Methods and apparatus of a smart electronic health records platform for veterinarians and human providers are disclosed. The platform integrates clinical IT systems with patient tracking whiteboards, billing processes and artificial intelligence software to increase efficiency of the patient treatment process. By aggregating many services into one platform, interaction and communication between clinics and patients will be enhanced and streamlined.

Methods and apparatus of a smart electronic health records platform for veterinarians and human providers are disclosed. The platform integrates clinical IT systems with patient tracking whiteboards, billing processes and artificial intelligence software to increase efficiency of the patient treatment process. By aggregating many services into one platform, interaction and communication between clinics and patients will be enhanced and streamlined.

Techniques are disclosed for identifying hypocrisy in text. A computer system creates, from fragments of text, a syntactic tree that represents syntactic relationships between words in the fragments. The system identifies, in the syntactic tree, a first entity and a second entity. The system further determines that the first entity is opposite to the second entity. The system further determines a first sentiment score for a first fragment comprising the first entity and a second sentiment score for a second fragment comprising the second entity. The system, responsive to determining that the first sentiment score and the second sentiment score indicate opposite emotions, identifies the text as comprising hypocrisy and providing the text to an external device.

Systems and methods are provided for performing operations including: receiving, by a messaging application, input that selects an option to generate a message using an avatar with a caption; presenting, by the messaging application, the avatar and a caption entry region proximate to the avatar; populating, by the messaging application, the caption entry region with a text string comprising one or more words; determining, by the messaging application, context based on the one or more words in the text string; and modifying, by the messaging application, an expression of the avatar based on the determined context.

A service identifies a level of specificity of one or more identified entities in a user input comprising a query, within one of multiple levels of a hierarchy of a hierarchical coding system. Responsive to determining that additional levels of specificity beyond the identified level of specificity are recommended to return a minimum answer set to the query, the service returns one or more answers requesting one or more additional inputs refining the query based on one or more values identified in a next level. Responsive to determining that no additional levels of specificity beyond the identified level of specificity are recommended to return the minimum answer set to the query, the service returns an answer set comprising a selection of information for the current level of specificity from an ingested corpus of knowledge mapped to the hierarchical coding system.

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Various embodiments, methods and systems for implementing a distributed computing system machine-learning training service are provided. Initially a machine learning model is accessed. A plurality of synthetic data assets are accessed, where a synthetic data asset is associated with asset-variation parameters that are programmable for machine-learning. The machine learning model is retrained using the plurality of synthetic data assets. The machine-learning training service is further configured for executing real-time calls to generate an on-the-fly-generated synthetic data asset such that the on-the-fly-generated synthetic data asset is rendered in real-time to preclude pre-rendering and storing the on-the-fly-generated synthetic data asset. The machine-learning training service further supports hybrid-based machine learning training, where the machine learning model is trained based on a combination of the plurality of synthetic data assets, a plurality of non-synthetic data assets, and synthetic data asset metadata associated with the plurality of synthetic data assets.

A method including receiving, at multiple cloud computing servers, multiple streaming data sets for the same sensing task each from a respective client device. The streaming data set from each client device comprises sensed data sensed by one or more sensors of said client device. The streaming data sets are encrypted. Each respective streaming data set from a respective client device is divided into multiple streaming data set portions, each to be received at a respective one of the cloud computing server. The method also includes processing, at each respective cloud computing server, the corresponding streaming data set portions received to generate a corresponding share of a result for the sensing task. The method also includes encrypting, at each respective one of the cloud computing servers, the corresponding share of the result; and facilitating creation or update of a blockchain based on the encrypted shares of the result.

A method including receiving, at multiple cloud computing servers, multiple streaming data sets for the same sensing task each from a respective client device. The streaming data set from each client device comprises sensed data sensed by one or more sensors of said client device. The streaming data sets are encrypted. Each respective streaming data set from a respective client device is divided into multiple streaming data set portions, each to be received at a respective one of the cloud computing server. The method also includes processing, at each respective cloud computing server, the corresponding streaming data set portions received to generate a corresponding share of a result for the sensing task. The method also includes encrypting, at each respective one of the cloud computing servers, the corresponding share of the result; and facilitating creation or update of a blockchain based on the encrypted shares of the result.