Illustrative methods and systems may determine whether a rideshare is verified based on received rideshare data. A verification code may be assigned to a rideshare trip. The verification code may be provided to a rider of the rideshare trip. The verification code may be received by a vehicle device assigned to the rideshare trip via user input or communication from the rider device. Whether the rider has entered the correct vehicle for the rideshare trip may be verified based on the verification code assigned to the rideshare trip and the verification code received by the rideshare vehicle.

A merchant may operate a retail store that users are able to visit in person in order to view and purchase products. When a user visits the store, the user might not know where a desired product (“target product”) is located. Computer technology may help direct the user to the target product in real-time. In some embodiments, a model of passable areas and the location of products in the retail store may be determined, e.g. by a merchant device. In some embodiments, when the user visits the retail store, a computer generates a product recommendation, e.g. based on user-specific information, and a route in the retail store is determined for the user. In some embodiments, the route in the retail store may be determined using the model based on the target product, the user's location in the store, and one or more recommended products.

A client device determines a local user gradient value based on a current user preference vector and a local item gradient value based on a current item feature vector. The client device updates a user preference vector by using the local user gradient value and updates an item feature vector by using the local item gradient value. The client device determines a neighboring client device based on a predetermined adjacency relationship. The local item gradient value is sent by the client device to the neighboring client device. The client device receives a neighboring item gradient value sent by the neighboring client device. The client device updates the item feature vector by using the neighboring item gradient value. In response to the client device determining that a predetermined iteration stop condition is satisfied, the client device outputs the user preference vector and the item feature vector.

Techniques for dynamic targeted content processing performed at a server including processor(s) and a non-transitory memory are described herein. In some embodiments, the server obtains user content similarity scores between media content items and users and obtains content similarity scores between a targeted content item and the media content items by projecting the targeted content item and the media content items onto a content vector space. The server also identifies a list of media content items on the content vector space based on the content similarity scores, e.g., a respective media content item in the list has a respective content similarity score satisfying a first criterion. The server additionally locates, for the list of media content items, a set of users among the users based on the user content similarity score, e.g., a respective user in the set has a respective user content similarity score satisfying one or more second criteria.

A live streaming system 10 identifies, with regard to a plurality of users each wearing an HMD 100 to watch same content, types of emotions that the plurality of users are experiencing based on information associated with the plurality of users, the information being detected by a predetermined apparatus. The live streaming system 10 generates, as an image to be displayed on the HMD 100 of a certain user of the plurality of users, an image including the content and at least one of a plurality of avatars corresponding to the plurality of users. The live streaming system 10 changes display appearances of the plurality of avatars depending on the types of emotions that the plurality of users are experiencing.

A system described herein may allow for the intelligent, dynamic selection of an active tenant for a standalone, multi-tenant environment, such as a multi-operator bus or other vehicle. Intelligent selection may be performed using machine learning and/or other suitable techniques, which may be based on similarity to previous usage by a registered tenant, and may further include analyzing structured and/or unstructured data regarding the environment. In addition, the system may allow different profiles, content, or content templates to be associated with different tenants, thus granting a high level of dynamic flexibility in tailoring the content and/or services provided to the users of the environment based on the selected tenant.

The present teaching relates to generating combination distributions for ads. Features are computed based on training data associated with ads, each of which has a plurality of attributes. The training data include asset combinations with past performance thereof for each of the ads. Each combination includes multiple assets representing respective attributes of an ad. The features are used in machine learning to obtain an auxiliary model, which is used to generate combination distributions for each ad based on predicted performance for each combination associated with the ad. Such generated combination distributions are sent to an explore/exploit layer (EEL) for a frontend ad serving engine to draw a combination therefrom for an auction winning ad for rendering on a webpage viewed by a user on a user device.

Blockchain-enabled crypto asset systems and a Digital Social Recorder system are operable within a computer network environment for allowing a user to control how advertisers access the user's personal data; allowing crypto asset compensation in exchange for social amplification; and tracking asset allocation. Payments made via blockchain tracking, and the distribution of any revenues derived from cost savings provided to terrestrial, satellite or digital radio broadcasters back to music rights holders and other related groups are provided. These rights holders typically like to incentivize consumers, and by using the crypto assets or tokens created by the present invention, a reward for listening/consuming may be provided. Further, payments for industry services to the rights holder are contemplated to include, but not be limited to any Performance Rights Organizations (PROs), Record Labels, Publishing Companies/Administrators, Managers, Agents or any fractional rights holders or owners who would hold claim against any such revenues.

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, for providing content. A method includes receiving a request for an advertisement to be displayed in a slot associated with a third-party content site; identifying a relevant advertisement to be provided in the slot; determining information to be included in an annotation associated with the advertisement, the annotation including customized information to be presented along with the advertisement; providing the advertisement responsive to the request including providing the annotation along with a control for re-publishing the advertisement along with the relevant advertisement; receiving user input selecting the control and designating the advertisement for re-publishing to a group, the group being designated by the user; and targeting additional content to the group based on the received user input.

A system and method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle is described. In one embodiment, a method for controlling an autonomous vehicle to affect a view seen by an occupant of the autonomous vehicle includes determining a navigation route, determining content associated with the navigation route, monitoring current conditions of the autonomous vehicle and the occupant, determining, based on the current conditions, whether to change a position of the vehicle to affect the view seen by the occupant, and when the current conditions permit, moving the autonomous vehicle to affect the view seen by the occupant.