A transaction system has Internet-connected partner platforms which display webpages with an Offer-Now button initiating coded instructions to display an electronic input form enabling a person to configure a transaction offer, and an Internet-connected service enterprise providing the coded instructions to the partners, configured specifically to partner requirements. Upon the person activating the Offer Now button from a mobile device, a verification code is sent to the device, to be returned to verify the device, and offer input provided through the device and the electronic form is tracked to be saved as an offer for the transaction.

In order to attain an example object of providing a service suitable for a user in a virtual space, a virtual space changing apparatus includes: an acquisition section that acquires position information and line-of-sight target information, the position information including a position of a user in a virtual space or a record of the position, and the line-of-sight target information including a line-of-sight target existing in a line-of-sight direction of the user in the virtual space or a record of the line-of-sight target; and a selection section that selects, based on the position information and the line-of-sight target information, a person in charge of dealing with the user in the virtual space.

A computer-implemented method and system for providing personalized style recommendations in a social shopping environment are described. The method involves searching for a wardrobe associated with a specific person, identifying styles, and generating virtual fit pics for users. These virtual fit pics allow users to see digital representations of themselves wearing clothing items and include interactive elements for purchasing. Users can follow specific wardrobes, which are displayed in their content streams, and receive updates with new digital representations or clothing items. The system comprises a remote storage system, a personal stylist agent, a user interface, and a social wardrobe feed, all working together to enhance the shopping experience.

An online concierge system generates a graph connecting items with attributes of the items and other items. Hence, the graph includes nodes corresponding to attributes and nodes corresponding to items, with an item connected to attributes of the item in the graph. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and compares different combinations of terms to the graph to determine connections between different combinations of terms in the graph. Based on measures of connectedness between combinations of terms and connections in the graph, items are identified from one or more combinations of terms. Information about the identified items is presented to the customer.

An online system may receive, from a content provider, a content presentation campaign that includes one or more objectives. The online system may define a set of one or more policy functions that automatically controls the content presentation campaign. A policy function may control one or more criteria in bidding content slots. The online system may monitor a realized outcome of the content presentation campaign. The online system may apply a reinforcement learning algorithm in adjusting the set of policy functions. The reinforcement learning algorithm adjusts one or more parameters in the set of policy functions to reduce a difference between the realized outcome and the desired outcome set by the content provider. The online system generates an adjusted set of policy functions and uses the adjusted set of policy functions in bidding content slots to present one or more content items provided by the content provider.

A system and method are provided for context-aware virtual assistance and cross-application action execution based on real-time visual input. A client device captures real-time images of a real-world environment and analyzes the images to identify objects or regions of interest. Eye-tracking information is used to determine user interest in the identified objects or regions, and a user context is determined based on visual information, eye-tracking information, and a history of user interactions aggregated across multiple applications. Computer-generated visual content is presented as an overlay on the real-time images based on the determined user context, the overlay comprising a recommendation for a follow-on action associated with a second application. The response is presented via at least one of text, synthesized speech, or computer-generated visual content on a wearable display. Upon detecting user acceptance, the system causes execution of the follow-on action by the second application.

A system for autonomous creation of agreements. The system includes an electronic processor configured to, using a buyer manager artificial intelligence (AI) agent, select a buyer AI sub-agent of a plurality of buyer AI sub-agents, using the selected buyer AI sub-agent, generate and send an initial electronic communication to a seller manager AI agent, and, using the seller manager AI agent, select a seller AI sub-agent of a plurality of seller AI sub-agents based on an electronic conversation history. The electronic processor is also configured to, using the selected seller AI sub-agent, generate and send a response to the buyer manager AI agent based on listing data associated with a seller and the electronic conversation history and determine whether an electronic conversation is terminated. The electronic processor is also configured to, in response determining the agreement is reached, convert unstructured electronic conversation into a structured agreement.

An artificial intelligence (AI) agent generates responses customized to a user based in part on monitored actions of the user. The AI agent, formed from a machine-learning model, is instantiated with inputs that include a set of objectives, an online catalog of items, and user data associated with a user of an online system. Actions performed by a user on the online system are monitored. Action types of at least some of the monitored actions are determined. Responsive to a determination that an action of the monitored actions has an action type of a set of predetermined types of actions, the AI agent is prompted with a description of the action and a request to suggest a response to the action. The determined response is based in part on one or more of the set of objectives. The response suggested by the AI agent is invoked.