Abstract: Methods and systems are described herein for modifying scheduled events based on bandwidth availability. To modify the scheduled event, the system determines a plurality of user devices corresponding to an event. The system receives first network conditions for a first user device and generates a feature input based on the first network conditions. The system inputs the feature input into an artificial intelligence model to determine a first available bandwidth metric and aggregates the first available bandwidth metric with respective available bandwidth metrics for other user devices of the plurality of user devices to determine a composite available bandwidth metric. The system can compare the composite available bandwidth metric to a threshold available bandwidth metric and in response to determining that the composite available bandwidth metric equals or exceeds the threshold available bandwidth metric, the system generates for display, on a user device interface, a recommendation for modifying the event.

Abstract: In some implementations, a data processing device may receive, from a data source, a set of delimiter-separated values and may divide the set of delimiter-separated values into a plurality of subsets. Each subset may correspond to at least a portion of a column or correspond to at least a portion of a row. The data processing device may generate a plurality of vectors, corresponding to the plurality of subsets, according to an embedding space. The data processing device may compare the plurality of vectors to each other and may select a row or a column of the set of delimiter-separated values as one or more headers based on comparing the plurality of vectors to each other. Accordingly, the data processing device may output a tabular data structure including the one or more headers distinguished from a remainder of the set of delimiter-separated values.

Abstract: Disclosed embodiments include systems and methods for providing a secure physical storage system. The system may receive a request to register a first physical storage box from an entity including location information and security information. The request can be validated by comparing the security information to a predetermined security threshold. The location information associated with the first physical storage box can be recorded to a blockchain. The first registration information can be received from a first user device. The first physical storage box can be assigned to the first user device and a first identity token associated with the first physical storage box. The assignment information associated with the first physical storage box can be recorded to the blockchain. A first identity token can be received from the first user device. Instructions can be transmitted to the first physical storage box to transition from a locked to an unlocked state.

Abstract: A method for object protection identification is provided. The method may: monitor, using a processor, at least one of audio data or history data associated with a user; detect an object replacement triggering event, based on a result of the monitoring; receive user data for a user associated with the at least one of audio data or history data; identify an object corresponding to the object replacement triggering event based on the user data; identify object-related information, the object-related information including at least one of an object protection information or an object replacement information; and transmit the at least one of the object protection information or the object replacement information based on identifying the object-related information.

Abstract: In some implementations, a user device may determine that the user device was granted access to a first set of resources by a first authentication process. The user device may receive a request to access a second set of resources. The user device may generate, based on the request, a token that indicates that the user device was granted access to the first set of resources by the first authentication process. The user device may transmit, based on the request, the token to a server device to cause a second authentication process to be performed on the token. The user device may receive, from the server device, access information indicating whether access to the second set of resources is granted or denied based on transmitting the token to the server device.

Abstract: In some implementations, a server may receive, from a user device, one or more credentials associated with a user. Accordingly, the server may transmit, to the user device, instructions for generating a user interface including a plurality of visual components based on authenticating the user with the one or more credentials. The server may detect, during a first interval, a lack of interaction with the user interface. Accordingly, the server may remove one of the plurality of visual components from the user interface based on the lack of interaction. Additionally, the server may detect, during a second interval, one or more interactions with the user interface and may update a similarity score associated with the user based on properties associated with the one or more interactions. Accordingly, the server may restore the visual component to the user interface based on the updated similarity score satisfying a similarity threshold.

Abstract: Disclosed embodiments may include a system for providing automated bill splitting. The system may receive speech data. The system may identify, from the speech data and using natural language processing, one or more users. The system may determine, from the speech data and using natural language processing, orders of the one or more users. The system may determine, from the speech data and using natural language processing, rules for the orders of the one or more users. The system may process one or more payments for the orders based on the rules and one or more credentials associated with the one or more users.

Abstract: Logic may receive one or more heatmaps captured by one or more user devices associated with a user, wherein each of the one or more heatmaps include data related to wireless communications. The logic may store the one or more heatmaps in a heatmap data structure associated with a user profile for the user. The logic may receive a login attempt with a heatmap, the login attempt associated with the user. The logic may generate a score for the login attempt by comparing the heatmap with the one or more heatmaps stored in a heatmap data structure associated with the user profile for the user. And, in some embodiments, the logic may determine to authenticate the login attempt based on the score.

Abstract: Disclosed embodiments may include a method and system for automated incremental payments. The system may identify recurring charges from historical account data. Based on the recurring charges and an incremental period, the system may calculate an incremental amount and expected amount. At each iteration of the incremental period, the incremental amount may be assigned to a savings bucket. The value of the savings bucket may be subtracted from an actual account balance to calculate a reduced account balance. The system may generate and transmit a graphical user interface to a user device showing the reduced account balance. The system may receive current data containing a charge that corresponds to the recurring charges. The system may reduce the value of the savings bucket by the amount of the current data charge. If the current data charge is different from the expected amount, the system may adjust the incremental amount accordingly.

Abstract: In some implementations, a recording device may obtain a settings configuration associated with deactivating an audio recording function or an audio processing function of the recording device, wherein the settings configuration indicates one or more deactivation events. The recording device may obtain first audio content associated with the recording device for identifying audio prompts associated with causing the recording device to perform one or more actions. The recording device may detect a deactivation event of the one or more deactivation events. The recording device may refrain from obtaining audio content based on detecting the deactivation event and until an activation event is detected. The recording device may obtain second audio content associated with the recording device based on detecting the activation event.

