Sony Interactive Entertainment Inc.

Sony Interactive Entertainment America LLC

Michael G Taylor

Glenn T Black

Javier Fernandez Rico

Sergey Bashkirov

Todd Tokubo

Dennis Dale Castleman

Jeffrey Roger Stafford

David Perry

Erik Beran

Victor Octav Suba Miura

Steven Osman

Warren M Benedetto

Ruxin Chen

Dominic Saul Mallinson

Andrew Young

Celeste Bean

Sudha Krishnamurthy

Megumi Kikuchi

Javier Fernandez-Rico

Masanori Omote

Jaekwon Yoo

Elliot S Brodzki

Sean Ian Allen

David Sansot

A method for assisting game play. The method includes monitoring game play of the user playing a gaming application, wherein the user has a defined task to accomplish, wherein the task is associated with a task type. The method includes determining a task type proficiency rule for the task type based on results of a plurality of players taking on a plurality of tasks having the task type. The method includes determining a player proficiency score for accomplishing the task based on the task type proficiency rule. The method includes determining a user predictive rate of success in accomplishing the task based on the player proficiency score, the task type proficiency rule, and the task. The method includes determining a recommendation for the user based on the user predictive rate of success.

Automated artificial intelligence (AI) personal assistant

A media system employs techniques to create a framework for evaluating gameplay content in a vector-space. These techniques include monitoring frames for content streams that correspond to gameplay in a game environment, determining feature-values for features associated with the frames, mapping the content streams to position vectors in the vector-space based on the feature-values, and assigning a set of position vectors in the vector-space to an area in the game environment based on a relative proximity of the set of position vectors in the vector-space.

Vector-space framework for evaluating gameplay content in a game environment

A method for dynamically modifying audio playback of a video game is provided. The method includes ascertaining game music data associated with the video game. The game music data may include a plurality of game soundtracks classified according to predetermined criteria. The method may include collecting feedback while the user is playing the video game, the feedback including data associated with the user's performance; an express user action; an evaluation of game results; the user's emotional state; and a user input. The method may continue with determining one or more replacement soundtracks based on criteria associated with the one or more replacement soundtracks. The method may further include dynamically modifying the game music data while the user is playing the video game by replacing at least one of the plurality of game soundtracks with the one or more replacement soundtracks to obtain modified game music data.

Systems and methods for dynamic modification of audio playback with user feedback

A method, system and non-transitory instructions for control input, comprising, taking an integral of an output value from a Motion Decision Neural Network for a movable joint to generate an integrated output value. Generating a subsequent output value using a machine learning algorithm that includes a sensor value and the integrated output value as inputs to the Motion Decision Neural Network and imparting movement with the moveable joint according to an integral of the subsequent output value.

Control input scheme for machine learning in motion control and physics based animation

A controller apparatus includes two or more balls having a size sufficient for a human to manipulate with a single foot. Three or more bearings support at least one of the balls from below and permit rotation with respect to at least two axes. One or more position encoders are disposed proximate a surface of each of the two or more balls. The encoders are configured to determine a rotational displacement of each of the two or more balls with respect to two or more axes.

Dual sphere foot operated position-based controller

A method is provided, including: recording gameplay data from a first session of a video game, the first session defined for interactive gameplay of a user; training a machine learning model using the gameplay data, wherein the training causes the machine learning model to imitate the interactive gameplay of the user; after the training, determining a classification of the machine learning model by exposing the machine learning model to one or more scenarios of the video game, and evaluating actions of the machine learning model in response to the one or more scenarios; and, using the classification of the machine learning model to provide a coaching recommendation to the user.

AI modeling for video game coaching and matchmaking

Systems and methods for receiving a scene by a head mounted display (HMD) of an HMD user. One method includes receiving image data of a real world space where the HMD is located. The image data is analyzed to identify positional data on the one or more spectators present in the real world space. The method includes identifying, based on the positional data, that a personal space of a spectator is being encroached. The identifying causing an indicator to alert the HMD user of said encroachment of said personal space of the spectator.

Delivery of spectator feedback content to virtual reality environments provided by head mounted display

A foot operated controller apparatus is disclosed. The apparatus includes a ball large enough for a human to manipulate with two feet, and a support apparatus configured to support the ball from below, restrict translation of the ball and permit rotation of the ball about its center with respect to at least two axes. One or more position encoders are disposed proximate a surface of the ball. The encoder(s) are configured to determine a rotational displacement of the ball with respect to two or more axes.

Single sphere foot operated position-based controller

A method, system and computer product for training a control input system involve taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value and generating a subsequent output value using a machine learning algorithm that includes a sensor value and a previous joint position if the integrated output value does not at least meet the threshold. Surface damping interactions with at least a simulated environment, a rigid body position and a position of the one or more movable joints based on an integral of the subsequent output value are simulated. The Motion Decision Neural Network is trained with the machine learning algorithm based upon at least a result of the simulation of the simulated environment and position of the one or more movable joints.

Method for robotic training based on randomization of surface damping

Methods for tagging content in a video game title during game play executed on a game cloud system, and social sharing methods. One method includes receiving a pause indication during the game play and suspending the game play to hold the video game title in a current frame image, storing the game state, and receiving the tag data that is associated to a location in the current frame image and to a user identifier for the current frame image. The method further includes generating a video recording of the game play having the tag data and generating a mini-game from a portion of the video game title. The mini-game includes a playable portion to enable view of a portion of the video recording for the mini-game and an executable portion to enable the play of game code for the mini-game that is a portion of the video game title.

Systems and methods for tagging content of shared cloud executed mini-games and tag sharing controls

A warning is generated when a computer simulation controller is determined to have insufficient charge to permit use through an upcoming simulation sequence. Thus, responsive to a computer simulation having a first context and a computer simulation controller having a first voltage, a human-perceptible indication of low voltage is presented, whereas if the computer simulation has a second context typically requiring less input than the first context, no indication is presented if the controller has the same first voltage.

Low battery switchover

Methods and systems are provided for providing real world assistance by a robot utility and interface device (RUID) are provided. A method provides for identifying a position of a user in a physical environment and a surface within the physical environment for projecting an interactive interface. The method also provides for moving to a location within the physical environment based on the position of the user and the surface for projecting the interactive interface. Moreover, the method provides for capturing a plurality of images of the interactive interface while the interactive interface is being interacted with by the use and for determining a selection of an input option made by the user.

Robot utility and interface device

An autonomous personal companion utilizing a method of object identification that relies on a hierarchy of object classifiers for categorizing one or more objects in a scene. The classifier hierarchy is composed of a set of root classifiers trained to recognize objects based on separate generic classes. Each root acts as the parent of a tree of child nodes, where each child node contains a more specific variant of its parent object classifier. The method covers walking the tree in order to classify an object based on more and more specific object features. The system is further comprised of an algorithm designed to minimize the number of object comparisons while allowing the system to concurrently categorize multiple objects in a scene.

Modular hierarchical vision system of an autonomous personal companion

Computer animation involving monocular pose prediction is disclosed. A plurality of candidate pose sequences of a three-dimensional model of an animation character is generated such that each candidate pose of each sequence has a segmentation map that matches a segmentation map of a corresponding character derived from a corresponding frame of a video. A distance between candidate poses at each time step is maximized. An optimum pose sequence is determined and used to generate a corresponding sequence of frames of animation.

Growing community of inventors

San Mateo, CA, United States of America

Michael G Taylor