Mary J Swift from San Antonio, TX, age 94

Name / Title

Company / Classification

Phones & Addresses

Mary Jo Swift
Branch Manager

Daughters of Charity Services of San Antonio
Medical Doctor's Office

18555 Leal St, San Antonio, TX 78221
2106261745

Mary Swift
Director

SAVANNAH BLUFF HOMEOWNERS ASSOCIATION, INC
Membership Organization

1600 NE Loop 410 STE 202, San Antonio, TX 78209

Mary Swift
Director

Texas Dental Association
Nonprofit Organization Management · Dentist Membership Organization & Provides Educational Seminars & Publishes A Dental Journal · Trade Association

Austin, TX 78704
1946 S Interstate 35, Austin, TX 78704
5124433675, 5124433031, 8008321145

Mary Swift
Principal

Swift Design Svcs
Business Services

7667 Callaghan Rd, San Antonio, TX 78229

Mary Swift
Director

Paid Dental Inc
Insurance · Marketing Consultant

1946 S I H 35 #300, Austin, TX 78704
1946 S Interstate 35, Austin, TX 78704
5124482132, 5124438112

Real Estate Brokers

Mary Swift, San Antonio TX Agent

view source

Work:

Realty Executives Alamo
San Antonio, TX
2103926361 (Phone)

License Records

Mary Cecile Swift

Address:

14118 Parkhurst, San Antonio, TX 78232

License #:

181935 - Expired

Issued Date:

Jul 3, 2007

Renew Date:

Jul 3, 2007

Expiration Date:

Sep 30, 2009

Type:

Registered Nurse

Mary C Swift

Address:

14118 Parkhurst, San Antonio, TX

Phone:

2104882773

License #:

9224936 - Expired

Category:

Health Care

Issued Date:

Nov 10, 2004

Effective Date:

Aug 2, 2016

Expiration Date:

Jul 31, 2014

Type:

Registered Nurse

Us Patents

Image Dispositioning Using Machine Learning
view source
US Patent:

20220414396, Dec 29, 2022
Filed:

Jun 28, 2021
Appl. No.:

17/359959
Inventors:

- Armonk NY, US
Anne Elizabeth Gattiker - Austin TX, US
Matthew Comer - Austin TX, US
Mary D. Swift - Rochester NY, US
Ambal Balakrishnan - Austin TX, US
Florian Pinel - New York NY, US
International Classification:

G06K 9/62
G06N 3/08
Abstract:

Provided is a method, computer program product, and system for predicting image sharing decisions using machine learning. A processor may receive a set of annotated images and an associated text input from each user of a plurality of users. The processor may train, using the set of annotated images and the associated text input from each user, a neural network model to output an image sharing decision that is specific to a user.

User Interface For A Query Answering System
view source
US Patent:

20180341699, Nov 29, 2018
Filed:

Jul 17, 2018
Appl. No.:

16/038153
Inventors:

- Armonk NY, US
Scott H. Isensee - Austin TX, US
Ashok Kumar - North Chelmsford MA, US
Mark Marrara - Round Rock TX, US
Mary D. Swift - Rochester NY, US
Cale R. Vardy - East York, CA
International Classification:

G06F 17/30
G06F 17/27
Abstract:

A method, system or computer usable program product for utilizing a dialectical model for providing an answer to a user query including applying NLP to the query to generate a first set of NLP structures; generating a contrary set of NLP structures contrary to the user query; evaluating the first set of NLP structures to identify a first set of evidence; evaluating the contrary set of NLP structures to identify a second set of evidence; evaluating a first set of hypotheses from the first set of NLP structures and a contrary set of hypotheses from the contrary set of NLP structures to determine a set of answers to the user query; summarizing the set of answers including indicating derivation thereof; and providing the summarized set of answers to the user.

User Interface For A Query Answering System
view source
US Patent:

20160350406, Dec 1, 2016
Filed:

May 27, 2015
Appl. No.:

14/722830
Inventors:

- Armonk NY, US
Scott H. Isensee - Austin TX, US
Ashok Kumar - North Chelmsford MA, US
Mark Marrara - Round Rock TX, US
Mary D. Swift - Rochester NY, US
Cale R. Vardy - East York, CA
International Classification:

G06F 17/30
G06F 17/28
Abstract:

A method, system or computer usable program product for utilizing a dialectical model for providing an answer to a user query including applying NLP to the query to generate a first set of NLP structures; generating a contrary set of NLP structures contrary to the user query; evaluating the first set of NLP structures to identify a first set of evidence; evaluating the contrary set of NLP structures to identify a second set of evidence; evaluating a first set of hypotheses from the first set of NLP structures and a contrary set of hypotheses from the contrary set of NLP structures to determine a set of answers to the user query; summarizing the set of answers including indicating derivation thereof; and providing the summarized set of answers to the user.