Patents by Inventor Alex Paul Pentland

Alex Paul Pentland 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).

  • Publication number: 20230419038
    Abstract: Described is a system and technique for identifying passages of legal precedent and assembling arguments that use this precedent. In embodiments, passages of judicial precedent are identified by taking advantage of a network of judicial citations. In embodiments, identified passages and relevant context from legal opinions are assembled into a synthetic argument that can be used to identify and/or predict relevant legal precedent. In embodiments, the system and technique may be used identify and/or predict precedent relevant to new arguments. The described the system and technique uses state-of-the-art natural language processing techniques, in particular transformer-based language models trained on a legal corpus, to identify and/or predict precedent relevant to a legal argument.
    Type: Application
    Filed: June 28, 2022
    Publication date: December 28, 2023
    Applicant: Massachusetts Institute of Technology
    Inventors: Robert Zev MAHARI, Alex Paul PENTLAND
  • Patent number: 10992541
    Abstract: In some implementations of this invention, the performance of a network of reinforcement learning agents is maximized by optimizing the communication topology between the agents for the communication of gradients, weights or rewards. For instance, a sparse Erdos-Renyi network may be employed, and network density may be selected in such a way as to maximize reachability and to minimize homogeneity. In some cases, a sparse network topology is employed for massively distributed learning, such as across entire fleets of autonomous vehicles or mobile phones that learn from each other instead of requiring a master to coordinate learning.
    Type: Grant
    Filed: June 1, 2020
    Date of Patent: April 27, 2021
    Assignee: Massachusetts Institute of Technology
    Inventors: Dhaval Adjodah, Alex Paul Pentland, Esteban Moro, Yan Leng, Peter Krafft, Daniel Calacci, Abhimanyu Dubey
  • Publication number: 20200296002
    Abstract: In some implementations of this invention, the performance of a network of reinforcement learning agents is maximized by optimizing the communication topology between the agents for the communication of gradients, weights or rewards. For instance, a sparse Erdos-Renyi network may be employed, and network density may be selected in such a way as to maximize reachability and to minimize homogeneity. In some cases, a sparse network topology is employed for massively distributed learning, such as across entire fleets of autonomous vehicles or mobile phones that learn from each other instead of requiring a master to coordinate learning.
    Type: Application
    Filed: June 1, 2020
    Publication date: September 17, 2020
    Inventors: Dhaval Adjodah, Alex Paul Pentland, Esteban Moro, Yan Leng, Peter Krafft, Daniel Calacci, Abhimanyu Dubey
  • Patent number: 10715395
    Abstract: In some implementations of this invention, the performance of a network of reinforcement learning agents is maximized by optimizing the communication topology between the agents for the communication of gradients, weights or rewards. For instance, a sparse Erdos-Renyi network may be employed, and network density may be selected in such a way as to maximize reachability and to minimize homogeneity. In some cases, a sparse network topology is employed for massively distributed learning, such as across entire fleets of autonomous vehicles or mobile phones that learn from each other instead of requiring a master to coordinate learning.
    Type: Grant
    Filed: November 27, 2018
    Date of Patent: July 14, 2020
    Assignee: Massachusetts Institute of Technology
    Inventors: Dhaval Adjodah, Alex Paul Pentland, Esteban Moro, Yan Leng, Peter Krafft, Daniel Calacci, Abhimanyu Dubey
  • Publication number: 20190166005
    Abstract: In some implementations of this invention, the performance of a network of reinforcement learning agents is maximized by optimizing the communication topology between the agents for the communication of gradients, weights or rewards. For instance, a sparse Erdos-Renyi network may be employed, and network density may be selected in such a way as to maximize reachability and to minimize homogeneity. In some cases, a sparse network topology is employed for massively distributed learning, such as across entire fleets of autonomous vehicles or mobile phones that learn from each other instead of requiring a master to coordinate learning.
    Type: Application
    Filed: November 27, 2018
    Publication date: May 30, 2019
    Inventors: Dhaval Adjodah, Alex Paul Pentland, Esteban Moro, Yan Leng, Peter Krafft, Daniel Calacci, Abhimanyu Dubey
  • Patent number: 9098798
    Abstract: In exemplary implementations of this invention, mobile application (app) installations by users of one or more networks are predicted. Using network data gathered by smartphones, multiple “candidate” graphs (including a call log graph) are calculated. The “candidate” graphs are weighted by an optimization vector and then summed to calculate a composite graph. The composite graph is used to predict the conditional probabilities that the respective users will install an app, depending in part on whether the user's neighbors have previously installed the app. Exogenous factors, such as the app's quality, may be taken into account by creating a virtual candidate graph. The conditional probabilities may be used to select a subset of the users. Signals may be sent to the subset of users, including to recommend an app. Also, the probability of successful “trend ignition” may be predicted from network data.
    Type: Grant
    Filed: May 29, 2012
    Date of Patent: August 4, 2015
    Assignee: Massachusetts Institute of Technology
    Inventors: Wei Pan, Yaniv Altshuler, Alex Paul Pentland, Nadav Aharony
  • Patent number: 8914505
    Abstract: In exemplary implementations of this invention, one or more computer processors receive electronic data indicative of, or compute (i) at least three different topologies of a network and (ii) a level of network performance of a task for each of the different topologies, respectively. The processors also calculate (i) a cascade probability for each of the different topologies, respectively, (ii) a curve indicative of correlation between the cascade probabilities and levels of network performance, and (iii) an optimal cascade probability which optimizes the level of network performance. A topological change in the network is produced (or its likelihood is increased). The topological change makes or would make the cascade probability closer to the optimal cascade probability. The processors output control signals (i) to make the topological change or (ii) to communicate an incentive for the topological change to an electronic node device in the network.
