Disclosed herein are systems, methods, and computer-readable storage devices for a new browser including multiple application programming interfaces. A method includes receiving, from a site, at a browser and via a first application programming interface that defines a first protocol for communicating data between the browser and the site, a first payment request associated with a potential purchase by a user, in response to the first payment request and based on an identification of a payment service, communicating, from the browser and via a second application programming interface that defines a second protocol for communicating data between the browser and the payment service, a second payment request to the payment service, receiving, at the browser, from the payment service, via the second application programming interface, authorized payment information and communicating, from the browser, to the site and via the first application programming interface, the authorized payment information.

A shopping terminal that is used in a store includes a memory that stores labels indicating environmental conditions each in association with sensor data, and a processor configured to execute a program that is stored in the memory to perform the steps of: acquiring a query indicating a question input by a user, acquiring sensor data from a sensor, searching the memory for a label corresponding to the acquired sensor data, generating a prompt based on the query and the label, inputting the prompt to a computer model, which generates in response thereto an answer to the question, the computer model having learned relationships and connections between human perceptions under different environmental conditions, and data of items sold in the store, and converting the answer into audio data, and outputting the audio data.

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.

Described implementations determine or monitor one or more parameters of an electrical circuit at a location to determine device usage at the location and utilize that information to determine when consumable inventory at the location is depleted and should be reordered. For example, when a device at the location is turned on, the device affects voltage that is introduced into the voltage signal at the location and detectable by, for example, a plug-in sensor. Different devices generate different patterns or signatures of voltage as they operate, thereby making the signatures unique, or almost unique, to different device types and/or different devices. Utilizing this information for devices that utilize consumable inventory, such as coffee pods, laundry detergent, dishwashing detergent, frozen dinners, popcorn, etc., it can be determined when the consumable inventory is depleted and should be reordered.

An online system, such as a concierge service, provides services to users using a set of limited resources. To allocate the limited resources of the system among the users, the system uses a model to predict each user's sensitivity to different levels of service. An allocation module then allocates the limited resources among a set of users based in part on the estimated sensitivities and the supply of available resources.

A computer system for sump pump monitoring and repair service provider notification may include one or more processors configured to: detect that a sump pump is faulty, transmit a prompt for service quotes to a machine learning (ML) chatbot to cause the ML chatbot to: request sump pump replacement or repair services from one or more service providers, receive cost estimates from the one or more repair service providers, receive schedule availability from the one or more repair service providers, receive, from the ML chatbot, the cost estimates and the schedule availability, and communicate the cost estimates and/or the schedule availability to a user associated with the sump pump.

A system to personalize a shopping experience in a conversational commerce platform is disclosed. The system includes a processing subsystem having a user interface module for consumer input and an input conversion module that processes and translates this input using a large language model (LLM) engine. The engine module features a catalog facet creation module that structures product information, a facet enrichment module for detailed descriptions, images and buyers' profile, and a customer profiling module utilizing natural language processing to understand customer needs. An AI merchandising module presents optimal product facets to customers based on profiles and historical data. Additionally, a conversational commerce module facilitates product selection through guided conversations, while a personalization module tailors recommendations. The system also includes a data collection and analytics module for performance tracking and a training and optimization module for continuous improvement of the LLM.

A method for providing a personalized shopping and styling experience using an AI-Interface application is provided. The method includes presenting a user app interface on a user device associated with a user to receive user data comprising user shopping and styling preferences, shopping habits, and images of the user's personal wardrobe inventory. The method also includes providing a virtual closet for the user, wherein the virtual closet comprises processed images of the personal wardrobe inventory of the user. The method further includes providing a personalized product feed source by filtering product data. The method additionally includes providing a personal stylist interface that allows stylists to access the virtual closet of the user. The method includes analyzing using an AI model, the user preferences and shopping habits, sales history, browsing history, and the selected items, wherein the AI model continuously learns and generating personalized product recommendations to the user.

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.

An adaptive collaborative platform applies various machine learning techniques to correlate potential purchasers with high-value articles of property that may be of interest. Attributes, characteristics, preferences, and the like of a potential purchaser are scored against attributes and features of articles. The platform learns from interaction by the agents and the potential purchasers and adapts to become more attuned to the desires and lifestyle of purchasers and to gain more and more pertinent information from the listing agents regarding high-value articles, so as to ultimately to arrive at a better match between a high value article for sale and a likely purchaser.