Patents by Inventor Michael Hind

Michael Hind 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).

  • Patent number: 12263139
    Abstract: The present invention relates to the use of cannabidiol (CBD) for the treatment of tumours associated with Tuberous Sclerosis Complex (TSC). In particular the CBD was able to decrease the number and size of marker cells, pS6, in a zebrafish model of TSC. This is suggestive of a disease modifying effect whereby treatment with CBD could result in the reduction or prevention of the benign tumours that occur in TSC patients. Preferably the CBD used is in the form of a highly purified extract of cannabis such that the CBD is present at greater than 98% of the total extract (w/w) and the other components of the extract are characterised. In particular the cannabinoid tetrahydrocannabinol (THC) has been substantially removed, to a level of not more than 0.15% (w/w) and the propyl analogue of CBD, cannabidivarin, (CBDV) is present in amounts of up to 1%. Alternatively, the CBD may be a synthetically produced CBD. In use the CBD is given concomitantly with one or more other drugs used in the treatment of TSC.
    Type: Grant
    Filed: January 30, 2023
    Date of Patent: April 1, 2025
    Assignee: JAZZ PHARMACEUTICALS RESEARCH UK LIMITED
    Inventors: Benjamin Whalley, William Hind, Royston Gray, Michael Bazelot, Ines De Silva Serra, Claire Williams, Andrew Tee
  • Publication number: 20250094541
    Abstract: Techniques regarding the governing of use by a consumer of an artificial intelligence technology are described. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include an analyzing component that can, based on an artificial intelligence usage policy, analyze a proposed use by a consumer of an artificial intelligence technology, resulting in an analyzed use of the artificial intelligence technology. The computer executable components can further include a governing component that can, based on the analyzing, govern use by the consumer of the artificial intelligence technology.
    Type: Application
    Filed: September 15, 2023
    Publication date: March 20, 2025
    Inventors: John Thomas Richards, Manish Anand Bhide, Michael Hind, Aleksandra Mojsilovic, Jacquelyn Martino, David John Piorkowski
  • Publication number: 20240362337
    Abstract: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to risk assessment for artificial intelligence models, and more specifically, to the generation of customized risk scores and converted comparable scores. In an embodiment, the customized risk assessment scores can be based on a risk profile determined from risk assessment requirements and measurements of an artificial intelligence model. In another embodiment, one or more customized risk assessment scores can be converted to a converted risk assessment score that is comparable to a customized risk assessment score or another converted risk assessment score.
    Type: Application
    Filed: April 28, 2023
    Publication date: October 31, 2024
    Inventors: Abigail Goldsteen, Michael Hind, Jacquelyn Martino, David John Piorkowski, Orna Raz, John Thomas Richards, Moninder Singh, Marcel Zalmanovici
  • Publication number: 20240330577
    Abstract: Provided are techniques for dynamic fact contextualization in support of AI model development. A template from a plurality of templates is selected, where the template includes definitions for identifying facts. The facts are retrieved from a facts repository based on the definitions. It is determined that that the facts are valid based on one or more policies. A FactSheet is generated using the template and the facts. A machine learning model is used to identify one or more deficient facts from the FactSheet. The FactSheet is displayed in a preview with the one or more deficient facts. One or more facts corresponding to the one or more deficient facts are located. The FactSheet is updated to correct the one or more deficient facts with the corresponding facts.
    Type: Application
    Filed: March 30, 2023
    Publication date: October 3, 2024
    Inventors: John Thomas Richards, Thomas Hampp-Bahnmueller, Michael Hind, David John Piorkowski
  • Patent number: 12056585
    Abstract: A computer implemented method of performing large-scale machine learning experiments includes expanding on one or more input datasets by systematically generating several data set drift splits. A set of experimental jobs corresponding to the generated data set drift splits are executed to generate experimental results. The experimental results are processed, consolidated, and clustered according to the generated data set drift splits.
