James D Pratt

Address:

5324 Mariners Dr, Plano, TX 75093

VIN:

1FTFW1C61BFA65633

Make:

FORD

Model:

F-150

Year:

2011

US Patent:

8643477, Feb 4, 2014

Filed:

Jun 1, 2009

Appl. No.:

12/476180

Inventors:

Steven M. Belz - Sunnyvale TX, US
James Pratt - Round Rock TX, US

Assignee:

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

International Classification:

G08B 21/00

US Classification:

340 1224, 340 1222, 340 1226, 340 411, 341176, 348734

Abstract:

A method and system for programming a universal remote control (URC) to operate with a remote-controlled device is disclosed. A user may be instructed to operate a control element of an original remote control (ORC) of the remote-controlled device. The control element of the ORC may be operated with consumer-premises equipment of the MCDN, which receives a code associated with the control element. The code may be used to identify the remote-controlled device and obtain corresponding programming codes. The URC may be configured to use at least one of the programming codes to remotely control the remote-controlled device.

US Patent:

20220394338, Dec 8, 2022

Filed:

Jun 8, 2021

Appl. No.:

17/342413

Inventors:

- Atlanta GA, US
Vivek Rajasekharan - Plano TX, US
James Pratt - Round Rock TX, US

International Classification:

H04N 21/466
H04N 21/475
H04N 21/258
H04N 21/458

Abstract:

A processing system may identify a context of a user selection within a content, identify a sequence of known user interactions with the content based on the context, modify the content to include at least one custom selection based on the sequence of known user interactions that is identified, and present the content that is modified to a user.

US Patent:

20220385689, Dec 1, 2022

Filed:

May 25, 2021

Appl. No.:

17/330029

Inventors:

- Atlanta GA, US
Seyed Amir Mir Bagheri - Dallas TX, US
James Pratt - Round Rock TX, US

International Classification:

H04L 29/06
G06N 3/04
G06N 3/08

Abstract:

A processing system may identify a plurality of user interaction data associated with a target category of a plurality of users, identify a relevant subset of user interaction data, compress the plurality of user interaction data to the relevant subset of user interaction data, train a machine learning model with the relevant subset of user interaction data, obtain additional user interaction data associated with an additional user, identify a relevant subset of the additional user interaction data, apply the relevant subset of the additional user interaction data as an input to the machine learning model, obtain an output of the machine learning model quantifying a measure of which the relevant subset of the additional user interaction data is indicative of the target category, and perform at least one action responsive to the measure of which the relevant subset of the additional user interaction data is indicative of the target category.

US Patent:

20220327326, Oct 13, 2022

Filed:

Apr 9, 2021

Appl. No.:

17/226908

Inventors:

- Atlanta GA, US
Mark Austin - Allen TX, US
Prince Paulraj - Coppell TX, US
Ana Armenta - San Jose CA, US
James Pratt - Round Rock TX, US

International Classification:

G06K 9/62
G06N 20/00

Abstract:

An example method includes receiving data to be provided to an application using a scoring model for calculating a score, determining that the data is incompatible with a current feature set of the scoring model applied by the application, receiving a next best model of features in response to the determining that the data is incompatible with the current feature set, executing the application to calculate the score with the data and the features of the next best model, and generating an output in accordance with the score.

US Patent:

20220303306, Sep 22, 2022

Filed:

Mar 16, 2021

Appl. No.:

17/203099

Inventors:

- Atlanta GA, US
Vivek Rajasekharan - Plano TX, US
James Pratt - Round Rock TX, US

International Classification:

H04L 29/06
G06N 20/00
G06N 5/04
G06F 16/955

Abstract:

A processing system may identify a plurality of uniform resource locators associated with a target category of a plurality users of a communication network, identify a plurality of sequences of URLs, each sequence comprising URLs from among the plurality of URLs, each sequence associated with a user known to be of the target category, and train a machine learning model with the plurality of sequences to detect additional sequences that are indicative of the target category. The processing system may next obtain a set of URLs associated with an additional user, identify a sequence comprising URLs, from among the plurality of URLs, that are contained within the set of URLs, apply the sequence as an input to the machine learning model that has been trained, and obtain an output of the machine learning model quantifying a measure of which the sequence is indicative of the target category.

US Patent:

20220292960, Sep 15, 2022

Filed:

May 27, 2022

Appl. No.:

17/826879

Inventors:

- Atlanta GA, US
Sanjiv Singh - Allen TX, US
James Pratt - Round Rock TX, US

Assignee:

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

International Classification:

G08G 1/087
G08G 1/01

Abstract:

A method includes determining that a prioritized vehicle plans to traverse an intersection and receiving sensor data from a plurality of sources in a vicinity of the intersection. The method also includes, based on the sensor data, determining a traffic solution to enable the prioritized vehicle to traverse the intersection, the traffic solution identifying a traffic lane and, based on the traffic solution, controlling a traffic light to cause traffic in the traffic lane to disperse and controlling a second traffic light to instruct traffic in an adjacent traffic lane to stop. The method includes instructing the prioritized vehicle to travel via the traffic lane. The traffic in the traffic lane and the traffic in the adjacent traffic lane are traveling in a same direction.

US Patent:

20230099502, Mar 30, 2023

Filed:

Sep 27, 2021

Appl. No.:

17/486770

Inventors:

- Atlanta GA, US
Cuong Vo - Sachse 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 5/02

Abstract:

A method performed by a processing system including at least one processor includes monitoring interactions of a human user with a platform for building machine learning models, where the human user is using the platform to build a new machine learning model, detecting, within the interactions, an event that triggers a suggestion feature, performing a search of a data source for existing data from existing machine learning models which can be reused to build the new machine learning model, using information about the event, presenting a suggestion to the human user to reuse a portion of the existing data discovered in the search in the new machine learning model, receiving a user feedback in response to the suggestion, and generating an updated suggestion in response to the user feedback.

US Patent:

20210365863, Nov 25, 2021

Filed:

May 22, 2020

Appl. No.:

16/881343

Inventors:

- Atlanta GA, US
Brian Bachman - Grapevine TX, US
James Pratt - Round Rock TX, US

International Classification:

G06Q 10/06
G06Q 30/02

Abstract:

Propensities of entities, comprising human users and virtual assistants (VAs), for various behaviors can be determined and used to facilitate managing interactions between entities. An interaction management component (IMC) can determine an aggregate propensity metric relating to a propensity of an entity to engage in a behavior based on a cross-correlation of respective propensity metrics relating to respective propensities of the entity to engage in respective behaviors. During an interaction between entities, including the entity, IMC can determine an action to perform to interact with the entity based on the aggregate propensity metric and a context determined for the interaction. The action can be one that is predicted to elicit a defined action by the entity in response to the action. During (or after) the interaction, IMC can update behavior attributes, context, and/or aggregate propensity metric associated with the entity based on actions performed during the interaction.