Abstract: In some implementations, a server may receive, from a user device, one or more credentials associated with a user. Accordingly, the server may transmit, to the user device, instructions for generating a user interface including a plurality of visual components based on authenticating the user with the one or more credentials. The server may detect, during a first interval, a lack of interaction with the user interface. Accordingly, the server may remove one of the plurality of visual components from the user interface based on the lack of interaction. Additionally, the server may detect, during a second interval, one or more interactions with the user interface and may update a similarity score associated with the user based on properties associated with the one or more interactions. Accordingly, the server may restore the visual component to the user interface based on the updated similarity score satisfying a similarity threshold.

Abstract: In some aspects, a computing system may generate graph data structures that can be compared with each other to make recommendations. A first graph data structure of the contrasting graphs may be generated based on a first subset of a dataset. For example, the first graph data structure may be generated based on users that have left an organization and graph inference techniques may be used to identify sources that caused the users to leave. A second graph data structure may be generated based on high-performing users of the organization and graph inference techniques may be used to identify potential causes of the users' high performance. The computing system may compare the first and second graph data structures to make recommendations. For example, the computing system may compare the two graphs to determine a modification to make the first graph more similar to the second graph.

Abstract: In some implementations, a data processing device may receive, from a data source, a set of delimiter-separated values and may divide the set of delimiter-separated values into a plurality of subsets. Each subset may correspond to at least a portion of a column or correspond to at least a portion of a row. The data processing device may generate a plurality of vectors, corresponding to the plurality of subsets, according to an embedding space. The data processing device may compare the plurality of vectors to each other and may select a row or a column of the set of delimiter-separated values as one or more headers based on comparing the plurality of vectors to each other. Accordingly, the data processing device may output a tabular data structure including the one or more headers distinguished from a remainder of the set of delimiter-separated values.

Abstract: Systems, methods, and apparatuses for automatically generating reduced training datasets are described. A training dataset may be inputted into a machine learning model to train the machine learning model to output a label. The machine learning model may comprise nodes, and each of the nodes may be associated with a weight. Based on datapoints, changes to the weight associated with each node of the plurality of nodes may be determined. Using model explainability techniques and based on the changes to the weight associated with each node of the plurality of nodes, pathways that decrease an accuracy of the machine learning model are identified. A first set of the datapoints that correlate with pathways that decrease the accuracy of the machine learning model outputting the label may be determined. Furthermore, the first set of the datapoints may be removed from the training dataset to generate a reduced training dataset.

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to orient webpage content based on user attention. The system may determine a user has navigated to a webpage. The system may generate an attention level based on received user feature(s) associated with activity of the user on the webpage. Responsive to determining the attention level exceeds a predetermined threshold, the system may identify a duration associated with the attention level, transmit an offer to one or more entities to submit predetermined content based on the duration, receive predetermined content from the one or more entities, identify, based on a predetermined amount of predetermined content space, selected content of the received predetermined content for placement on the webpage, and cause a GUI of the user device to display the selected content.

Abstract: Systems and methods are disclosed herein for building contextual transcripts. A computing system may receive a textual transcript of a meeting that contains a variety of statements made by various attendees of the meeting, select the first statement made during the meeting, and determine which meeting attendee made the statement. A machine learning model corresponding to the particular attendee that has been trained using previously received statements by the particular attendee may be used on the utterance to determine the tone of the utterance. That tone may be recorded within the transcript and this process may be repeated for each utterance to build a contextual transcript.

Abstract: Disclosed embodiments include systems and methods for providing a secure physical storage system. The system may receive a request to register a first physical storage box from an entity including location information and security information. The request can be validated by comparing the security information to a predetermined security threshold. The location information associated with the first physical storage box can be recorded to a blockchain. The first registration information can be received from a first user device. The first physical storage box can be assigned to the first user device and a first identity token associated with the first physical storage box. The assignment information associated with the first physical storage box can be recorded to the blockchain. A first identity token can be received from the first user device. Instructions can be transmitted to the first physical storage box to transition from a locked to an unlocked state.

Abstract: Disclosed embodiments may include a system for generating custom content. The system may generate a first webpage comprising first feature(s). The system may transmit the first webpage for display via a graphical user interface (GUI) of a user device. The system may iteratively, until a predetermined threshold is achieved: receive data corresponding to a first user; generate, by an encoder, encoded data based on the data; generate, by a decoder, second feature(s) based on the encoded data; modify the first webpage to generate a second webpage comprising the second feature(s); transmit the second webpage for display via the GUI of the user device; receive user feedback associated with the second webpage; and determine whether the user feedback exceeds the predetermined threshold. Responsive to the predetermined threshold being achieved, the system may transmit the latest version of the second webpage without requesting additional user feedback.

Abstract: Systems and methods are disclosed herein for building contextual transcripts. A computing system may receive a textual transcript of a meeting that contains a variety of statements made by various attendees of the meeting, select the first statement made during the meeting, and determine which meeting attendee made the statement. A machine learning model corresponding to the particular attendee that has been trained using previously received statements by the particular attendee may be used on the utterance to determine the tone of the utterance. That tone may be recorded within the transcript and this process may be repeated for each utterance to build a contextual transcript.

Abstract: In some implementations, a device may train the model to generate embeddings for log files associated with an application, and to enable the model to generate embeddings for sensitive information included in a set of training log files. The device may receive a log file associated with the application. The device may generate a compressed log file including a set of embedding vectors associated with records included in the log file, where a record that includes sensitive information is associated with one or more embedding vectors for the sensitive information and one or more embedding vectors for other information included in the record. The device may store the compressed log file including the set of embedding vectors where a size of the compressed file is less than a size of the log file, and the embedding vectors obfuscate the records included in the log file.