Karen Kay Myers

US Patent:

20090307162, Dec 10, 2009

Filed:

Jun 1, 2009

Appl. No.:

12/476020

Inventors:

Hung Bui - Mountain View CA, US
Steven Eker - East Palo Alto CA, US
Daniel Elenius - San Mateo CA, US
Melinda Gervasio - Mountain View CA, US
Thomas J. Lee - San Francisco CA, US
Mei Marker - Santa Clara CA, US
David Morley - Camberwell, AU
Janet Murdock - Mountain View CA, US
Karen Myers - Menlo Park CA, US
Bart Peintner - Palo Alto CA, US
Shahin Saadati - Santa Clara CA, US
Eric Yeh - Alameda CA, US
Neil Yorke-Smith - Mountain View CA, US

International Classification:

G06F 15/18
G06F 9/46
G06N 5/02

US Classification:

706 12, 718100, 706 54

Abstract:

The present invention relates to a method and apparatus for assisting with automated task management. In one embodiment, an apparatus for assisting a user in the execution of a task, where the task includes one or more workflows required to accomplish a goal defined by the user, includes a task learner for creating new workflows from user demonstrations, a workflow tracker for identifying and tracking the progress of a current workflow executing on a machine used by the user, a task assistance processor coupled to the workflow tracker, for generating a suggestion based on the progress of the current workflow, and a task executor coupled to the task assistance processor, for manipulating an application on the machine used by the user to carry out the suggestion.

US Patent:

20130311411, Nov 21, 2013

Filed:

Jun 27, 2012

Appl. No.:

13/534155

Inventors:

Rukman Senanayake - San Jose CA, US
Grit Denker - Palo Alto CA, US
Patrick D. Lincoln - Woodside CA, US
Karen Myers - Menlo Park CA, US
Melinda Gervasio - Mountain View CA, US
Thomas J. Lee - San Francisco CA, US

International Classification:

G06F 15/18
G06F 9/45

US Classification:

706 13, 703 22

Abstract:

A device, method and system for monitoring, predicting, and accelerating interactions with a computing device includes determining a current interaction context at a computing device based on interactions occurring at the computing device, predicting a number of potential subsequent interactions, speculatively executing at least some of the potential subsequent interactions, and presenting interactive representations of the speculatively-executed interactions at the computing device.

US Patent:

20200356855, Nov 12, 2020

Filed:

Mar 5, 2020

Appl. No.:

16/810324

Inventors:

- Menlo Park CA, US
Melinda T. Gervasio - Mountain View CA, US
Karen L. Myers - Menlo Park CA, US
Daniel J. Sanchez - Sunnyvale CA, US
Matthew Crossley - San Mateo CA, US

International Classification:

G06N 3/08
G06N 3/04
G06F 40/30

Abstract:

Techniques are disclosed for training a machine learning model to perform actions within an environment. In one example, an input device receives a declarative statement. A computation engine selects, based on the declarative statement, a template that includes a template action performable within the environment. The computation engine generates, based on the template, synthetic training episodes. The computation engine further generates experiential training episodes, each experiential training episode collected by a machine learning model from past actions performed by the machine learning model. Each synthetic training episode and experiential training episode comprises an action and a reward. A machine learning system trains, with the synthetic training episodes and the experiential training episodes, the machine learning model to perform the actions within the environment.