Alexander W Reid

US Patent:

20190179903, Jun 13, 2019

Filed:

Dec 3, 2018

Appl. No.:

16/208488

Inventors:

- Foster City CA, US
Werner Koepf - Seattle WA, US
Siddhartha Reddy Jonnalagadda - Bothell WA, US
James D. Harriger - Duvall WA, US
William Dominic Webb-Purkis - San Francisco CA, US
Macgregor S. Gainor - Bellingham WA, US
Ryan Francis Ginstrom - Snohomish WA, US
Caleb Andrew Bredlow - Kirkland WA, US
Kyle Sargent - Newcastle WA, US
Alexander Carmelo Reid Fordyce - Lynnwood WA, US
Ian McCann - Foster City CA, US

International Classification:

G06F 17/27
G06N 3/00
G06N 3/08
G06N 3/04

Abstract:

Systems and methods for improvements in AI model learning and updating are provided. The model updating may reuse existing business conversations as the training data set. Features within the dataset may be defined and extracted. Models may be selected and parameters for the models defined. Within a distributed computing setting the parameters may be optimized, and the models deployed. The training data may be augmented over time to improve the models. Deep learning models may be employed to improve system accuracy, as can active learning techniques. The models developed and updated may be employed by a response system generally, or may function to enable specific types of AI systems. One such a system may be an AI assistant that is designed to take use cases and objectives, and execute tasks until the objectives are met. Another system capable of leveraging the models includes an automated question answering system utilizing approved answers. Yet another system for utilizing these various classification models is an intent based classification system for action determination. Lastly, it should be noted that any of the above systems may be further enhanced by enabling multiple language analysis.