Abstract: A method includes storing, by one or more processors of one or more computing devices, a plurality of datasets in a non-transitory computer memory associated with the one or more computing devices. A plurality of index representations is generated where each one of the plurality of index representations includes a compressed representation of a respective one of the plurality of datasets. The plurality of index representations is stored in the non-transitory computer memory. A sample dataset is received by the one or more processors. A sample dataset representation is generated that includes a compressed representation of the sample dataset. A determination that at least one of the plurality of datasets is most similar to the sample dataset based on the sample dataset representation and the plurality of index representations is performed.

Abstract: The present disclosure provides systems for encoding transforms based on intent to be useable by developers. The system receives input datasets, generates output datasets, and identifies characteristics of the input or output datasets. Using these characteristics, the system can encode transforms associated with the datasets based on intent. The system stores and/or associates the intent-encoded transforms in data profiles, so that the system enables the transforms to be searched, recommended, and/or combined.

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: System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.

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: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: Systems as described herein may implement a tunable pre-trained discriminator in a machine learning model, such as a general adversarial network. A server may generate training data using a generator of the machine learning model. The server may send the training data to a first discriminator (e.g., a pre-trained discriminator) and a second discriminator (e.g., an untrained discriminator). The server may receive a first set and a second set of labels from the first discriminator and the second discriminator, respectively. The server may select a label from either the first or the second set of labels. Accordingly, the server may provide the selected labels and the corresponding data records to further train the generator of the machine learning model.

Abstract: A computer-implemented method may include: receiving, from at least one camera, image data associated with a first user at a public access user computing device; detecting, based on the received image data, by employing a machine learning model trained using a dataset of actions collected from a plurality of previous users, that the first user has moved away from the public access user computing device; automatically encrypting, based upon the detection, a user session associated with the first user, wherein the encrypted user session is configured to be subsequently activated by the first user; and initiating a new generic user session on the public access user computing device for a second user.

Abstract: Methods and systems are disclosed herein for using machine learning to send notifications. A computer system may receive a message and may determine a sentiment level and/or an urgency level associated with the message. The computer system may use the sentiment level and/or urgency level to predict when the user will respond to the message. The computer system may compare the predicted response time with one or more thresholds to determine a time to send a notification for the message to the user device.

Abstract: In some implementations, a system may obtain document lineage training data associated with a plurality of historical documents and corresponding lineage data of independent historical documents of the plurality of historical documents. The system may train, based on the document lineage training data, a lineage analysis model to determine a lineage of edited sections of a source document. The system may receive a plurality of document files that correspond to a plurality of versions of a document. The system may determine, using a similarity analysis model, that a first section from a first version of the plurality of versions corresponds to a second section from a second version of the plurality of versions. The system may determine, using the lineage analysis model, a lineage of a corresponding section of the document that is associated with the first section and the second section.

Abstract: Apparatuses, systems and methods are described herein for separately collecting and storing form contents. Different information may be collected from a user on a form. Based on determining that portions of the form request a first type of information, an extended reality (XR) environment may be provided to the user. The user may provide the first type information via an input method in the XR environment. The user may provide a second type of information using a different input method outside of the XR environment. The first type of information may be processed and stored in a different database as compared to the second type of information. The database storing the first type of information may have a higher security standard than the database storing second type of information.

Abstract: Randomizations of a web page may be generated in advance and provided to a client. The client may store the randomizations in its cache. Multiple randomizations for the same web page may be provided to the client and stored in the client's cache. When a request for a web page is made, it is determined if the client has any cached randomizations. Randomizations for the probable next web page to be requested by the client may be provided to the client for storage in the cache. For example, the probability that a link will be clicked or a website visited may be determined. Those web pages and websites with higher probabilities may be determined. Randomizations for those web pages are then provided to the client for use.

Abstract: A device may receive a preauthorization associated with missed transaction prevention for a transaction account of a user, wherein the missed transaction prevention involves preventing a missed transaction associated with merchant accounts of the user. The device may monitor a transaction log of the transaction account and identify a transaction pattern associated with a merchant account based on a plurality of historical transactions identified in the transaction log related to the merchant account. The device may determine that a historical transaction of the plurality of historical transactions is not designated for automatic execution and that an execution of an upcoming transaction corresponding to the plurality of historical transactions is not scheduled. The device may cause an account transaction associated with the upcoming transaction to be automatically executed before a transaction period expiration, associated with the merchant account, passes.

Abstract: Methods and systems described herein relate to the creation of a digital repository of artificial intelligence models that allows users to determine their individual fairness metric. More specifically, the methods and systems provide this digital repository by storing it on a blockchain network and tracking any changes made to the model and/or its fairness metric.

Abstract: In some embodiments, gaze-tracking-based image downscaling for multi-party video communication may be provided. In some embodiments, a set of gaze locations may be received from a set of receiving devices during concurrent video communication sessions between the receiving devices and a sending device. Different collections of positions may be determined based on the gaze locations, and, for each such collection, a spatial indicator (e.g., a bounded region) may be determined. A first downscaled encoding of the source image (from the sending device) may be generated based on the first spatial indicator, and a second downscaled encoding of the source image may be generated based on the second spatial indicator, etc. The downscaled encodings may then be sent to the respective receiving devices during the concurrent video communication sessions.

Abstract: Disclosed herein are system, method, and apparatus for generating labels for k-means clusters. The method includes accessing a plurality of data records from a database repository, and storing the plurality of data records into at least one of primary or secondary memory associated with at least one computer processor performing the method, along with a cluster number for each data record. All data records having a same cluster number form a cluster, and each record has been categorized or designated a cluster number out of a total K number of clusters. The method includes for each of a plurality of classification features, performing cluster-based analysis for a first cluster with respect to a single feature to generate a single feature overlap score. The method includes sorting, grouping, and generating a naming label for the first cluster based on the predetermined number of features having the lowest overlap scores.

Abstract: Systems and methods of procuring real data items based on user affinity gauged via synthetic data items are disclosed. In one embodiment, an exemplary computer-implemented method may comprise: utilizing a trained machine learning model to generate a synthetic data item based on real user data; presenting the synthetic data item to those users; obtaining indications identifying user responses to the synthetic data item; obtaining user-defined control parameters from the users; configuring a user-defined control mechanism to share a portion of the real user data based thereon; obtaining a subset of the real user data based the user-defined control parameters; providing to a particular third-party data source at least one of: data regarding the synthetic data item, the at least one portion of the real user data, and the indications of the users; and then receiving a second real data item from the particular third-party data source.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that provide new capabilities for recommending purchases to a user based on a new descriptor referred to as “purchase embeddings.” The purchase embedding may include a tuple in a new multi-dimensional search space for describing and tracking purchases of goods and services. Recommendations may be based on a distance between tuples in the search space, which provides a measure of similarity between items represented by the tuples.

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: Systems as described herein may label data to preserve privacy. An annotation server may receive a document comprising a collection of text representing a plurality of confidential data from a first computing device. The annotation server may convert the document to a plurality of text embeddings. The annotation server may input the text embeddings into a machine learning model to generate a plurality of synthetic images, and receive a label for each of the plurality of synthetic images from a third-party labeler. Accordingly, the annotation server may send the confidential data and the corresponding labels to a second computing device.