Patents by Inventor Lascelles Forrester
Lascelles Forrester has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11803772Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.Type: GrantFiled: March 11, 2019Date of Patent: October 31, 2023Assignee: Accenture Global Solutions LimitedInventors: Carl Matthew Dukatz, Daniel Garrison, Lascelles Forrester, Corey Hollenbeck
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Patent number: 10990892Abstract: Methods and systems for a quantum computing approach to solving challenging, e.g., NP-complete, problems in transportation. One of the methods includes (a) ingesting transportation-related data into a graph structure, the transportation-related data being associated with a transportation system; (b) identifying a transportation metric associated with the transportation system; (c) identifying at least one attribute associated with the transportation-related data, where the transportation metric is based at least in part on the attribute; (d) using a quantum computer to derive an operational parameter for the attribute that improves the transportation metric; and (e) applying the operational parameter to the operation of the transportation system.Type: GrantFiled: July 2, 2019Date of Patent: April 27, 2021Assignee: Accenture Global Solutions LimitedInventors: Carl Matthew Dukatz, Sonali Parthasarathy, Srinivas Yelisetty, Lascelles Forrester
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Publication number: 20190325338Abstract: Methods and systems for a quantum computing approach to solving challenging, e.g., NP-complete, problems in transportation. One of the methods includes (a) ingesting transportation-related data into a graph structure, the transportation-related data being associated with a transportation system; (b) identifying a transportation metric associated with the transportation system; (c) identifying at least one attribute associated with the transportation-related data, where the transportation metric is based at least in part on the attribute; (d) using a quantum computer to derive an operational parameter for the attribute that improves the transportation metric; and (e) applying the operational parameter to the operation of the transportation system.Type: ApplicationFiled: July 2, 2019Publication date: October 24, 2019Applicant: Accenture Global Solutions LimitedInventors: Carl Matthew Dukatz, Sonali Parthasarathy, Srinivas Yelisetty, Lascelles Forrester
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Patent number: 10387791Abstract: Methods and systems for a quantum computing approach to solving challenging, e.g., NP-complete, problems in transportation. One of the methods includes (a) ingesting transportation-related data into a graph structure, the transportation-related data being associated with a transportation system; (b) identifying a transportation metric associated with the transportation system; (c) identifying at least one attribute associated with the transportation-related data, where the transportation metric is based at least in part on the attribute; (d) using a quantum computer to derive an operational parameter for the attribute that improves the transportation metric; and (e) applying the operational parameter to the operation of the transportation system.Type: GrantFiled: March 22, 2017Date of Patent: August 20, 2019Assignee: Accenture Global Solutions LimitedInventors: Carl Matthew Dukatz, Sonali Parthasarathy, Srinivas Yelisetty, Lascelles Forrester
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Publication number: 20190205790Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.Type: ApplicationFiled: March 11, 2019Publication date: July 4, 2019Inventors: Carl Matthew Dukatz, Daniel Garrison, Lascelles Forrester, Corey Hollenbeck
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Patent number: 10275721Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.Type: GrantFiled: April 19, 2017Date of Patent: April 30, 2019Assignee: Accenture Global Solutions LimitedInventors: Carl Matthew Dukatz, Daniel Garrison, Lascelles Forrester, Corey Hollenbeck
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Publication number: 20180308000Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.Type: ApplicationFiled: April 19, 2017Publication date: October 25, 2018Inventors: Carl Matthew Dukatz, Daniel Garrison, Lascelles Forrester, Corey Hollenbeck
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Publication number: 20180276994Abstract: Methods and systems for a quantum computing approach to solving challenging, e.g., NP-complete, problems in transportation. One of the methods includes (a) ingesting transportation-related data into a graph structure, the transportation-related data being associated with a transportation system; (b) identifying a transportation metric associated with the transportation system; (c) identifying at least one attribute associated with the transportation-related data, where the transportation metric is based at least in part on the attribute; (d) using a quantum computer to derive an operational parameter for the attribute that improves the transportation metric; and (e) applying the operational parameter to the operation of the transportation system.Type: ApplicationFiled: March 22, 2017Publication date: September 27, 2018Inventors: Carl Matthew Dukatz, Sonali Parthasarathy, Srinivas Yelisetty, Lascelles Forrester