Stephen R Webster

US Patent:

20220179401, Jun 9, 2022

Filed:

Feb 25, 2022

Appl. No.:

17/681652

Inventors:

- Mountain View CA, US
Christopher Gamble - London, GB
Amanda Gasparik - Philadelphia PA, US
Vedavyas Panneershelvam - London, GB
David Barker - Reading, GB
Dustin Reishus - Mountain View CA, US
Abigail Ward - Mountain View CA, US
Jerry Luo - Mountain View CA, US
Brian Kim - Sunnyvale CA, US
Mark Schwabacher - Santa Clara CA, US
Stephen Webster - San Mateo CA, US
Timothy Jason Kieper - Beacon NY, US
Daniel Fuenffinger - Bellevue NE, US
Zakerey Bennett - London, GB

International Classification:

G05B 19/4155
G06N 20/00

Abstract:

Methods, systems, apparatus and computer program products for implementing machine learning within control systems are disclosed. An industrial facility setting slate can be received from a machine learning system and a determination can be made as to whether to adopt the settings in the industrial facility setting slate. The machine learning model can be a neural network, e.g., a deep neural network, that has been trained, e.g., using reinforcement learning to predict a data setting slate that is predicted to optimize an efficiency of a data center.

US Patent:

20200050178, Feb 13, 2020

Filed:

Oct 16, 2019

Appl. No.:

16/654978

Inventors:

- Mountain View CA, US
Christopher Gamble - London, GB
Amanda Gasparik - Philadelphia PA, US
Vedavyas Panneershelvam - London, GB
David Barker - Reading, GB
Dustin Reishus - Mountain View CA, US
Abigail Ward - Mountain View CA, US
Jerry Luo - Mountain View CA, US
Brian Kim - Sunnyvale CA, US
Mark Schwabacher - Santa Clara CA, US
Stephen Webster - San Mateo CA, US
Timothy Jason Kieper - Beacon NY, US
Daniel Fuenffinger - Bellevue NE, US
Zakerey Bennett - London, GB

International Classification:

G05B 19/4155
G06N 20/00

Abstract:

Methods, systems, apparatus and computer program products for implementing machine learning within control systems are disclosed. An industrial facility setting slate can be received from a machine learning system and a determination can be made as to whether to adopt the settings in the industrial facility setting slate. The machine learning model can be a neural network, e.g., a deep neural network, that has been trained, e.g., using reinforcement learning to predict a data setting slate that is predicted to optimize an efficiency of a data center.