Abstract: Disclosed are systems and methods for displaying content on a user device. For example, a method of displaying content on a user device may include: receiving a first set of content data; arranging and displaying the first set of content in a first sequence of consecutive segments; detecting user input indicative of a scroll pattern of the user through the first sequence of consecutive segments; determining a preferred category based on the detected user input; receiving a second set of content data; arranging the second set of content data into a second sequence of consecutive segments based on the preferred category; and displaying the second set of content data in the arranged second sequence of consecutive segments on the display of the user device.

Abstract: A device receives user rendering data for a 3-D rendering of a user. The 3-D rendering is a proportional representation of the user and the user rendering data is available via an application. The device determines user characteristics of the user. The device receives an indication that a user device has submitted a vehicle search request. The device identifies vehicles to recommend to the user based on an analysis of: the user characteristics, and vehicle characteristics for a collection of vehicles being offered via the application. The device causes vehicle description data for the vehicles to be displayed via an interface of the application. The device receives user interaction data that indicates a user selection of vehicle. The device causes, based on receiving the user interaction data, the interface of the application to display a placement of the 3-D rendering of the user into a 3-D rendering of the vehicle.

Abstract: A signal interpretation system includes a communication device, a memory storing instructions, and one or more processors configured to execute the instructions to perform operations including: receiving scanned information including a shape of at least one article scanned with a scanning device to identify the at least one article and identifying a geographic location of the scanning device, when a scan of the at least one article was performed, based on a location signal received from the scanning device. The operations also include evaluating a signal indicative of interest in the identified at least one article and transmitting, via the communication device, a notification based on the evaluated signal, the notification being indicative of the identified at least one article and the identified geographic location, the notification being configured to cause an update in at least one graphical element presented by the scanning device or another device.

Abstract: An image information overlay system retrieves an image associated with a vehicle listing and uses machine learning models to classify the image, generating identification data that may comprise a vehicle make and model, a feature or part of the vehicle present in the image, and a location of the vehicle feature or part. The identification data or an individual identifier of the vehicle, such as a Vehicle Identification Number (VIN), may be used to retrieve overlay information related to the vehicle make and model, such as recalls or known maintenance issues or information specific to the vehicle, such as mileage, accident reports, or ownership history. The overlay information is displayed on the image as an overlay at the location of the vehicle feature or part corresponding to the overlay information.

Abstract: Methods, systems, and apparatuses are described herein for providing purchase recommendations by analyzing social networks using machine learning. A machine learning model may be trained to select one or more of the first plurality of users. Purchase intention data that indicates an intention of a first user to acquire a type of asset may be received. Social networking data that comprises a plurality of associations between a second plurality of users may be received. Purchase history data indicating one or more purchases, of one or more assets associated with the type of asset, made by the second plurality of users may be received. The trained machine learning model may be provided the data. In return, the trained machine learning model may provide an indication of a second user. A notification may be sent to the second user.

Abstract: In some implementations, a system may input a set of values, for a corresponding set of features, to a machine learning model that is trained to predict a likelihood that a user will perform the action in connection with one or more entities. The set of values may be based on interactions of the user with one or more user interfaces associated with a plurality of entities. The system may execute the machine learning model on the set of values. The system may generate, based on executing the machine learning model on the set of values, an output indicative of the likelihood that the user will perform the action. The system may identify an entity, of the one or more entities, based on the output satisfying a threshold and may provide information to facilitate communication between the user and the entity.

Abstract: Aspects described herein may allow an automated generation of an interactive multimedia content with annotations showing vehicle damage. In one method, a server may receive vehicle-specific identifying information of a vehicle. Image sensors may capture multimedia content showing aspects associated with exterior regions of the vehicle, and may send the multimedia content to the server. For each of the exterior regions of the vehicle, the server may determine, using a trained classification model, instances of damage. Furthermore, the server may generate an interactive multimedia content that shows images with annotations indicating instances of damage. The interactive multimedia content may be displayed via a user interface.

Abstract: In some implementations, a system may receive an access request associated with an agent and the vehicle. The system may authenticate, based on an agent identification associated with the agent, the agent in association with providing the vehicle service. The system may send, based on authenticating the agent, an authorization request to a user associated with the vehicle, wherein the authorization request is sent to a user device associated with the user that enables the user to authorize the agent to access the vehicle in association with providing the vehicle service. The system may receive, from the user device, a user authorization that authorizes the agent to access the vehicle. The system may configure the vehicle to enable the agent to access the vehicle via a client device associated with the agent.

Abstract: Systems and methods for presenting an augmented reality view are disclosed. Embodiments include a system with a database for personalizing an augmented reality view of a physical environment using at least one of a location of a physical environment or a location of a user. The system may further include a hardware device in communication with the database, the hardware device including a renderer configured to render the augmented reality view for display and a controller configured to determine a scope of the augmented reality view authenticating the augmented reality view. The hardware device may include a processor configured to receive the augmented reality view of the physical environment, and present, via a display, augmented reality content to the user while the user is present in the physical environment, based on the determined scope of the augmented reality view.

