Immersion Corporation

Unanimous A. I., Inc.

Outland Research, LLC

Microscribe, LLC

Google Inc.

Other

Louis B. Rosenberg

Richard B. Gillespie

Bruce M. Schena

Louis B Rosenberg

Bruce M Schena

Adam C Braun

Dean C Chang

Kenneth M Martin

Bernard G Jackson

James R Riegel

Erik James Shahoian

Gregg Willcox

Scott B Brave

Mike D Levin

Jonathan L Beamer

Jeffrey R Mallett

David F Moore

Sian W Tan

Ramon Alarcon

Michael D Levin

Christopher J Hasser

Ryan D Bruneau

JoeBen Bevirt

Evan F Wies

John Q Norwood

Richard B Gillespie

Alex S Goldenberg

Steve P Vassallo

Danny A Grant

Christophe Ramstein

Vincent Hayward

Niccolo Pescetelli

Matthew Mather

David Baltaxe

Hans Schumann

The present disclosure describes systems and methods for enabling real-time conversational dialog among a large population of networked human users while facilitating convergence on groupwise decisions, insight extraction, and solutions, and amplifying collective intelligence. A plurality of computing devices associated with members of a population of participants is provided, wherein the plurality of computing devices is networked via a computer network and in communication with a central server. In some cases, the central server divides the population into a plurality of subgroups and enables an LLM-powered conversational surrogate agent associated with each subgroup. The conversational surrogate agent is configured to repeatedly observe a conversation among members of its assigned subgroup and store content of the conversation to extract insights from the conversation at appropriate intervals. The conversational surrogate agent assesses a numerical measure of conviction, confidence, or scope associated with each unique insight within the conversation, passes the insights and the numerical measure to other subgroups and modulates a strength of the insights based on the numerical measures.

Methods and systems for enabling collective superintelligence

The present disclosure describes systems and methods for enabling real-time conversational dialog among a large population of networked human users while facilitating convergence on groupwise decisions, insights, and solutions, and amplifying collective intelligence. A collaboration server running a collaboration application is provided, wherein the collaboration server is in communication with the plurality of the networked computing devices and each computing device is associated with one user of the population of human participants. In some cases, the collaboration server defines a plurality of sub-groups of human participants. A local chat application configured for displaying a conversational prompt received from the collaboration server is provided on each networked computing device. The local chat application enables real-time communication with other users of a sub-group assigned by the collaboration server. According to some embodiments, the computer mediated collaboration is enabled through communication between the collaboration application and the local chat applications.

Methods and systems for hyperchat and hypervideo conversations across networked human populations with collective intelligence amplification

The present disclosure describes systems and methods for enabling real-time conversational dialog among a large population of networked human users while facilitating convergence on groupwise decisions, insights, and solutions, and amplifying collective intelligence. A collaboration server running a collaboration application is provided, wherein the collaboration server is in communication with the plurality of the networked computing devices and each computing device is associated with one user of the population of human participants. In some cases, the collaboration server defines a plurality of sub-groups of the population of human participants. A local chat application configured for displaying a conversational prompt received from the collaboration server is provided on each networked computing device. The local chat application enables real-time chat communication with other users of a sub-group assigned by the collaboration server. According to some embodiments, the computer mediated collaboration enables through communication between the collaboration application and the local chat applications.

Methods and systems for enabling conversational deliberation across large networked populations

System and method for amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines a score wherein the alignment score indicates how well that participant's prediction aligns with the predictions given by the baseline population. Participants can then be selected from the population based on the participant alignment scores.

Systems and methods for curating an optimized population of networked forecasting participants from a baseline population

Systems and methods for amplifying the intelligence of networked human populations, maximizing the accuracy of collaborative forecasts and group insights. This includes systems and methods for sending and presenting a forecasting query for a future event to a plurality of participants, each using a networked computing device, the forecasting query describing a future event to be collaboratively predicted by the population of human participants. An initial forecast response is collected from each participant and analyzed by a central server. A plurality of unique overlapping subsets of responses are determined by the server. Unique overlapping subsets of unique initial forecast responses are then displayed, at substantially the same time, on each computing device. A second forecast response is collected from each participant and a final forecast is determined.

Hyper-swarm method and system for collaborative forecasting

The present disclosure describes systems and methods for computer-moderated collaborative estimation among a population of human participants using a plurality of networked computing devices. A query (e.g., estimation prompt) may be presented to participants for collecting collaborative responses. The population of users may each set an initial estimation response to the prompt during an initial estimation time period, which is then followed by a collaborative estimation time period (during which all users are asked to produce an updated estimation response to the same prompt). A forbidden deadband region defines an area around each participant's initial estimation that the participant must move their variable slider out of in order for their slider to register as part of the collaborative real-time process. In some embodiments, a participant is not shown initial estimation responses of other participants until the participant has moved their slider out of the forbidden deadband region.

Real-time collaborative slider-swarm with deadbands for amplified collective intelligence

Methods and systems for hyperchat conversations among large networked populations with collective intelligence amplification

Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

System and method for enhanced collaborative forecasting

Systems and methods for amplifying the accuracy of group forecasts and insights through interactive behavioral polling with perturbation analysis. During a first time period the system collects behavioral data of the user interaction with the dynamic user interface and a first displayed prompt, and then performs a perturbation analysis using the data collected during the first time period. A perturbation stimulus is displayed to the user, and during a second time period the user may additionally interact with the dynamic interface during a second time period, during which the system collects behavioral data of the user interaction during the second time period. The system determines a prediction based on data collected during at least one of the time periods from each of a plurality of users.

Interactive behavioral polling for amplified group intelligence

Amplifying group intelligence by adaptive population optimization

Method and system for amplifying collective intelligence using a networked hyper-swarm

System and method of non-linear probabilistic forecasting to foster amplified collective intelligence of networked human groups

Systems and methods for obtaining dynamic behavioral data from a plurality of users of a plurality of computing devices in response to a stimuli, and using the dynamic behavioral data to make an optimized forecast regarding the outcome of a future event. During a first time period the system collects behavioral data of the user interaction with the dynamic user interface and a first displayed prompt, and then performs a perturbation analysis using the data collected during the first time period. A perturbation stimulus is displayed to the user, and during a second time period the user may additionally interact with the dynamic interface during a second time period, during which the system collects behavioral data of the user interaction during the second time period. The system determines a prediction based on data collected during at least one of the time periods from each of a plurality of users.

Interactive behavioral polling and machine learning for amplification of group intelligence

System and method amplifying the accuracy of forecasts generated by software systems that harness the collective intelligence of human populations by curating optimized sub-populations through an intelligent selection process. Participants predict event outcomes and/or provide evaluations of their confidence in their predictions. The system determines an outlier score for each participant based on the participant's responses and the relation of the participant's responses to the predictions of the population as a whole. Participants can then be selected from the population based on the participant outlier scores.

Adaptive population optimization for amplifying the intelligence of crowds and swarms

Method and system for a parallel distributed hyper-swarm for amplifying human intelligence

Growing community of inventors

San Luis Obispo, CA, United States of America

Louis B Rosenberg