Jeffrey Dean Dix

US Patent:

20220391745, Dec 8, 2022

Filed:

Jun 2, 2021

Appl. No.:

17/336573

Inventors:

- Atlanta GA, US
Jeffrey Dix - Rowlett TX, US
Waicheng Moo - Lake Mary FL, US
Hunter Kempf - Dallas TX, US

Assignee:

AT&T Intellectual Property I, L.P. - Atlanta GA
AT&T Mobility II LLC - Atlanta GA

International Classification:

G06N 20/00
G06N 5/04
G06F 11/34

Abstract:

Aspects of the subject disclosure may include, for example, a non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations including selecting modeling logic for an artificial intelligence (AI) model that solves a use case of a plurality of use cases; executing the AI model using holdout data to obtain a sub-result; evaluating the sub-result based on an evaluation metric; and combining the sub-result with other sub-results of the plurality of use cases to determine whether an exit criteria has been met. Other embodiments are disclosed.

US Patent:

20220300259, Sep 22, 2022

Filed:

Jun 8, 2022

Appl. No.:

17/835121

Inventors:

- Atlanta GA, US
Jeffrey Dix - Rowlett TX, US

Assignee:

AT&T Intellectual Property I, L.P. - Atlanta GA

International Classification:

G06F 8/35
G06N 20/00
G06F 8/61
H04L 67/00

Abstract:

Aspects of the subject disclosure may include, for example, a device, including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving user specified metadata for execution tasks associated with a machine learning (ML) model; receiving artifacts specifying program code for implementing the ML model; creating a file system structure for a container to hold the ML model; receiving environment variables for operation of the ML model; and building the container including a model image for the ML model. Other embodiments are disclosed.

US Patent:

20230101955, Mar 30, 2023

Filed:

Sep 27, 2021

Appl. No.:

17/486798

Inventors:

- Atlanta GA, US
Jeremy Fix - Acworth GA, US
Jeffrey Dix - Rowlett TX, US
Eric Zavesky - Austin TX, US
Abhay Dabholkar - Allen TX, US
Rudolph Mappus - Plano TX, US
James Pratt - Round Rock TX, US

International Classification:

G06N 20/00
G06K 9/62

Abstract:

A method performed by a processing system including at least one processor includes defining a proposal for a proposed machine learning model, identifying an existing machine learning model, where the existing machine learning model shares a similarity with the proposed machine learning model, evaluating a fitness of the existing machine learning model for reuse in building the proposed machine learning model, building a new machine learning model that is consistent with the proposal for the proposed machine learning model by reusing a portion of the existing machine learning model, and monitoring a performance of the new machine learning model in a deployment environment.

US Patent:

20210334078, Oct 28, 2021

Filed:

Apr 24, 2020

Appl. No.:

16/858225

Inventors:

- Atlanta GA, US
Jeffrey Dix - Rowlett TX, US

Assignee:

AT&T Intellectual Property I, L.P. - Atlanta GA

International Classification:

G06F 8/35
H04L 29/08
G06F 8/61
G06N 20/00

Abstract:

Aspects of the subject disclosure may include, for example, a device, including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving user specified metadata for execution tasks associated with a machine learning (ML) model; receiving artifacts specifying program code for implementing the ML model; creating a file system structure for a container to hold the ML model; receiving environment variables for operation of the ML model; and building the container including a model image for the ML model. Other embodiments are disclosed.