Google Inc.

Kinoo, Inc.

University of Nevada

Eyefluence, Inc.

Other

University and Community College System of Nevada

Board of Regents of the Nevada System of Higher Education

Dotslam, Inc.

Nelson George Publicover

Lewis James Marggraff

William C Torch

John Sutko

Spencer James Connaughton

Marc Michael Thomas

Christopher N Spitler

Gholamreza Amayeh

Eliot Francis Drake

Edward D Krent

Alexander Paul Barangan

Mary Jo Marggraff

David Leblanc

Blake Marggraff

David LeBlanc

Ivan Maleev

Peter Milford

Jim Marggraff

Craig A Vincze

Nathan Lord

Dave Le Blanc

Zhiming Liu

Rory Pierce

Michael Vacchina

Jason Heffernan

Josh Larkin

Joshua David Larkin

Angelique Kano

Peter N Milford

Systems and methods are described in which the control of virtual activities is cooperatively shared among two or more interactive users. Within selected virtual actions, an initiation component is identified that, when enacted, automatically informs one or more shared-experience users of the intent by the initiator to complete the virtual action and triggers monitoring of the shared-experience users for indications signaling agreement to proceed. When the degree of agreement meets a predetermined threshold or is judged by the initiator to be adequate, the completion component of the virtual actions is enacted on all devices. Automatic incorporation of initiation and completion components during shared activities may allow for cooperative control of virtual activities without repeated and potentially monotonous questions and responses regarding when to proceed.

Systems and methods to cooperatively perform virtual actions

Systems and methods are described in which the location of a tap on the body of a handheld device is determined in real time using data streams from an embedded inertial measurement unit (IMU). Taps may be generated by striking the handheld device with an object (e.g., a finger), or by moving the handheld device in a manner that causes it to strike another object. IMU accelerometer, gyroscopic and/or orientation (relative to the magnetic and/or gravitational pull of the earth) measurements are examined for signatures that distinguish a tap at a location on the body of the device compared with signal characteristics produced by taps at other locations. Neural network and/or numerical methods may be used to perform such classifications. Tap locations, tap timing and tap attributes such as the magnitude of applied forces, device orientation, and the amplitude and directions of motions during and following a tap, may be used to control or modulate responses within the handheld device and/or actions within connected devices.

Determining tap locations on a handheld electronic device based on inertial measurements

Systems and methods are described to enhance interactive engagement during simultaneous delivery of serial or digital content (e.g., audio, video) to a plurality of users. A machine-based awareness of the context of the content and/or one or more user reactions to the presentation of the content may be used as a basis to interrupt content delivery in order to intersperse a snippet that includes a virtual agent with an awareness of the context(s) of the content and/or the one or more user reactions. This 'contextual virtual agent' (CVA) enacts actions and/or dialog based on the one or more machine-classified contexts coupled with identified interests and/or aspirations of individuals within the group of users. The CVA may also base its activities on a machine-based awareness of 'future' content that has not yet been delivered to the group, but classified by natural language and/or computer vision processing. Interrupting the delivery of content substantially simultaneously to a group of users and initiating dialog regarding content by a CVA enhances opportunities for users to engage with each other about their shared interactive experience.

Systems and methods to enhance interactive engagement with shared content by a contextual virtual agent

Systems and methods are described to enact machine-based, collective control by two individuals of one or more displayed virtual objects. Collective interactions may be implemented by combining an ability to specify one or more locations on a touch-sensitive display using one or more digits of a first user with an ability to monitor a portable, handheld controller manipulated by the other user. Alternatively or in addition, pointing by the first hand to the one or more locations on a display may be enhanced by a stylus or other pointing device. The handheld controller may be tracked within camera-acquired images by following camera-trackable controller components and/or by acquiring measurements from one or more embedded internal measurement units (IMUs). Optionally, one or more switches or sensors may be included within the handheld controller, operable by one or more digits of the second hand to enable alternative virtual object display and/or menu selections during collective interactions.

Systems and methods for collective control of virtual objects

Systems and methods are described to enact machine-based, simultaneous classification of emotional and cognitive states of an individual in substantially real time. A bootstrap approach is used to identify indicators of emotional state, including boredom, engagement and feeling overwhelmed, by finding additional interactions temporally adjacent to known indicators. A similar bootstrap approach is used to identify new indicators of knowledge acquisition (or confusion), by locating frequent temporally adjacent interactions. Systems and methods may enhance teaching by identifying knowledge presentations that result in successful knowledge acquisition, and learning by allowing instructors associated with an individual to track materials that have been understood (or misunderstood). Machine-based tracking of learning may circumvent boredom by avoiding needless repetition, and facilitate teaching of synergistic topics related to materials recently understood. Systems and methods may provide for an enhanced, individualized environment for both emotional and cognitive development.

Systems and methods to measure and enhance human engagement and cognition

Systems and methods to enact machine-based, substantially simultaneous, two-handed interactions with one or more displayed virtual objects. Bimanual interactions may be implemented by combining an ability to specify one or more locations on a touch-sensitive display using one or more digits of a first hand with an ability to monitor a portable, handheld controller manipulated by the other hand. Alternatively or in addition, pointing by the first hand to the one or more locations on a display may be enhanced by a stylus or other pointing device. The handheld controller may be tracked within camera-acquired images by following camera-trackable controller components and/or by acquiring measurements from one or more embedded internal measurement units (IMUs). Optionally, one or more switches or sensors may be included within the handheld controller, operable by one or more digits of the second hand to enable alternative virtual object display and/or menu selections during bimanual interactions.

