read full post
Researchers extended the K-Search AI-driven kernel optimization framework to translate CUDA GPU kernels into Apple Silicon's MLX framework, achieving near-expert performance and significant speedups. This approach leverages decades of CUDA expertise to optimize kernels for Apple hardware without rebuilding from scratch.

More in Machine Learning

Machine Learning4 min read

DeepSeek launches V4.1-Flash and retires V4-Pro, its flagship model

The Next Web
Machine Learning3 min read

Nvidia and Palantir fine-tune a 30B Nemotron model for Nvidia’s supply chain. It beats a model 18 times its size.

Covered by 3 sources
Machine Learning6 min read

CoreWeave Puts Field Engineers Inside Customer Teams for Physical AI

Covered by 2 sources