Meta Platforms Technologies, LLC

Meta Platforms, Inc.

Hsien-Hsin Sean Lee

Manan Suri

Ziyun Li

Xuan Zhang

Syed Shakib Sarwar

Liu Ke

Udit Gupta

Carole-Jean Wu

Mark David Hempstead

Brandon Reagen

Vivek Kamalkant Parmar

A console and headset system locally trains machine learning models to perform customized online learning tasks. To customize the online learning models for specific users of the system without using outside resources, the system trains the models to compare a target frame to stored calibration frames, rather than directly inferring information about a target frame. During deployment, an embedding is generated for the target frame. A sample embedding that is closest to the target embedding is selected from a group of embeddings of calibration frames. The information about the selected embedding and target embedding and ground truths for the calibration frame are provided as inputs to one of the trained models. The model predicts a difference between the target frame and the calibration frame, which can be used to determine information about the target frame.

Personalized online learning for artificial reality applications

A device (e.g., an application-specific integrated circuit chip) includes a memory module processing unit and an interface. The memory module processing unit is configured to receive an instruction to obtain values stored in one or more memory components and process the obtained values to return a processed result. The memory module processing unit is also configured to store the obtained values in a cache based on one or more criteria. The memory module processing unit is configured to be included on a computer memory module configured to be installed in a computer system. The interface is configured to communicate with the one or more memory components included on the computer memory module.

Computer memory module processing device with cache storage

Growing community of inventors

Cambridge, MA, United States of America

Hsien-Hsin Sean Lee