Abstract: Techniques to apply machine learning to schedule events of interest for a device user. As described herein, a typical device user is inundated with information suggesting activities and other things to do. Using these techniques, the information is categorized according to the activity and those activities that are most likely to be engaged in by the device user are recommended to the device user (via their device) as events of interest. If the device user selects an event of interest, the device is updated to reflect that selection. For instance, a calendar application may be updated to include an event description at the event's date and time. Other embodiments are described and claimed.

Abstract: Genetic modeling is used to generate new term sets from existing term sets within a population cluster. Term attributes corresponding to a first plurality of term sets are encoded as genes for a computer-executed genetic algorithm. Clients are clustered in categories based on client attributes. The genetics algorithm is applied to a category of clustered clients to distribute the term sets to clients in the category. A first subset of terms sets is removed after receiving, within a first duration of time, a number of client responses that falls below a first threshold. A second subset of term sets is retained after receiving, within a second duration of time, a number of client responses above a second threshold. The second subset is bred using the genetic algorithm and a second plurality of term sets is generated based on the results.

Abstract: Aspects described herein may allow for receiving authorization allowing monitoring a user's spending account. A base-line spending profile and a dysfunctional spending profile for the user may be established. When notification of a pending purchase transaction is received, a determination may be made as to whether the pending purchase transaction is in accordance with the base-line spending profile of the user. If the pending purchase transaction is in accordance with the base-line spending profile of the user, the pending purchase transaction may be allowed. However, if the pending purchase transaction is not in accordance with the base-line spending profile of the user, then a temporary secondary approval may be instituted for a predetermined period of time and a secondary approval person may be electronically notified that their approval is required before allowing the pending purchase transaction to be made using the spending account of the user.

Abstract: Techniques for providing a real-time service that protects personal data of clients from customer service agents are provided. Customer data that includes personal data indicative of sensitive information of a customer can be received from the customer. The personal data within the received customer data can be detected and a token that does not include the sensitive information of the customer can be generated. The personal data and the generated token can be stored along with data indicating a relationship between the token and the personal data. The personal data in the received customer data can be replaced by the token to form modified customer data. The modified customer data can be provided to a customer service representative. The token within the modified customer data can later be detected and associated with the personal data without revealing the personal data to the customer service representative.

Abstract: Systems and methods for generating synthetic video are disclosed. For example, a system may include a memory unit and a processor configured to execute the instructions to perform operations. The operations may include receiving video data, normalizing image frames, generating difference images, and generating an image sequence generator model. The operations may include training an autoencoder model using difference images, the autoencoder comprising an encoder model and a decoder model. The operations may include identifying a seed image frame and generating a seed difference image from the seed image frame. The operations may include generating, by the image sequence generator model, synthetic difference images based on the seed difference image. In some aspects, the operations may include using the decoder model to synthetic normalized image frames from the synthetic difference images. The operations may include generating synthetic video by adding background to the synthetic normalized image frames.

Abstract: Systems and methods for authenticating a user to access a public terminal are described. Disclosed embodiments may include reading, using the physical credential reader, a user identifier from the physical credential device. Disclosed embodiments may also include transmitting the public terminal identifier and the user identifier to a secure server. Further, disclosed embodiments may include receiving, after completing the transmission, a unique code from the secure server. Disclose embodiments may additionally include displaying the unique code on the display device. Disclosed embodiments may include receiving, after displaying the unique code, an authentication message from the secure server. Disclosed embodiments may further include, responsive to receiving the authentication message, authorizing the user to use a terminal command at the public terminal.

Abstract: Techniques and apparatus for providing peer-based management of user accounts are described. In one embodiment, for example, an apparatus may include at least one memory and logic coupled to the at least one memory. The logic may be configured to receive a request from at least one first user account to unlock a second user account locked responsive to a fraud event, determine a safe authentication value for the fraud event, and unlock the second user account responsive to the at least one first user account being a safe authentication account and the safe authentication value being over a safe authentication threshold value. Other embodiments are described.

Abstract: Systems, methods, and computer-readable storage media for ensuring electronic communications have not been intercepted and manipulated. An exemplary device generates a public/private pair of keys, and transmits the public key to another device with information about the data to be shared. The second device encrypts associated data, while also executing a hash function on at least a portion of the data. The first device receives the encrypted data, decrypts it, and verifies its accuracy using a third party. The third party also executes the hash function on the data received from the first device, and transmits the output of that hash function to the first device. Both the first device and second devices and display the hash values, allowing users to visually determine if the data has been manipulated during the transaction.

Abstract: A server device may receive information identifying a user of a first device participating in a screen sharing session with a second device and associate the information identifying the user of the first device with information indicating a sequence of interactions with an application at the first device. The server device may determine one or more user interface elements that correspond to a current view of the application at the first device based on the sequence of interactions, and transmit, to the second device, information identifying the one or more user interface elements that correspond to the current view to permit the second device to reconstruct the current view based on the information identifying the one or more user interface elements that correspond to the current view and stored information related to a plurality of views associated with the application.

