Apple Inc.

Matthew S Weaver

Ali Farhadi

Mohammad Rastegari

Hessam Bagherinezhad

Anish Jnyaneshwar Prabhu

Maxwell Christian Horton

Carlo Eduardo Cabanero Del Mundo

Sophie Lebrecht

Daniel Carl Tormoen

Robert Stephen Karl, Jr

Alexander James Oscar Craver Kirchhoff

Peter Zatloukal

Andrew Luke Chronister

Dmitry Belenko

Keith Patrick Wyss

Chenfan Sun

Alexander Kirchhoff

In one embodiment, a method includes providing, to a client system of a user, a user interface for display. The user interface may include a first set of options for selecting an artificial intelligence (AI) task for integrating into a user application, a second set of options for selecting one or more devices on which the user wants to deploy the selected AI task, and a third set of options for selecting one or more performance constraints specific to the selected devices. User specifications may be received based on user selections in the first, second, and third sets of options. A custom AI model may be generated based on the user specifications and sent to the client system of the user for integrating into the user application. The custom AI model once integrated may enable the user application to perform the selected AI task on the selected devices.

Model selection interface

In one embodiment, a method includes receiving a user request from a client device associated with a user, accessing an instructional file comprising one or more binary inference engines and one or more encrypted model data corresponding to the one or more binary inference engines, respectively, selecting a binary inference engine from the one or more binary inference engines in the accessed instructional file based on the user request, sending a validation request for a permission to execute the binary inference engine to a licensing server, receiving the permission from the licensing server, decrypting the encrypted model data corresponding to the binary inference engine by a decryption key, executing the binary inference engine based on the user request and the decrypted model data, and sending one or more execution results responsive to the execution of the binary inference engine to the client device.

Integrating binary inference engines and model data for efficiency of inference tasks

Growing community of inventors

Bellevue, WA, United States of America

Matthew S Weaver