Abstract: A Multimodal Search System (MSS) is designed to enable accurate search and retrieval across different modalities of data, including images, videos, and text. The MSS leverages multimodal and domain-specific models to extract and represent features and information from multimodal data, enabling seamless querying using text-based search queries. The MSS integrates multiple pipelines, including feature vector-based and tag-based approaches, to ensure robust and scalable search capabilities. The MSS addresses current multimodal-search challenges by leveraging a hybrid approach that combines multimodal embeddings, text embeddings, and semantic tagging to enable cross-modal searching. Additionally, for visual data, both tagging and embedding techniques are integrated within a single modality, ensuring a comprehensive and accurate representation. By assembling multiple retrieval strategies, the solution harnesses the strengths of each, resulting in a balanced and effective search system.

Abstract: Methods, systems, and computer programs are presented for proactively generating content based on performance of previous content. One method includes an operation for transmitting a set of first items for presentation. The first items are multimodal, and each first item has values for attributes associated with the first item. The method further includes tracking performance of the transmitted set of first items, selecting values of attributes based on the tracked performance, and proactively generating, using one or more generative artificial intelligence (GAI) tools, a set of second items based on the selected values of the attributes. Further, the method includes operations for providing a user interface (UI) with an option to select from the set of second items, receiving in the UI a selection of selected second items for transmittal, and transmitting the selected second items to one or more users.

Abstract: Methods, systems, and computer programs are presented for generating personalized content. One method includes an operation for identifying audience parameter values that indicate which users are members of an audience. The method further includes operations for determining attribute values for attributes used to generate items based on the audience parameter values, and generating items for the audience based on the attribute values. Generating each item comprises creating a prompt based on a type of the item, the attribute values, and the audience parameter values; selecting a generative artificial intelligence (GAI) tool to generate the item based on the type of item; and providing the created prompt to the selected GAI tool. The method further includes causing presentation of the generated items in a user interface (UI), receiving on the UI a selection of one of the items; and transmitting the selected item to one or more members of the audience.

Abstract: Methods, systems, and computer programs are presented to provide a personalized view of webpages and an interactive assistant for exploring website content. One method includes operations for accessing website data of a website, and detecting a request entered by a user in a user interface (UI). One or more blocks for a webpage are generated in response to the request, where generating each block includes constructing a prompt by entering website data, user information, and block information on a prompt template; providing the prompt as input to a Generative Artificial Intelligence (GAI) tool; and utilizing the response from the GAI tool to build the block for the webpage. The method further includes causing presentation on the UI of the webpage including the generated one or more blocks.

Abstract: Methods, systems, and computer programs are presented for the generation of content in advance to enable quickly customized communications for multiple types of customers. One method includes an operation for identifying components of an image design that specifies how the components are combined to generate an image. For one or more of the identified components, variations of the components are generated using one of several generative artificial intelligence (GAI) models. The method further includes detecting a request, comprising user attributes, for the image. For one or more of the identified components, a respective variation is selected based on the user attributes, and a response image is created utilizing the image design and the one or more selected variations. Further, the response image is presented on a computer user interface.

Abstract: Methods, systems, and computer programs are presented for generating multimodal content utilizing multimodal templates. One method includes presenting, in a user interface (UI), a template-selection option with one or more templates. Each template comprises a sequence of operations, where each operation comprises a prompt for creating items using generative artificial intelligence (GAI) tools. Further, each operation in the template is multimodal to be configurable to create text and configurable to create one or more images. The method further includes detecting a selection of a template in the UI. For each operation in the selected template, perform operations comprising: presenting, in the UI, the prompt associated with the operation; in response to receiving an input for the prompt, selecting a GAI tool based on a mode of the operation; providing the input to the selected GAI tool to generate the item; and presenting, in the UI, the generated item.

Abstract: Methods, systems, and computer programs are presented for providing an interactive canvas tool to generate multimodal, personalized content. One method includes providing a user interface (UI) for a canvas tool to generate multimodal content. The canvas tool comprises a prompt panel, a variations panel, and a canvas configured to present items of several types, such as a text type and an image type. The method further includes receiving text input including a textual description with instruction for generating an item, where the canvas tool is configured to generate items from the several types. The method further includes providing the text input to a generative artificial intelligence (GAI) tool, and presenting one or more variations based on an output of the GAI tool. The method further includes detecting a selection of one of the variations in the variations panel, and adding the selected variation to the canvas in the UI.

Abstract: Methods, systems, and computer programs are presented for enhancing a machine-generated product image. One method includes an operation for receiving a request on a user interface (UI) to generate an image, where the request comprises a description of the image to be generated and identification of a product for inclusion in the image. The method further includes operations for generating, by a generative artificial intelligence (GAI) model, a first image based on the request, analyzing the first image to identify a presentation of the product in the first image, and selecting a product image from a database of product images based on the identification of the product. The method further includes replacing the presentation of the product in the first image with the selected product image to obtain a second image, and causing presentation in the UI of the second image.

Abstract: Methods, systems, and computer programs are presented for providing a prompt tool with interactive entry. One method includes operations for providing a multimodal prompt tool for entering textual description of an item to be generated, and detecting an input that is one of a special character entered in the textual description or a mouse action requesting assistance. Furthermore, a menu is presented with options for the item to be generated, and a list of products, previously added to a data store, is obtained. Further, the method includes providing the list of products for selection; in response to a selection of a product from the list of products, including text associated with the selected product in the textual description; and detecting submittal of the textual description. Further, the textual description is entered as input to a generative artificial intelligence (GAI) tool, and causing presentation of items generated by the GAI tool.