Xianzhi Du

In this report we describe the 2025 Apple Foundation Models ("AFM"). We also introduce the new Foundation Models framework, which gives app developers direct access to the on-device AFM model. machinelearning.apple.com/research/apple…

Proud to share our report on AXLearn (github.com/apple/axlearn), the code base for building Apple Foundation Models: arxiv.org/abs/2507.05411.

At WWDC we introduce a new generation of LLMs developed to enhance the Apple Intelligence features. We also introduce the new Foundation Models framework, which gives app developers direct access to the on-device foundation language model. machinelearning.apple.com/research/apple…

As Apple Intelligence is rolling out to our beta users today, we are proud to present a technical report on our Foundation Language Models that power these features on devices and cloud: machinelearning.apple.com/research/apple…. 🧵

Earlier today at #WWDC24, we introduced Apple Intelligence, the personal intelligence system integrated deeply into iPhone, iPad, and Mac, to enable powerful capabilities across language, images, actions, and personal context. We’re excited to share more about how Apple Intelligence models have been built and adapted to perform specialized tasks efficiently, accurately, and responsibly on Apple’s ML Research site: machinelearning.apple.com/research/intro…

Today we present SpineNet, a novel alternative to standard scale-decreased backbone models for visual recognition tasks, which uses reordered network blocks with cross-scale connections to better preserve spatial information. Learn more below: goo.gle/3dNq9fa