General Electric Company

Ge Aviation Systems Limited

Varish Vyankatesh Mulwad

Kareem Sherif Aggour

Anna Louise Von Reden

Eric Fluharty

Ethan Winograd

Tao Jing

Peter Henry Tu

Naresh Sundaram Iyer

Paul Edward Cuddihy

Alberto Santamaria-Pang

Andrew Walter Crapo

Nurali Virani

Jenny Marie Weisenberg Williams

Guangliang Zhao

Vijay Shiv Kumar

Luis Babaji Ng Tari

Tianyi Wang

Meinolf Sellmann

Paul E Cuddihy

Ivan Bueno

Vijaya Raghava Mutharaju

A system and method to assist aircraft pilots with rapid decision-making in cases where the pilot needs to make a flight diversion at low altitudes due to an emergency (for example, loss of thrust). Once an emergency need for diversion is detected, the system and method generates a list of alternative airports the plane can reach given: (i) the current conditions of the plane; (ii) a real-emergency time simulation of evolving conditions of the plane; (iii) the environment at potential landing sites; and (iv) the environment on the flight path to those sites. For airports potentially within reach, the system and method provides a confidence scores for successful landings for alternative simulated landing options. The simulations and confidence scores take into account aircraft position, altitude, speed, and possible further problems with the aircraft for the both the current flight path and for each simulated alternative.

Decision-support system for aircraft requiring emergency landings

Briefly, embodiments are directed to a system, method, and article for acquiring a symbol comprising a representation of input data. The symbol may be converted into an emergent language expression in an emergent language via processing of a first neural network. Transmission of the emergent language expression may be initiated over a communications network, where the emergent language comprises a language based on and specific to the input data. The emergent language expression may be translated back into the representation of the input data via processing of a second neural network.

Emergent language based data encryption

A system, method, and computer-readable medium to extract information from at least one of code and text documentation, the extracted information conforming to a base ontology and being extracted in the context of a knowledge graph; add the extracted information to the knowledge graph; generate, in a mixed interaction with a user selectively in communication with the system, computational models including scientific knowledge; and persist, in a memory, a record of the generated computational models.

Method and system for principled approach to scientific knowledge representation, extraction, curation, and utilization

According to some embodiments, a system, method and non-transitory computer-readable medium are provided comprising receiving a node group at an integration module, wherein the node group includes one or more requests for internal data and external data, wherein internal data is data stored in an internal datastore and external data is data stored outside of the internal data store; identifying in a configuration data, one or more meta-data nodes from the node group, wherein each meta-data node indicates a request for external data; retrieving the internal data via execution of an internal data query; determining an order of execution for the one or more meta-data nodes; executing a first meta-data node based on the determined order to generate a first result; ingesting the first result into a semantic datastore; and executing a query to generate a final result, wherein the query includes the retrieved internal data and the ingested first result. Numerous other aspects are provided.

System and method for performing semantically-informed federated queries across a polystore

According to some embodiments, a system and method are provided to extract relationships from unstructured text documents. The method comprises receiving a training set of sentences that comprise labeled objects and subjects for creating an initial relationship model. A set of unlabeled sentences may be received. Objects and subjects from the set of unlabeled sentences are determined based on the initial model and the determined objects and subjects from the set of unlabeled sentences are displayed to a user for feedback and approval. An indication of whether the determined objects and subjects from the set of unlabeled sentences are correct is received and the initial relationship model is updated based on the received indication.

Systems and methods for learning to extract relations from text via user feedback

Display screen or portion thereof with graphical user interface

An apparatus, system and method of providing an artificially intelligent (AI) agent capable of assisting information technology (IT) personnel in addressing an IT ticket. The AI agent may include a visualization interface for display capable of receiving dialog from the IT personnel related to the IT ticket; a translation module capable of translating the received dialog to at least one machine language translation; a solutions module capable of receiving the machine language translation, comparing the machine language to a plurality of prospective solutions for IT issues, and selecting a subset of the plurality of prospective solutions deemed most relevant to the IT ticket and returning that subset to the visualization interface; and a feedback module capable of receiving explicit and implied feedback from the IT personal regarding the machine language translation and the selected subset, wherein the selecting of the subset varies upon subsequent received dialog according to the feedback.

Apparatus, system and method for providing an agent that intelligently solves information technology issues

According to one embodiment, a method for text analysis is provided. The method includes recognizing a concept. Recognizing a concept includes receiving a stream of text including a plurality of entities, and extracting at least one concept from the plurality of entities. The method also includes disambiguating the at least one extracted concept. Disambiguating the at least one extracted concept includes receiving the at least one extracted concept, and generating at least one disambiguated concept corresponding to the at least one extracted concept.

System and method for entity recognition and linking

Growing community of inventors

Glenville, NY, United States of America

Varish Vyankatesh Mulwad