Machine LearningResearch at Apple
Machine Learning
Research at Apple
Research highlights
MLX on Mac with Apple silicon lets AI researchers and developers experiment locally with the latest models and methods in a private environment. The open-source array framework leverages the unified memory architecture of Apple silicon, enabling anyone to run new inference and fine-tuning methods on their own hardware and explore other AI techniques. In a previous post, we highlighted the advantages of the M5 architecture and its GPU Neural Accelerators.
Our next generation of Apple Intelligence is centered around our users, integrated deeply into our operating systems, and powered by a bold new architecture with privacy at its core.
Recent publications
AuthorsAli Benlalah*, Sepehr Johari*, Patricia Vitoria*, Armin Kappeler*, Artem Sevastopolsky, Alexander Jung, Gabriele Fanelli, Kevin Mader, Manuel Breitenstein, Claudia Plüss, Jan Rüegg, Simon Biland, Thomas Etterlin, Dmitry Kostiaev, Mathias Deschler, Brian Amberg, Sebastian Martin
AuthorsMingfei Zhang, Amit Surana, Ziauddin Majid, Chenxi Wang, Michael Xu
Events
Empirical Methods in Natural Language Processing (EMNLP) 2026
October 22, 2026
Apple is presenting new research at the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), taking place October 24–29 in Budapest, Hungary. EMNLP focuses on research surrounding the science and technology of spoken language processing. Below is an overview of Apple’s participation at EMNLP 2026.
Apple is presenting new research at the European Conference on Computer Vision (ECCV), which takes place in Malmö, Sweden, from September 8–12. We are proud to again sponsor the biennial conference, which brings together the scientific and industrial research communities around ML and computer vision. Below is an overview of Apple’s participation at ECCV 2026.
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