Systems and methods for bimanual control of virtual objects

Systems and methods are provided to produce electromechanical interconnections within integrated circuits (ICs), printed circuit boards (PCBs) and between PCBs and other electronic components such as resistors, capacitors and integrated circuits. Elements include so-called 'smart pins' or 'neuro-pins' that facilitate electrical pathways in the dimension normal to the plane of a PCB. Smart pins or neuro-pins may be inserted using automated processes that do not require the high temperatures normally associated with soldering. Resultant circuits generally contain a large number of layers that are more compact and more readily constructed compared with conventional PCB-based circuitry.

Method for producing electrical connections

Systems and methods are described for measuring, using one or more cameras, anthropomorphic features of two or more individuals to classify and/or grade whether the two or more individuals possess physical abilities to collectively perform desired physical acts, actions or activities. The performance of such actions may involve objects with measured or known dimensions, and/or one or more assistive devices to compensate for differences in anthropomorphic features. Anthropomorphic features of the two or more individuals may also be projected into the future based on attributes such as ages, medical conditions, activity levels and predispositions. Classification schemes may use neural network-based approaches and/or statistical methods based on labelled datasets of abilities of two or more individuals with given anthropomorphic features to perform selected actions.

Systems and methods to assess abilities of two or more individuals to perform collective physical acts

Systems and methods are described for time-shifting interactions by sharing an artificial intelligence personality (AIP). An AIP is an understanding construct that may control a variety of communication experiences to support a sense of ongoing social connectedness. An AIP may be instantiated within one or more HIEs that interact with humans in a human, cartoon or pet-like manner. HIEs may include robots, robotic pets, toys, simple-to-use devices, and graphical user interfaces. The AIP may be periodically updated based on human interactions sensed by the HIEs as well as knowledge of historical and ongoing events. The systems may provide users with intuitive machine companions that exhibit an expert knowledge base and a familiar, cumulative personality. HIEs may continue to operate without interruption in the presence of telecommunications delays or interruptions, and/or the absence of one or more human participants; allowing participants to 'time-shift' their sense of connectedness.

Systems and methods for time-shifting interactions using a shared artificial intelligence personality

Systems and methods are described for time-sharing interactions using a shared artificial intelligence personality (AIP) incorporated within multiple human interaction entities (HIEs). An AIP is an understanding construct that may control a variety of communication experiences to support a sense of ongoing social connectedness. An AIP may be instantiated within two or more HIEs that interact with humans in a human, cartoon or pet-like manner. HIEs may include robots, robotic pets, toys, simple-to-use devices, and graphical user interfaces. The AIP may be periodically updated based on human interactions sensed by the HIEs as well as knowledge of historical and ongoing events. The systems may provide two or more users with intuitive machine companions that exhibit an expert knowledge base and a familiar, cumulative personality. HIEs may continue to operate without interruption in the presence of interruptions, and/or the absence of one or more human participants; allowing participants to 'time-share' their sense of connectedness.

Systems and methods for time-sharing interactions using a shared artificial intelligence personality

Systems and methods are provided to measure reaction times and/or responses for head, eye, eyelid movements, and/or changes in pupil geometry. The system includes eyewear or headwear including one or more eye-tracking cameras for monitoring the position and geometry of at least one eye and its components of the user, one or more scene cameras for monitoring the user's surroundings, and one or more processors to determine reaction times. Optionally, the system may include one or more of a multi-axis accelerometer to monitor head movements, light sources to trigger visual evoked responses, and/or electronic inputs that may be used to indicate the time of occurrence of external reference events. Measured reaction times and other measurements may be monitored for use in a range of applications. Responses and reaction times may be measured continuously over extended periods, even over a lifetime to measure consequences of the aging process.

Systems and methods for measuring reactions of head, eyes, eyelids and pupils

Systems and methods are described for sharing an artificial intelligence personality (AIP) among multiple human interaction entities (HIEs). An AIP is an understanding construct that interacts with one or more humans in a human- or pet-like manner, implementing a variety of communication experiences to support a sense of ongoing social connectedness. HIEs may include robots, robotic pets, toys, and avatars. The system may be implemented using two or more HIEs and, optionally, one or more remote and/or distributed processors to compute AIPs and sequence telecommunications. AIPs are periodically updated primarily based on human interactions sensed by the two or more HIEs. HIEs may continue to operate without interruption in the presence of significant telecommunications delays. The systems may provide two or more users with intuitive machine companions that exhibit an integrated knowledge base and personality cumulatively acquired from all users.

Systems and methods for sharing an artificial intelligence personality

An electronic system tracks a user's gaze to rapidly transport a cursor to a location within a focal region of the user's eye. The electronic system transports the cursor from an initial location across one or more displays to a new location in response to detecting one or more saccadic and/or vergence movements of the user's eye or in response to a signal indicating that the user desires to move the cursor to a new location within a focal region of the user's eye or eyes. In some embodiments, the electronic system moves the cursor to the new location along a trajectory wherein the cursor is visible along at least a portion of the trajectory, enabling the user to find the cursor more easily.

Eye-signal augmented control

Systems and methods are provided for discerning the intent of a device wearer primarily based on movements of the eyes. The system can be included within unobtrusive headwear that performs eye tracking and controls screen display. The system can also utilize remote eye tracking camera(s), remote displays and/or other ancillary inputs. Screen layout is optimized to facilitate the formation and reliable detection of rapid eye signals. The detection of eye signals is based on tracking physiological movements of the eye that are under voluntary control by the device wearer. The detection of eye signals results in actions that are compatible with wearable computing and a wide range of display devices.

Growing community of inventors

Reno, NV, United States of America

Nelson George Publicover