    Type: Grant
    Filed: December 2, 2020
    Date of Patent: August 6, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Evelyn Duesterwald, Anupama Murthi, Michael Hind, Matthew Richard Arnold, Benjamin Tyler Elder, Jiri Navratil
  • Patent number: 11940978
    Abstract: An example operation may include one or more of generating a plurality of successive data points of an iterative simulation based on predefined checkpoints, each data point identifying an evolving state of the iterative simulation with respect to a previous data point among the successive data points, transmitting a blockchain request for validating state data within a first data point among the plurality of successive data points to a first subset of endorsing nodes of a blockchain network, and transmitting a blockchain request for validating state data within a second data point among the plurality of successive data points to a second subset of endorsing nodes which are mutually exclusive from the first subset of endorsing nodes of the blockchain network for parallel endorsement of the first and second data points.
    Type: Grant
    Filed: September 19, 2018
    Date of Patent: March 26, 2024
    Assignee: International Business Machines Corporation
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K Pissadaki, Nelson K. Bore
  • Publication number: 20240095575
    Abstract: Techniques regarding determining sufficiency of one or more machine learning models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in memory. The computer executable components can comprise a measurement component that measures maximum deviation of a supervised learning model from a reference model over a certification set and an analysis component that determines sufficiency of the supervised learning model based at least in part on the maximum deviation.
    Type: Application
    Filed: September 13, 2022
    Publication date: March 21, 2024
    Inventors: Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush Raj Varshney, Elizabeth Daly, Moninder Singh, Michael Hind
  • Publication number: 20230412360
    Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.
    Type: Application
    Filed: August 29, 2023
    Publication date: December 21, 2023
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson K. Bore
  • Patent number: 11784789
    Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.
    Type: Grant
    Filed: April 30, 2021
    Date of Patent: October 10, 2023
    Assignee: International Business Machines Corporation
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson K. Bore
  • Publication number: 20220172109
    Abstract: A computer implemented method of performing large-scale machine learning experiments includes expanding on one or more input datasets by systematically generating several data set drift splits. A set of experimental jobs corresponding to the generated data set drift splits are executed to generate experimental results. The experimental results are processed, consolidated, and clustered according to the generated data set drift splits.
    Type: Application
    Filed: December 2, 2020
    Publication date: June 2, 2022
    Inventors: Evelyn Duesterwald, Anupama Murthi, Michael Hind, Matthew Richard Arnold, Benjamin Tyler Elder, Jiri Navratil
  • Publication number: 20220121648
    Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.
    Type: Application
    Filed: January 3, 2022
    Publication date: April 21, 2022
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K Pissadaki, Nelson K. Bore
  • Patent number: 11306699
    Abstract: Provided is a method for adjusting a pitch angle of a rotor blade connected to a rotor of a wind turbine, the method includes: pitching the rotor blade towards a target blade pitch angle, the manner of pitching depending on a load on a pitch bearing and/or an azimuthal position of the rotor.
    Type: Grant
    Filed: November 27, 2017
    Date of Patent: April 19, 2022
    Assignee: Siemens Gamesa Renewable Energy A/S
    Inventors: Julian Ehlers, Michael Hind, Drew Eisenberg, Alejandro Gomez Gonzalez, Peder Bay Enevoldsen, Lasse Gilling
  • Patent number: 11263188
    Abstract: A method for automatically generating documentation for an artificial intelligence model includes receiving, by a computing device, an artificial intelligence model. The computing device accesses a model facts policy that indicates data to be collected for artificial intelligence models. The computing device collects artificial intelligence model facts regarding the artificial intelligence model according to the model facts policy. The computing device accesses a factsheet template. The factsheet template provides a schema for an artificial intelligence model factsheet for the artificial intelligence model. The computing device populates the artificial intelligence model factsheet using the factsheet template with the artificial intelligence model facts related to the artificial intelligence model.