Abstract: A method for generating a dual-class dataset is disclosed. A single-class dataset and a context dataset are obtained. The context dataset can be labeled. A model can be trained using the combination of the single-class dataset and the labeled context dataset. The model can be run on the context dataset. The data points that are classified the same as the data points included in the single-class dataset, can be removed from the labeled context dataset and added to the single-class dataset. These steps can be repeated until no data points are classified by the model.

Abstract: Embodiments of the present disclosure provide a device, system, methods and components related to a modular card. Example components of the modular card include a thin rectangular rear plate, a thin rectangular front plate overlying the rear plate, a first plurality of fasteners fixed to the thin rectangular front plate, a second plurality of fasteners fixed to the thin rectangular rear plate, the second plurality of fasteners being configured to be removably engaged with the first plurality of fasteners; a magnetic strip, and/or an integrated circuit. In operation a user may remove and/or replace various components to customize the modular card. Some customizations include altering the accounts to which the modular card relates. In some example, the modular card may include components which relate to different accounts.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent plurality of colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors. A matrix barcode may be generated based on the most prevalent colors, the related plurality of colors, an infrared layer, and an ultraviolet layer.

Abstract: An error notification system includes a plurality of data production systems in communication with a monitoring server. Each data production system has a data processor configured to receive input data from a first set of data production systems, process the input data to produce output data, and make the output data accessible to a second set of data production systems. The monitoring server is configured to monitor data transmissions between the data production systems and to identify, for each data transmission, originating and receiving systems. The monitoring server is further configured to map data flow from each originating source system to identify all downstream data production systems. Upon identification of a data error in the originating source system, the monitoring server obtains data error information, assembles a data error notification, and transmits the data error notification to data production systems meeting system notification criteria.

Abstract: Aspects of the disclosure include computer-implemented methods and systems for providing generative adversarial network (GAN) digital image data. GAN digital image data corresponding to a suggested transaction for an identified customer can be determined.

Abstract: Described herein are embodiments for managing comments in a program code file. A system may select program code and compile it to an intermediary code. The system may compare the intermediary code to a library of intermediary code snippets associated with comments. Based on the comparison, a system may recognize the code to be obsolete. In some embodiments, a system may generate one or more recommendations to update a code. Based on received feedback regarding a recommendation, a system may accordingly update a code.

Abstract: A system for obtaining user parameters of e-commerce users to auto complete checkout forms includes one or more processors configured to monitor user interactions of a user with a merchant website on a user device; determine an intent to purchase one or more items based of the monitoring; determine an unfilled template of a checkout form associated with the merchant website based on previously stored website information, wherein the unfilled template of the checkout form comprises a plurality of checkout form fields; determine one or more user parameters associated with the user device; apply a machine learning algorithm to predict a geolocation of the user device based on the one or more user parameters; and auto fill the at least one of the plurality of checkout form fields in the unfilled template of the checkout form based on the predicted geolocation.

Abstract: A virtual environment platform may receive, from a user device, a request to access a virtual reality (VR) environment and may verify, based on the request, a user of the user device to allow the user device access to the VR environment. The virtual environment platform may receive, after verifying the user of the user device, user voice input and user handwritten input from the user device. The virtual environment platform may generate processed user speech by processing the user voice input, wherein a characteristic of the processed user speech and a corresponding characteristic of the user voice input are different and may generate formatted user text by processing the user handwritten input, wherein the formatted user text is machine-encoded text. The virtual environment platform may cause the processed user speech to be audibly presented and the formatted user text to be visually presented in the VR environment.

Abstract: In one aspect, the present disclosure relates to a method comprising: receiving, at a client device, information from a node manager about a plurality of nodes in a computer cluster, the information comprising a network address associated each of the plurality of nodes and sending, by the client device, a request to a load balancer to access a first node from the plurality of nodes, the request comprising a first URL including an encoded representation of the network address associated with the first node. The load balancer is configured to determine the request should be routed to a first network address based on decoding the URL, the first network address associated with a first node from the plurality of nodes and forward the request to the first node in response to the determining.

Abstract: Methods for generating data models using a generative adversarial network can begin by receiving a data model generation request by a model optimizer from an interface. The model optimizer can provision computing resources with a data model. As a further step, a synthetic dataset for training the data model can be generated using a generative network of a generative adversarial network, the generative network trained to generate output data differing at least a predetermined amount from a reference dataset according to a similarity metric. The computing resources can train the data model using the synthetic dataset. The model optimizer can evaluate performance criteria of the data model and, based on the evaluation of the performance criteria of the data model, store the data model and metadata of the data model in a model storage. The data model can then be used to process production data.

Abstract: A browser extension application is configured to collect data relating to the user's browsing activity and display notifications on a user interface. A user can instruct a web browsing application to navigate to a website. The browser extension application can detect a type of the webpage, and based on the type of the webpage, collect certain information relating to what the webpage is asking the user to provide and what the user is providing to the webpage. The browser extension application can transmit this information to a browser extension server. The browser extension server can determine a likelihood that the website is associated with instances of hacking online accounts. The browser extension server can transmit a signal to the browser extension application of the user's computing device. The browser extension application can take an action, e.g., direct the user to another website or log out of the user's account.