A method for using an electronic shopping list to resolve ambiguity associated with a selected product may include accessing an electronic shopping list associated with a customer of a retail store; receiving image data captured using one or more image sensors in the retail store; analyzing the image data to detect a product selection event involving a shopper; identifying a product associated with the detected product selection event based on analysis of the image data and further based on the electronic shopping list; and based on the identification of the product, updating a virtual shopping cart associated with the shopper.

A server for managing data of items sold by a store, includes a network interface configured to communicate with a mobile terminal, a memory, and a processor configured to execute a program stored in the memory to perform: upon receipt of first text from the terminal, inputting the first text about an item sold by the store to a model, which generates in response thereto second text that promotes the item, acquiring related information corresponding to the item, generating third text based on the acquired information, storing the third text in a location, and generating a link to the location, generating answer information including the second text and the link, and transmitting the answer information to the mobile terminal.

One embodiment relates to a method for searching for travel items. The method includes obtaining interaction data indicating a set of interactions of a first user across a plurality of platforms. The method includes generating a dynamic user profile indicating a plurality of travel preferences for the first user. The method includes generating search suggestions for the first user based on the dynamic user profile, the search suggestions specific to the first user and generated based at least in part on characteristics of the dynamic user profile. The search suggestions include at least one of suggested search queries or suggested filters. The method includes receiving a selection from the first user of a first search suggestion. The method includes identifying a first plurality of travel items using the selected first search suggestion. The method includes providing, to the first user, the first plurality of travel items.

One embodiment relates to a method for travel comparison. The method includes obtaining, by one or more processing circuits, interaction data indicating a set of interactions of a first user across a plurality of platforms. The method includes generating a dynamic user profile indicating a plurality of travel preferences for the first user using the interaction data. The method includes providing, to the first user, a first set of travel search results based on the dynamic user profile. The method includes generating a comparison among two or more travel items included in the first set of travel search results, where the comparison relates to one or more features of the two or more travel items, and where generating the comparison includes selecting the one or more features based at least in part on one or more characteristics of the dynamic user profile.

One embodiment relates to a method for dynamic user preference assessment. The method includes receiving a dynamic user profile indicating a plurality of travel preferences for a user. The method includes providing, to the user, a first indication of a first set of one or more of the plurality of travel preferences indicated by the dynamic user profile at a first time. The method includes obtaining interaction data indicating interactions of the user across a plurality of platforms. The method includes processing the interaction data to infer changes to the plurality of travel preferences indicated by the dynamic user profile. The method includes updating the dynamic user profile to include the changes to the plurality of travel preferences.

The disclosed system obtains data entries associated with a user including segmentation, preferences, behavior elements, contextual events, and trust expectations. The system obtains data entries associated with the wireless telecommunication network including available products, available promotions, and selling channels. The system receives an indication to initiate an interaction between the user and a channel associated with the wireless telecommunication network, where the interaction is aimed at completing a task. Based on the indication to initiate the interaction, the data entries associated with the user, and the data entries associated with the wireless telecommunication network, the system generates a first question to present to the user. The system receives a response to the question from the user. Based on the response, the system generates a second question to present to the user, where the second question furthers completion of the task.

A system for executing actions based on user input is provided. The system comprises a virtual agent for a software application, wherein the virtual agent is configured to store a correlation between actions available in the software application. Further, the system associates one or more of the actions with one or more tags. The system receives at least an audio input from a user of the software application and uses the input to identify an action desired by the user to be performed among the actions. Further, the system executes one or more actions based on the desired action and the correlation between the actions available in the software application.

Systems and methods for providing an AI assistant to users of a food delivery system. The method includes receiving a user query, wherein the user query is associated with a food delivery system. The method further includes accessing contextual data for the user query. The method further includes generating model input, the model input including the user query and the contextual data for the user query. The method further includes providing model input as input to a machine-learned large language model. The method further includes receiving a query response as an output of the machine-learned large language model processing the model input. The method further includes outputting the query response to the user for display, the query response comprising a carousel of selectable options available through the food delivery system.

The present teaching relates to conduct persona-adaptive communications with a customer at a geo-locale. Transcripts of a current and historic communications involving the customer are used to characterize the persona of the customer. Transcripts of historic communications with customers at the geo-locale are used to characterize the persona of the geo-locale. Current persona of the customer exhibited in the current communication is combined with the customer's persona and the geo-locale's persona to compute a response input vector, A language model generates, based on the response input vector, a persona-adaptive response, which is then sent to the customer a response.

A computer system for flood monitoring and insurance provider notification, the computer system may include one or more processors configured to: detect a flood event in a structure, transmit information associated with the structure and a prompt for flood reimbursement services to a machine learning (ML) chatbot to cause the ML chatbot to file a flood reimbursement claim with an insurance provider having an insurance policy associated with the structure via telephone by converting a text output into a voice output.