A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.

A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.

A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.

A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.

Systems and methods for selecting and reporting objects based on events are provided. An indication of first and second objects, an indication of first events associated with the first object, and an indication of second events associated with the second object may be received. Based on the first events, it may be determined to include in a textual content a description based on the first events of the first object. Based on the second events, it may be determined not to include in the textual content any description based on the second events of the second object. Data associated with the first events may be analyzed to generate a particular description of the first object. The textual content including the particular description of the first object and not including any description based on the second events of the second object may be generated and provided.

Systems and methods for selecting and reporting objects based on events are provided. An indication of first and second objects, an indication of first events associated with the first object, and an indication of second events associated with the second object may be received. Based on the first events, it may be determined to include in a textual content a description based on the first events of the first object. Based on the second events, it may be determined not to include in the textual content any description based on the second events of the second object. Data associated with the first events may be analyzed to generate a particular description of the first object. The textual content including the particular description of the first object and not including any description based on the second events of the second object may be generated and provided.

A program generation apparatus includes a generation unit that inputs a specification of a program to be generated described in natural language into a model trained on a relationship between a specification of a program described in natural language and the program to generate a first program, and a change unit that changes the first program to generate a second program satisfying a set of one or more input values and output values, and thus the possibility of a desired program being automatically generated can be increased.

A program generation apparatus includes a generation unit that inputs a specification of a program to be generated described in natural language into a model trained on a relationship between a specification of a program described in natural language and the program to generate a first program, and a change unit that changes the first program to generate a second program satisfying a set of one or more input values and output values, and thus the possibility of a desired program being automatically generated can be increased.

The present disclosure provides a method and a system for expanding vocabulary. The method includes: obtaining a target vocabulary, the target vocabulary including a single word or a phrase composed of two or more words; obtaining at least one candidate text associated with the target vocabulary; determining a plurality of candidate vocabularies from the at least one candidate text, the plurality of candidate vocabularies including words from the at least one candidate text and a phrase formed by at least two consecutive words in position; and determining at least one expansion vocabulary of the target vocabulary from the plurality of candidate vocabularies.