Abstract: A method includes determining a first state of a simulation being run by a system and sending first data indicative of the first state of the simulation to a first computing device. The method further includes receiving, after the first data is sent, second data from the first computing device. The second data includes at least one first instruction configured to cause a first move associated with the simulation and is formatted according to a specification. The method further includes determining a second state of the simulation based on the second data received from the first computing device and sending third data indicative of the second state of the simulation to a second computing device. The method further includes receiving, after sending the third data, fourth data from the second computing device. The fourth data includes at least one second instruction configured to cause a second move.

Abstract: Systems, methods, and apparatuses are described herein for performing sentiment analysis on electronic communications relating to one or more image-based communications methods, such as emoji. Message data may be received. The message data may correspond to a message that is intended to be sent but has not yet been sent to an application. Using a first machine learning model, one or more subsets of the plurality of emoji may be determined. The one or more subsets of the plurality of emoji may comprise one or more different types and quantities of emoji, and may each correspond to the same or a different sentiment. Using a second machine learning model, one or more emojis may be selected from the one or more subsets. The one or more emojis selected may correspond to responses to the message.

Abstract: A fraud detection system may identify a suspected fraudulent transaction based on one or more criteria. The transaction may be associated with a user. Based on identifying a suspected fraudulent transaction, the fraud detection system may receive augmented reality data from an augmented reality device of the user. The fraud detection system may determine, based on the augmented reality data, whether the transaction is fraudulent, and may take an action based on the determination.

Abstract: Systems, methods, and apparatuses are described herein for performing sentiment analysis on electronic communications relating to one or more image-based communications methods, such as emoji. Message data may be received. The message data may correspond to a message that is intended to be sent but has not yet been sent to an application. Using a first machine learning model, one or more subsets of the plurality of emoji may be determined. The one or more subsets of the plurality of emoji may comprise one or more different types and quantities of emoji, and may each correspond to the same or a different sentiment. Using a second machine learning model, one or more emojis may be selected from the one or more subsets. The one or more emojis selected may correspond to responses to the message.

Abstract: An example method includes identifying, using a browser extension, content of a first webpage of a first website being displayed using a browser. The identifying of the content includes determining a product related to the content of the first webpage and determining that the product has been added to an electronic shopping cart. The method further includes determining a merchant that offers the product for sale and determining, based on a user account associated with the browser extension, a customer reward offered by the merchant and available to the user account. The method further includes determining that the browser has navigated away from the first webpage to a second webpage of a second website. The method further includes modifying the browser to display a graphical user interface element including information about the customer reward and a link configured to navigate the browser back to the first website.

Abstract: A system and method in accordance with examples may include an identity verification kiosk. The identity verification kiosk may include a display comprising a user interface; a card reader; a document scanner; a printer; and a processor in data communication with a server and a database storing user information. The processor may be configured to receive an identification verification request from the user interface; receive user information via the document scanner or the card reader; retrieve user information from the database; verify the identity of a user; and print a unique identifier on a document using the printer.

Abstract: In some embodiments, an authentication prompt may be generated based on (i) an object, detected in an image stream of an environment of a user, satisfying one or more criteria and (ii) object data associated with the detected object. The criteria may include (i) the object being in a plurality of different samples and (ii) the object being in a first spatial region of a first sample of the different samples, where the first spatial region of the first sample is a spatial region at which the user looked. An authentication response may be obtained from a user device of the user in connection with the authentication prompt, and the user may be authenticated based on the authentication response obtained from the user device.

Abstract: An example method includes identifying, using a browser extension, content of a first webpage of a first website being displayed using a browser. The identifying of the content includes determining a product related to the content of the first webpage and determining that the product has been added to an electronic shopping cart. The method further includes determining a merchant that offers the product for sale and determining, based on a user account associated with the browser extension, a customer reward offered by the merchant and available to the user account. The method further includes determining that the browser has navigated away from the first webpage to a second webpage of a second website. The method further includes modifying the browser to display a graphical user interface element including information about the customer reward and a link configured to navigate the browser back to the first website.

Abstract: In some embodiments, an authentication prompt may be generated based on (i) an object, detected in an image stream of an environment of a user, satisfying one or more criteria and (ii) object data associated with the detected object. The criteria may include (i) the object being in a plurality of different samples and (ii) the object being in a first spatial region of a first sample of the different samples, where the first spatial region of the first sample is a spatial region at which the user looked. An authentication response may be obtained from a user device of the user in connection with the authentication prompt, and the user may be authenticated based on the authentication response obtained from the user device.