Abstract: A device may process, after obtaining an image that includes image data concerning a product, first audio data obtained concerning a first utterance of a user of a user device, and first video data obtained concerning a first eye gaze direction of the user, to determine a first reaction of the user to the image. The device may process, after causing display of the image and an overlay superimposed on the image by the user device, second audio data obtained concerning a second utterance of the user, and second video data obtained concerning a second eye gaze direction of the user, to determine a second reaction of the user to the image and the overlay. The device may retrain a product recommendation model using the first reaction and the second reaction, and may generate and cause display of a product recommendation based on the product recommendation model.

Abstract: The present disclosure relates to systems and methods for generating real-time quotes using machine learning algorithms. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device, extracting one or more features from the image, based on the extracted features and using a machine learning algorithm, identifying one or more attributes of the vehicle, based on the identified attributes of the vehicle, determining a make and a model of the vehicle, obtaining comparison information based at least in part on the determined make and model, estimating a quote for the vehicle based on the comparison information; and transmitting the estimated quote for display on the client device.

Abstract: A computer-implemented method for determining an actual cost of ownership of a purchase product may include determining a baseline value of the purchase product, and receiving usage information representative of usage of a user product from a computing device in communication with the user product. The purchase product and the user product may belong to a same class of products. The method also may include determining a user cost component based on the received usage information, and determining an actual cost of ownership of the purchase product based on at least the baseline value and the user cost component.

Abstract: Embodiments disclosed herein provide for a system and method for recalibrating an augmented reality experience in mobile devices using a plurality of physical markers. The system and methods provide for realigning the digital representation to the physical world using known physical locations associated with the physical markers that map directly to the digital representation.

Abstract: Aspects described herein may facilitate an automated trade-in of a vehicle with limited human interaction. A server may receive a request to begin a value determination of a vehicle associated with the user. The server may receive first data comprising: vehicle-specific identifying information, and multimedia content showing a first aspect of the vehicle. The user may be directed to place the vehicle within a predetermined staging area. The server may receive, from one or more image sensors associated with the staging area, second data comprising multimedia content showing a second aspect of the vehicle. The server may create a feature vector comprising the first data and the second data. The feature vector may be inputted into a machine learning algorithm corresponding to the vehicle-specific identifying information of the vehicle. Based on the machine learning algorithm, the server may determine a value of the vehicle.

Abstract: Systems and methods of determining changes in an individual's interaction patterns indicative of changed circumstances are disclosed. An exemplary method can include receiving a first set of interaction records relating to an individual and creating an interaction profile based on the first set of interaction records. The method can also include monitoring a second set of more recent interaction records, comparing the second set of interaction records to the interaction profile to identify one or more changes to the interaction patterns identified in the first set of interaction records, analyzing the one or more changes to the interaction patterns to determine if the one or more changes is indicative of a changed circumstance for the individual, and generating recommendations for programs to be presented to the individual based on the changes to the interaction patterns identified in the first set of interaction records.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: Aspects described herein may allow for vehicle tracking. Systems and methods described herein may allow a vehicle to automatically detect the presence of a physical marker at a parking space. An image of the physical marker may be processed to determine the location of the vehicle, which may be stored and/or output for display.

Abstract: An image error identification system retrieves an image associated with a vehicle listing and uses various machine learning models to classify the image and generate identification data that may include a vehicle make, model, trim level, and/or various features of the vehicle present in the image. The identification data is compared to the rest of the vehicle listing to detect a mismatch between the image and the vehicle listing. An alert is generated, when a mismatch is detected, indicating the one of the image or the data in the vehicle listing is incorrect.

Abstract: Aspects described herein may allow for a payment card assembly including a payment card having a first surface, an opposed second surface, and an aperture extending through the payment card from the first surface to the second surface. An insert may be removably received in the aperture. Each of a plurality of identification elements may be configured to be removably received in the aperture and have an identification characteristic different than an identification characteristic of each of the other identification elements.

Abstract: A system for inspecting the reliability of an image. The system may include a processor in communication with a client device; and a storage medium. The storage medium may store instructions that, when executed, configure the processor to perform operations including: obtaining a plurality of images; categorizing the images into a plurality of image classes; calculating a plurality of probability outcomes; determining whether highest predicted probabilities of the images are less than a first threshold and whether an entropy of a predicted density of the probability outcomes exceeds a second threshold; indicating whether the image is associated with the image classes; ranking, the image amongst the plurality of images; filtering, a plurality of low reliability images according to a third threshold; providing, a likelihood of whether a user scanned a vehicle object associated with the image; and identifying a percentage of user scan failures.