At&t Intellectual Property I, LP

Lauren Savage

Mark D Austin

Abhay Dabholkar

Vijayan Nagarajan

Joshua Whitney

Joshua West

Gary Brian Temerowski, Ii

Martin Patrick McEnroe

Ana Armenta

Edmond J Abrahamian

Surya Murali

Jami Carter Brooks Daly

Aspects of the subject disclosure may include, for example, receiving a plurality of proposed machine learning solutions to a machine learning problem including receiving, for each respective proposed machine learning solution of the plurality of proposed machine learning solutions, one or more of a machine learning model, a dataset and a data pipeline output; automatically determining hybrid solutions to the machine learning problem, including combining, by the processing system, at least one of a first component from a first proposed machine learning solution with at least one of a second component from a second proposed machine learning solution; and ranking the hybrid solutions including determining a log loss score for each hybrid solution and sorting the hybrid solutions according to the log loss score for each hybrid solution. Other embodiments are disclosed.

System, method, and platform for auto machine learning via optimal hybrid AI formulation from crowd

An example method performed by a processing system obtaining a first port-in number for a first mobile device from a first mobile communications service provider, wherein the first port-in number is known to be involved in fraudulent activity, constructing a social graph of communications between the first port-in number and a plurality of other numbers associated with a plurality of other communications devices, identifying, by the processing system, a maximal subgraph of the social graph, wherein the maximal subgraph connects the first port-in number and a subset of the plurality of other numbers that includes those of the plurality of other numbers for which a usage metric is below a predefined threshold for a defined period of time prior to the first port-in number being ported into the first mobile communications service provider, and identifying, by the processing system, a potential fraud ring, based on the maximal subgraph.

Detecting fraud rings in mobile communications networks

A method and apparatus for detecting a photoacoustic light signal to prevent unauthorized voice commands for a microphone-controllable device are provided. The method includes receiving, by a processor, a signal, detecting, by the processor, that the signal is a photoacoustic signal generated by a thermal expansion and contraction of an object caused by at least one lightwave applied to the object, and activating, by the processor, a counter-measure to prevent the photoacoustic signal from reaching a microphone of a microphone-controllable device in response to detecting the photoacoustic signal.

Signal detection system for improved microphone-controllable device security

An example method performed by a processing system includes receiving a request from a user, wherein the request identifies a plurality of items of source content, and wherein the request indicates that the user would like to generate synthesized content from the plurality of items of source content, retrieving, by the processing system, a plurality of sets of permissions, wherein each set of permissions of the plurality of sets of permissions is associated with one item of source content of the plurality of items of source content, determining, by the processing system, whether the request can be satisfied, based on the plurality of sets of permissions, and automatically generating, by the processing system, the synthesized content using the plurality of items of source content, when the request can be satisfied based on the plurality of sets of permissions.

Generating personalized synthesized media

Growing community of inventors

Santa Clara, CA, United States of America

Lauren Savage