    Type: Grant
    Filed: April 19, 2013
    Date of Patent: December 16, 2014
    Assignee: Massachusetts Institute of Technology
    Inventors: Yaniv Altshuler, Alex Paul Pentland
  • Publication number: 20130297781
    Abstract: In exemplary implementations of this invention, one or more computer processors receive electronic data indicative of, or compute (i) at least three different topologies of a network and (ii) a level of network performance of a task for each of the different topologies, respectively. The processors also calculate (i) a cascade probability for each of the different topologies, respectively, (ii) a curve indicative of correlation between the cascade probabilities and levels of network performance, and (iii) an optimal cascade probability which optimizes the level of network performance. A topological change in the network is produced (or its likelihood is increased). The topological change makes or would make the cascade probability closer to the optimal cascade probability. The processors output control signals (i) to make the topological change or (ii) to communicate an incentive for the topological change to an electronic node device in the network.
    Type: Application
    Filed: April 19, 2013
    Publication date: November 7, 2013
    Inventors: Yaniv Altshuler, Alex Paul Pentland
  • Patent number: 8484035
    Abstract: A method of altering a social signaling characteristic of a speech signal. A statistically large number of speech samples created by different speakers in different tones of voice are evaluated to determine one or more relationships that exist between a selected social signaling characteristic and one or more measurable parameters of the speech samples. An input audio voice signal is then processed in accordance with these relationships to modify one or more of controllable parameters of input audio voice signal to produce a modified output audio voice signal in which said selected social signaling characteristic is modified. In a specific illustrative embodiment, a two-level hidden Markov model is used to identify voiced and unvoiced speech segments and selected controllable characteristics of these speech segments are modified to alter the desired social signaling characteristic.
    Type: Grant
    Filed: September 6, 2007
    Date of Patent: July 9, 2013
    Assignee: Massachusetts Institute of Technology
    Inventor: Alex Paul Pentland
  • Publication number: 20120316933
    Abstract: Disclosed herein are methods and systems for influencing behavior in social settings. The method/system gathers information about the behavior of socially connected entities/individuals, for example, and computes monetary rewards, for example, to distribute to these individuals, thus giving them incentive to adopt a particular behavior. Examples of applications include health insurance, car insurance, power production, weight-loss programs, and public utilities. These methods and systems can be twice as efficient in terms of effect per cost as compared to previous approaches. These methods and systems can improve overall quality of service among computer networks.
    Type: Application
    Filed: June 8, 2012
    Publication date: December 13, 2012
    Applicant: Massachusetts Institute of Technology
    Inventors: Alex Paul Pentland, Iyad Rahwan
  • Publication number: 20120303573
    Abstract: In exemplary implementations of this invention, mobile application (app) installations by users of one or more networks are predicted. Using network data gathered by smartphones, multiple “candidate” graphs (including a call log graph) are calculated. The “candidate” graphs are weighted by an optimization vector and then summed to calculate a composite graph. The composite graph is used to predict the conditional probabilities that the respective users will install an app, depending in part on whether the user's neighbors have previously installed the app. Exogenous factors, such as the app's quality, may be taken into account by creating a virtual candidate graph. The conditional probabilities may be used to select a subset of the users. Signals may be sent to the subset of users, including to recommend an app. Also, the probability of successful “trend ignition” may be predicted from network data.
    Type: Application
    Filed: May 29, 2012
    Publication date: November 29, 2012
    Applicant: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
    Inventors: Wei Pan, Yaniv Altshuler, Alex Paul Pentland, Nadav Aharony
  • Patent number: 7877082
    Abstract: Portable communication devices, such as Bluetooth enabled cellular phones, communicate with and identify like devices that are nearby, and send notification messages to a remote server. When a notification message is received at the server identifying two devices that have come within range of one another, the server compares the profile data associated with each of the two identified devices and facilitates communications between the devices when appropriate.
    Type: Grant
    Filed: May 5, 2005
    Date of Patent: January 25, 2011
    Assignee: Massachusetts Institute of Technology
    Inventors: Nathan Norfleet Eagle, Alex Paul Pentland
  • Patent number: 6757719
    Abstract: Techniques and approaches that facilitate acquisition, transmission or retrieval of data for wearable devices are disclosed. These wearable devices are electronic devices, such as mobile computing devices or wireless communication devices, and are often small in scale and very portable. Wearable devices are able to communicate with one another to exchange information. Wearable devices are also able to exchange information with a portal server. Personal portals can also be provided for users of the wearable devices so that they can easily access information gather by their wearable device and subsequently transmitted to their personal portal.
    Type: Grant
    Filed: April 28, 2000
    Date of Patent: June 29, 2004
    Assignee: Charmed.com, Inc.
    Inventors: Alexander Lightman, Alex Paul Pentland, Thad Starner, Jackson Jarrell Pair, Kenneth Russell, Brian L. Jordan, Russell Eugene Hoffman