Abstract: The subject technology includes a language model interface for generating natural language insights for objects included in a particular UI page. The language model interface may train application specific language models based on features determined from snapshot data of application UI pages. The features may include snapshot features derived from multi-modal embeddings. To train the application models using the snapshot features, system prompts may be constructed. The system prompts may include natural language descriptions determined by mapping the multi-modal embeddings to a trained text feature space. The language model interface may also include one or more coordination components for making the generated responses available to the application and optimizing the performance of the language models.

Abstract: The subject technology uses context models to improve the performance of language models. The technology may introduce one or more context insights into the prompts for language models to personalize the outputs of the language models for particular users. The context insights may include consumer dimensions determined based on identity data for a user. The consumer dimensions may be generated using machine learning techniques that are applied to consumer data, event data, and transaction data. A unique context model may be trained for each consumer dimension to increase the accuracy and specificity of the context models. The personalized content generated by the language models may be included in a piece of content published on a publication network. The performance the language models may be optimized based on the performance of the published content.

Abstract: In some examples, a system for determining a level of self-image congruence comprises at least one processor and a memory storing instructions which, when executed by the at least one processor among the processors, cause the system to perform operations comprising, at least: selecting one or more self-image attributes that align with a brand-user image; defining each of the selected self-image attributes via a type of subject matter that is of interest to consumers identifying with the selected attributes; identify consumers exhibiting one or more of the selected attributes based on a digital footprint including an online content consumption; computing a congruence score for each identified consumer relative to each selected attribute; and rating the resulting set of consumers based on their respective congruence scores for the selected attributes.

Abstract: In some examples, a system for determining a level of self-image congruence comprises at least one processor and a memory storing instructions which, when executed by the at least one processor among the processors, cause the system to perform operations comprising, at least: selecting one or more self-image attributes that align with a brand-user image; defining each of the selected self-image attributes via a type of subject matter that is of interest to consumers identifying with the selected attributes; identify consumers exhibiting one or more of the selected attributes based on a digital footprint including an online content consumption; computing a congruence score for each identified consumer relative to each selected attribute; and rating the resulting set of consumers based on their respective congruence scores for the selected attributes.

Abstract: The system and method of the present invention provides customers with real-time information in order to evaluate future consumer spending capacity. The present invention can help to identify situations beyond traditional credit metrics to determine change of circumstances for end-consumers. The system allows for selection of consumers based on data trends and learned industry risk and behavior indicators.

Abstract: A computer-implemented method for sending email messages with dynamically-determined content, the method comprising: transmitting email messages to a plurality of recipient groups each comprising at least one recipients, each message comprising one or more dynamic content network references associated with dynamically-selected content items; receiving, by a network-connected server, a dynamic content network request responsive to the rendering of one of said dynamic content network references within an email message received by a recipient device, the dynamic content network request comprising one or more content selection criteria, the content selection criteria comprising an embedded user identifier uniquely associated with a user to whom an email among the email messages was transmitted; dynamically selecting a content item from amongst a plurality of candidate content items based at least in part on the content selection criteria and the recipient's recipient group; implementing an exclusion service by cr