Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: Methods and systems for reducing network traffic between a service and client devices. In some aspects, the system receives a first data stream for a first type of communication between a service and a client device for a user. In response to determining that the first data stream includes an unresolved user query, the system determines that a second type of communication occurred between the service and the user. The system processes a second data stream for the second type of communication to determine that the second type of communication includes the unresolved user query and a service response to the unresolved user query. The system provides the unresolved user query and the service response to update a machine learning model used by the service to generate service responses to one or more user queries during a future communication of the first type.

Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: Methods and systems for reducing network traffic between a service and client devices. In some aspects, the system receives a first data stream for a first type of communication between a service and a client device for a user. In response to determining that the first data stream includes an unresolved user query, the system determines that a second type of communication occurred between the service and the user. The system processes a second data stream for the second type of communication to determine that the second type of communication includes the unresolved user query and a service response to the unresolved user query. The system provides the unresolved user query and the service response to update a machine learning model used by the service to generate service responses to one or more user queries during a future communication of the first type.

Abstract: Systems and methods for verifying digitally secured communications between users are disclosed herein. A first user identifier for a first user may be received. A first blockchain address for the first user based on the first user identifier may be determined. A first non-transferable token corresponding to the first user may be generated. A request for a communication may be received. A target address and a target user identifier may be extracted. Whether the communication metadata matches the token metadata may be determined. A validation status for the communication may be determined.

Abstract: Systems and methods for preventing blockchain functions associated with malicious entities are disclosed herein. A first blockchain status update may be received from a first authorizing entity. A first counter and a first plurality of authorizing entities can be determined. The first counter and the first plurality of authorizing entities can be updated. The first counter can be compared to a consensus threshold. A first instruction to block requests for communications to the first entity address can be generated. A confirmation of the first instruction can be generated for display.

Abstract: Methods and systems for reducing network traffic between a service and client devices. In some aspects, the system receives a first data stream for a first type of communication between a service and a client device for a user. In response to determining that the first data stream includes an unresolved user query, the system determines that a second type of communication occurred between the service and the user. The system processes a second data stream for the second type of communication to determine that the second type of communication includes the unresolved user query and a service response to the unresolved user query. The system provides the unresolved user query and the service response to update a machine learning model used by the service to generate service responses to one or more user queries during a future communication of the first type.

Abstract: In some implementations, a transaction card includes a card body having a first surface and a second surface opposite the first surface, and the card body may be in a configuration that defines a storage area for a physical key. The transaction card may include at least one of an integrated circuit chip or a magnetic stripe accessible from at least one of the first surface or the second surface of the card body. The transaction card may include a connecting element to connect the physical key to the card body. The connecting element may be configured to enable movement of the physical key between a storage position, in which at least a portion of the physical key occupies the storage area, and a use position, in which at least a portion of the physical key is outside of the storage area.

Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: Systems and methods are described for maintaining bifurcated data management while labeling data for artificial intelligence model development. For example, the system may receive a first label for a first sample from a first dataset, wherein the first dataset is accessible to a first subset of a plurality of users, and wherein the first subset comprises a first attribute. The system may receive first version metadata of the first label, wherein the first version metadata comprises a proposed label for the first sample assigned by a first user. The system may determine, based on a first user input from the first user, a first grouping of source code files for storing the first version metadata, wherein the first grouping of source code files is accessible to a second subset of the plurality of users, and wherein the second subset comprises a second attribute.

Abstract: In some implementations, a transaction card includes a card body having a first surface and a second surface opposite the first surface, and the card body may be in a configuration that defines a storage area for a physical key. The transaction card may include at least one of an integrated circuit chip or a magnetic stripe accessible from at least one of the first surface or the second surface of the card body. The transaction card may include a connecting element to connect the physical key to the card body. The connecting element may be configured to enable movement of the physical key between a storage position, in which at least a portion of the physical key occupies the storage area, and a use position, in which at least a portion of the physical key is outside of the storage area.

Abstract: Embodiments relate to enhancing data labeling for machine learning model training using context data. The context data is provided to data labelers to improve accuracy of labels assigned by the data labelers, such as those assigned for ambiguous or unclear target objects. In an example, a system determines and provides context sets for target objects at user devices. The system generates a first training dataset and a second training dataset with labels obtained in connection with a first subset and a second subset of the context sets, respectively. The system trains a first and second instance of a machine learning model on the first training dataset and the second training dataset, respectively, and determines a respective accuracy score for the model instances. If the first instance is more accurate than the second instance, the system generates subsequent context sets based on characteristics of the first subset of context sets.

Abstract: Systems and methods for documenting label versions for machine learning model input datasets are disclosed herein. The system may receive a label modification request for a dataset. The system may determine a dataset identifier and model error indicator. The system may determine a modification timestamp. The system may generate a label record and generate the label record in a label record database.

Abstract: Systems and methods for selecting labels based on dataset similarity for machine learning model training data are disclosed herein. The system may receive a label modification request for a training datum. The system may retrieve label records corresponding to the datum identifier. The system may compare a pre-existing label with the new label. Based on determining that the pre-existing label differs from the new label, the system may generate a first dataset and a second dataset. The system may calculate a first average similarity metric and a second average similarity metric. The system may compare the first average similarity metric with the second average similarity metric. The system may generate a recommendation for a modified label.

Abstract: System and methods for extracting data from and authenticating digital images of documents. The system may receive first digital image data. The system may determine a first image type of the first digital image data. The system may determine a first version identifier based on the first digital image data. The system may determine a first ruleset. The system may determine a first set of pixel coordinate ranges for authenticating digital images. The system may determine a first authentication status for the first digital image. The system may determine a second portion of the first digital image at a second set of pixel coordinate ranges. The system may compare a first portion to the second portion. The system may determine a second ruleset. The system may update the image ruleset database to include the second ruleset.

Abstract: System and methods disclosed herein are for generating labels for dynamically received textual data based on similarity with previously-labeled datasets. The system may receive first textual data. The system may determine a first timestamp at which the first textual data was received. The system may determine a first receipt range for the first textual data based on the first timestamp. The system may retrieve a plurality of datasets. The system may select a first dataset from the plurality of datasets. The system may retrieve second textual data from the first dataset. The system may determine a first similarity metric between the first textual data and the first dataset. The system may compare the first similarity metric to a threshold similarity metric. The system may determine to assign a label for the second textual data to the first textual data.

Abstract: Systems and methods for generating recommendations for unlabelled data for machine learning model training using natural language processing are disclosed herein. The system may receive first text data for a first unlabelled training datum. The system may retrieve textual datasets from a label record database. The system may determine a first dataset that corresponds to a first label record. The system may determine a first plurality of textual data corresponding to the first dataset. The system may compare the first text data and the first plurality of textual data to determine similarity metrics. Based on the similarity metrics, the system may determine the first label record for the first dataset. The system may generate a first recommendation for a first label for the first text data.

Abstract: In some implementations, a transaction card includes a card body having a first surface and a second surface opposite the first surface, and the card body may be in a configuration that defines a storage area for a physical key. The transaction card may include at least one of an integrated circuit chip or a magnetic stripe accessible from at least one of the first surface or the second surface of the card body. The transaction card may include a connecting element to connect the physical key to the card body. The connecting element may be configured to enable movement of the physical key between a storage position, in which at least a portion of the physical key occupies the storage area, and a use position, in which at least a portion of the physical key is outside of the storage area.