Abstract: In some implementations, an article of clothing includes a pocket that includes an opening to an interior cavity, and a lock device attached to the pocket. The lock device may include a first lock element and a second lock element configured to engage with the first lock element, where engagement of the first lock element and the second lock element at least partially closes the opening. The lock device may include a radio communication device configured to receive a signal for engagement or disengagement of the first lock element and the second lock element, and a controller configured to cause engagement or disengagement of the first lock element and the second lock element based on the signal.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an untrained machine learning model with a combined message and an appropriate emoji reaction icon. An embodiment operates by receiving a first and second user message. The first and second user comprises a first and second user text or a first and second user-inserted emoji reaction icon, respectively. The first or second user text is associated with a first or second system-specified emoji reaction icon, respectively. Thereafter, the first user message is determined to be associated with the second user message, the combined message is created based on the first and second messages, and the appropriate emoji reaction is identified as associated with the combined message. The combined message and associated appropriate emoji reaction icon are then sent to an untrained machine learning model configured to for training.

Abstract: A system and method in accordance with examples may include an identity verification kiosk. The identity verification kiosk may include a display comprising a user interface; a card reader; a document scanner; a printer; and a processor in data communication with a server and a database storing user information. The processor may be configured to receive an identification verification request from the user interface; receive user information via the document scanner or the card reader; retrieve user information from the database; verify the identity of a user; and print a unique identifier on a document using the printer.

Abstract: Systems, methods, and apparatuses are described herein for performing sentiment analysis on electronic communications relating to one or more image-based communications methods, such as emoji. Message data may be received. The message data may correspond to a message that is intended to be sent but has not yet been sent to an application. Using a first machine learning model, one or more subsets of the plurality of emoji may be determined. The one or more subsets of the plurality of emoji may comprise one or more different types and quantities of emoji, and may each correspond to the same or a different sentiment. Using a second machine learning model, one or more emojis may be selected from the one or more subsets. The one or more emojis selected may correspond to responses to the message.

Abstract: A method includes determining a first state of a simulation being run by a system and sending first data indicative of the first state of the simulation to a first computing device. The method further includes receiving, after the first data is sent, second data from the first computing device. The second data includes at least one first instruction configured to cause a first move associated with the simulation and is formatted according to a specification. The method further includes determining a second state of the simulation based on the second data received from the first computing device and sending third data indicative of the second state of the simulation to a second computing device. The method further includes receiving, after sending the third data, fourth data from the second computing device. The fourth data includes at least one second instruction configured to cause a second move.

Abstract: A fraud detection system may identify a suspected fraudulent transaction based on one or more criteria. The transaction may be associated with a user. Based on identifying a suspected fraudulent transaction, the fraud detection system may receive augmented reality data from an augmented reality device of the user. The fraud detection system may determine, based on the augmented reality data, whether the transaction is fraudulent, and may take an action based on the determination.

Abstract: Systems, methods, and apparatuses are described herein for performing sentiment analysis on electronic communications relating to one or more image-based communications methods, such as emoji. Message data may be received. The message data may correspond to a message that is intended to be sent but has not yet been sent to an application. Using a first machine learning model, one or more subsets of the plurality of emoji may be determined. The one or more subsets of the plurality of emoji may comprise one or more different types and quantities of emoji, and may each correspond to the same or a different sentiment. Using a second machine learning model, one or more emojis may be selected from the one or more subsets. The one or more emojis selected may correspond to responses to the message.

Abstract: Systems and methods provided herein may include a card replacement system. The system may include an automated teller machine in data communication with a server. The automated teller machine may include an input device; a processor; a replacement card storage containing at least one replacement card, wherein the at least one replacement cards may include a magnetic stripe and a chip; a magnetic stripe writer; a chip writer; and an embossing device. The processor may be configured to: receive a replacement card request via the input device; request replacement card information from the server; encode replacement card information onto the replacement card using the magnetic stripe writer and the chip writer; and emboss user information onto the replacement card using the embossing device.

Abstract: A fraud detection system may identify a suspected fraudulent transaction based on one or more criteria. The transaction may be associated with a user. Based on identifying a suspected fraudulent transaction, the fraud detection system may receive augmented reality data from an augmented reality device of the user. The fraud detection system may determine, based on the augmented reality data, whether the transaction is fraudulent, and may take an action based on the determination.

Abstract: A system and method in accordance with examples may include an identity verification kiosk. The identity verification kiosk may include a display comprising a user interface; a card reader; a document scanner; a printer; and a processor in data communication with a server and a database storing user information. The processor may be configured to receive an identification verification request from the user interface; receive user information via the document scanner or the card reader; retrieve user information from the database; verify the identity of a user; and print a unique identifier on a document using the printer.

Abstract: Systems and methods provided herein may include a card replacement system. The system may include an automated teller machine in data communication with a server. The automated teller machine may include an input device; a processor; a replacement card storage containing at least one replacement card, wherein the at least one replacement cards may include a magnetic stripe and a chip; a magnetic stripe writer; a chip writer; and an embossing device. The processor may be configured to: receive a replacement card request via the input device; request replacement card information from the server; encode replacement card information onto the replacement card using the magnetic stripe writer and the chip writer; and emboss user information onto the replacement card using the embossing device.