    Type: Grant
    Filed: November 1, 2019
    Date of Patent: March 1, 2022
    Assignee: International Business Machines Corporation
    Inventors: Matthew R. Arnold, Rachel K. E. Bellamy, Kaoutar El Maghraoui, Michael Hind, Stephanie Houde, Kalapriya Kannan, Sameep Mehta, Aleksandra Mojsilovic, Ramya Raghavendra, Darrell C. Reimer, John T. Richards, David J. Piorkowski, Jason Tsay, Kush R. Varshney, Manish Kesarwani
  • Patent number: 11212076
    Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.
    Type: Grant
    Filed: September 19, 2018
    Date of Patent: December 28, 2021
    Assignee: International Business Machines Corporation
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K Pissadaki, Nelson K. Bore
  • Publication number: 20210273781
    Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.
    Type: Application
    Filed: April 30, 2021
    Publication date: September 2, 2021
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson K. Bore
  • Patent number: 11032063
    Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.
    Type: Grant
    Filed: September 19, 2018
    Date of Patent: June 8, 2021
    Assignee: International Business Machines Corporation
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K Pissadaki, Nelson K. Bore
  • Publication number: 20210133162
    Abstract: A method for automatically generating documentation for an artificial intelligence model includes receiving, by a computing device, an artificial intelligence model. The computing device accesses a model facts policy that indicates data to be collected for artificial intelligence models. The computing device collects artificial intelligence model facts regarding the artificial intelligence model according to the model facts policy. The computing device accesses a factsheet template. The factsheet template provides a schema for an artificial intelligence model factsheet for the artificial intelligence model. The computing device populates the artificial intelligence model factsheet using the factsheet template with the artificial intelligence model facts related to the artificial intelligence model.
    Type: Application
    Filed: November 1, 2019
    Publication date: May 6, 2021
    Inventors: Matthew R. Arnold, Rachel K.E. Bellamy, Kaoutar El Maghraoui, Michael Hind, Stephanie Houde, Kalapriya Kannan, Sameep Mehta, Aleksandra Mojsilovic, Ramya Raghavendra, Darrell C. Reimer, John T. Richards, David J. Piorkowski, Jason Tsay, Kush R. Varshney, Manish Kesarwani
  • Publication number: 20200092086
    Abstract: An example operation may include one or more of generating a data frame storing content of a simulation, compressing the simulation content within the data frame based on previous simulation content stored in another data frame to generate a compressed data frame, and transmitting the compressed data frame via a blockchain request to one or more endorsing peer nodes of a blockchain network for inclusion of the compressed data frame within a hash-linked chain of blocks of the blockchain network.
    Type: Application
    Filed: September 19, 2018
    Publication date: March 19, 2020
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K Pissadaki, Nelson K. Bore
  • Publication number: 20200092082
    Abstract: An example operation may include one or more of obtaining data of a simulation, identifying checkpoints within the simulation data, generating a plurality of sequential data structures based on the identified checkpoints, where each data structure identifies an evolving state of the simulation with respect to a previous data structure among the sequential data structures, and transmitting the generated sequential data structures to nodes of a blockchain network for inclusion in one or more data blocks within a hash-linked chain of data blocks.
    Type: Application
    Filed: September 19, 2018
    Publication date: March 19, 2020
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson K. Bore
  • Publication number: 20200089791
    Abstract: An example operation may include one or more of generating a plurality of successive data points of an iterative simulation based on predefined checkpoints, each data point identifying an evolving state of the iterative simulation with respect to a previous data point among the successive data points, transmitting a blockchain request for validating state data within a first data point among the plurality of successive data points to a first subset of endorsing nodes of a blockchain network, and transmitting a blockchain request for validating state data within a second data point among the plurality of successive data points to a second subset of endorsing nodes which are mutually exclusive from the first subset of endorsing nodes of the blockchain network for parallel endorsement of the first and second data points.
    Type: Application
    Filed: September 19, 2018
    Publication date: March 19, 2020
    Inventors: Ravi Kiran Raman, Kush R. Varshney, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson K. Bore