Sphairos, Inc.

Zynga Inc.

Foghorn Systems, Inc.

Skyhive Technologies Holdings Inc.

Vizzario, Inc.

Skyhive Technologies Inc.

Peritus.ai, Inc.

Tyco Fire & Security Gmbh

Mohan Reddy

Syed Khizer Rahim Khaderi

Sean Thomas Hinton

Sergey Bukharov

Yuri Yerastov

Kamesh Raghavendra

Thirumalai Muppur Ravi

Jeffrey Zakrzewski

Sastry K M Malladi

Scott D MacGregor

Samuel Lavery

Rahul Kapur

Kyle Christopher McDermott

Rupert Cosulich

Amin Mousavi

Mykhailo Timonin

Vipul Mathur

Sastry Km Malladi

Santhosh Srinivasan

Goutham Shantigodu Tholpadi

Karthik Gooli

Prakash Jagatheesan

Methods and systems for tracking vision performance use various techniques such as and not limited to electrooculography. A modular device is integrated with frames of eyeglasses that can be worn by a user. The device incorporates one or more biosensors such as EOG sensors. EOG recording may be used to estimate eyelid and eye motion, and eye gaze direction. The modular device may be fitted into new eyewear or retrofitted into existing eyewear for tracking eyes of the wearer. Systems and methods enable seamless integration of eye tracking into everyday life to maximize productivity and performance.

Modular display and sensor system for attaching to eyeglass frames and capturing physiological data

A method comprises obtaining a hypernym tree for a word selected from each skill name of a plurality of skill names, the obtained hypernym tree including a node for each meaning of the word, each node of an obtained hypernym tree for a meaning of a word including one or more synonyms corresponding to the meaning and a summary description of the meaning, at least one hypernym tree including nodes for meanings of different words; creating an embedding for each skill name and for each synonym and the summary description included in a node of each obtained hypernym tree computing, a distance between the embedding for a skill name and the embedding for each synonym and summary description included in a node of an obtained hypernym tree; assigning to the skill name a meaning of a word associated with a node of any obtained hypernym tree that leads to a lowest distance.

Generating skill data through machine learning

The present specification describes methods and systems for modifying a media, such as Virtual Reality, Augmented Reality, or Mixed Reality (VR/AR/MxR) media based on a vision profile and a target application. In embodiments of the specification, a Sensory Data Exchange (SDE) is created that enables identification of various vision profiles for users and user groups. The SDE may be utilized to modify one or more media in accordance with each type of user and/or user group.

Methods and systems for obtaining, aggregating, and analyzing vision data to assess a person's vision performance

Techniques are described for automatically generating job descriptions. Training data is used to define job categories, job sections, and selective phrases for each job category and job section. In response to receiving request to generate a job description, a job category or additional information is derived from the request. Such information is used to populate existing templates for a job description based on a skill knowledge graph, which connects skill names based on hypernym trees and enables enhancement of a job description with better or broader coverage.

Job description generation based on machine learning

A method for enabling intelligence at the edge. Features include: triggering by sensor data in a software layer hosted on either a gateway device or an embedded system. Software layer is connected to a local-area network. A repository of services, applications, and data processing engines is made accessible by the software layer. Matching the sensor data with semantic descriptions of occurrence of specific conditions through an expression language made available by the software layer. Automatic discovery of pattern events by continuously executing expressions. Intelligently composing services and applications across the gateway device and embedded systems across the network managed by the software layer for chaining applications and analytics expressions. Optimizing the layout of the applications and analytics based on resource availability. Monitoring the health of the software layer. Storing of raw sensor data or results of expressions in a local time-series database or cloud storage.

Edge computing platform

A data management server computer ('server') and related methods are disclosed to enhance electronic documents or search processes related to skill data, including skill names, using machine learning techniques. The server is programmed to organize skill names from a dictionary into a knowledge graph. The knowledge graph includes nodes that represent the skill names and words of the skill names and edges that represent syntactic or semantic relationships. The server is programmed to respond to skill-related requests using the knowledge graph and track access patterns of the knowledge graph in responding to the requests. The replies to the request can be generated based on the structure or access patterns of the knowledge graph and used as search results or skill-related data, such as resumes or job descriptions.

The present specification describes methods and systems for tracking vision performance, using various techniques such as and not limited to electrooculography. A modular device is integrated with frames of eyeglasses that can be worn by a user. The device incorporates one or more biosensors such as EOG sensors. EOG recording may be used to estimate eyelid and eye motion, and eye gaze direction. The modular device may be fitted into new eyewear or retrofitted into existing eyewear for tracking eyes of the wearer. Embodiments of the present specification provide systems and methods to enable seamless integration of eye tracking into everyday life to maximize productivity and performance.

Techniques are described for automatically generating job descriptions. Job categories are identified for the documents in the job description dataset based on clustering the documents. Sections within each document in the job description dataset are automatically identified, and each identified section is automatically classified. Each type of section is analyzed independently of the other section types using natural language processing, which allows automatic generation of each section of a new job description based on the section-specific data derived from the dataset. Section- and category-specific selective phrases are identified within the job description dataset, and embeddings are generated for the identified selective phrases. A request to generate a new job description for a particular category is received. For each section of new job description, the selective phrase embeddings for the section and for the identified category are used to identify phrases to include within the section of the job description.

A method for enabling intelligence at the edge. Features include: triggering by sensor data in a software layer hosted on either a gateway device or an embedded system. Software layer is connected to a local-area network. A repository of services, applications, and data processing engines is made accessible by the software layer. Matching the sensor data with semantic descriptions of occurrence of specific conditions through an expression language made available by the software layer. Automatic discovery of pattern events by continuously executing expressions. Intelligently composing services and applications across the gateway device and embedded systems across the network managed by the software layer for chaining applications and analytics expressions. Optimizing the layout of the applications and analytics based on resource availability. Monitoring the health of the software layer. Storing of raw sensor data or results of expressions in a local time-series database or cloud storage. Services and components can be containerized to ensure smooth running in any gateway environment.

A system, a non-transitory machine-readable storage medium storing instructions, and a computer-implemented method to provide efficient game access is described. A request to access a first game using a first primary identifier is received. An internal identifier and a game identifier associated with the first primary identifier are accessed. A request to access a second game using a second primary identifier is received. An internal identifier and a game identifier associated with the second primary identifier are accessed. A determination that the first and second primary identifiers are associated with a particular player is made. An association between the internal identifiers is stored.

Systems and methods for providing efficient game access

A system operation management server computer (server), agent computer (agent), and related methods are disclosed to configure and manage the operation of systems in a system category. In some embodiments, the server and a plurality of agents are programmed to collaborate on exploring and improving the operation of systems in a system category through reinforcement learning.

Automatic configuration and operation of complex systems

A system operation management server computer (server) and related methods are disclosed. The server is programmed to learn the features of and relations among computer devices from various types of data related to the computer devices and build a knowledge graph (KG) to represent IT infrastructure. The server is also programmed to manage a collection of issue resolution rules each mapping the states of certain computer devices that characterize a known issue and a known resolution of the known issue. In response to receiving a support bundle that contains data related to a target computer system that has encountered an unknown issue the server is programmed to determine which issue resolution rules are applicable to the support bundle based on the KG and transmit a recommendation for resolving the unknown issue.

Growing community of inventors

Fremont, CA, United States of America

Mohan Reddy