Abstract: Systems, apparatuses, methods, and computer program products are disclosed for user-defined synthetic data generation. A method includes generating, by interface generation circuitry, a synthetic data generation user interface (UI) comprising a plurality of synthetic data generation UI elements. The method also includes causing presentation, by communications hardware, of the synthetic data generation UI. The method also includes receiving, by the communications hardware, a user input set comprising a plurality of user input indications generated based on user interactions with the synthetic data generation UI elements. The method also includes preprocessing, by synthetic data generation circuitry, the user input set to generate a parameter specification set for generating a synthetic dataset.

Abstract: Systems, apparatus, and computer program products are disclosed for generating a verification non-fungible token. An example method includes receiving an event generation request and in response to receiving the event generation request, capturing an asset position and a timestamp. The method further includes performing one or more authentication operations on the event generation request based on the asset identifier and the one or more authentication credentials. The method further includes, in an instance in which the one or more authentication operations authenticates the event generation request, generating the verification non-fungible token for the asset identifier and storing the verification non-fungible token in an associated distributed ledger.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for mitigating deterioration of modeling system performance. An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes determining, by context analysis circuitry and in response to detecting the occurrence of the triggering condition, a destination modeling solution based on a regime strategy for the modeling system. The example method also includes switching, by regime deployment circuitry and based on the regime strategy, from a source modeling solution to a destination modeling solution.

Abstract: An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes scheduling, by context analysis circuitry and based on the occurrence of the triggering condition, retraining of a model. The example method also includes generating, by data grafting circuitry and in response to scheduling the retraining of the model, a context-relevant training data set based on a target context vector. The example method also includes retraining, by model training circuitry, the model using the context-relevant training data set to mitigate deterioration of performance of the model.

Abstract: An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes scheduling, by context analysis circuitry and based on the occurrence of the triggering condition, retraining of a model. The example method also includes generating, by data grafting circuitry and in response to scheduling the retraining of the model, a context-relevant training data set based on a target context vector. The example method also includes retraining, by model training circuitry, the model using the context-relevant training data set to mitigate deterioration of performance of the model.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for two-stage application testing using generative artificial intelligence. An example method includes receiving, by communications hardware, an application and a first context setting and testing, by preliminary testing circuitry, the application using a preliminary testing model. The example method further includes generating, by advanced testing circuitry and using a scenario generation model, one or more first context-based testing scenarios based on the first context setting and testing, by the advanced testing circuitry, the application using an advanced testing model, where the advanced testing model uses the one or more first context-based testing scenarios.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for mitigating deterioration of modeling system performance. An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes determining, by context analysis circuitry and in response to detecting the occurrence of the triggering condition, a destination modeling solution based on a regime strategy for the modeling system. The example method also includes switching, by regime deployment circuitry and based on the regime strategy, from a source modeling solution to a destination modeling solution.

Abstract: Systems, apparatus, and computer program products are disclosed for generating a verification non-fungible token. An example method includes receiving an event generation request and in response to receiving the event generation request, capturing an asset position and a timestamp. The method further includes performing one or more authentication operations on the event generation request based on the asset identifier and the one or more authentication credentials. The method further includes, in an instance in which the one or more authentication operations authenticates the event generation request, generating the verification non-fungible token for the asset identifier and storing the verification non-fungible token in an associated distributed ledger.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for generating one or more candidate event material sets. An example method includes receiving an event material generation request. The example method further includes generating one or more candidate event feature sets and one or more candidate event material sets based on the one or more candidate event feature sets. The method further includes providing the one or more candidate event material sets.