Microsoft Technology Licensing, LLC

Rolly Seth

Rajat Chamria

Nikita Viktorovich Sarychev

A data processing system implements receiving, from a sender device, a request to personalize and distribute a design content item based on content consumption needs and/or preferences of recipients, wherein the content consumption needs and/or preferences include a data type; constructing a prompt by appending the design content item and the content consumption needs and/or preferences to an instruction string, the instruction string including instructions to a generative model to transform per recipient the design content item into a personalized content item based at least one of a content consumption need or a content consumption preference of a respective recipient; providing as an input the prompt to the generative model and receiving as an output the personalized content item from the generative model; providing the personalized content item to a recipient device; and causing a user interface of the recipient device to render the personalized content item.

AI-based personalized bulk design content creation

A user device having a presentation application includes a processor; a memory storing the presentation application for implementation by the processor, alone or in combination with other processors. The application includes a user interface allowing a user to request integration of multiple slides into a single canvas with a common background generated by an Artificial Intelligence (AI) model based on backgrounds of the multiple slides being integrated into the single canvas.

Integrating multiple slides for a presentation using a generated common background

A computing apparatus comprising one or more computer readable storage media, one or more processors operatively coupled with the one or more computer readable storage media, and an application comprising program instructions stored on the one or more computer readable storage media that direct the computing apparatus to at least display electronic document in a user interface to an application and send a request to an energy analysis service to analyze an energy footprint of the electronic document, wherein the request identifies a characteristic of the electronic document. The program instructions further direct the computing apparatus to receive a reply to the request, wherein the reply includes a recommendation to decrease the energy footprint of the electronic document and modify the electronic document in accordance with the recommendation.

Systems, methods and software for improving the energy footprint of an electronic document

The present disclosure relates to management of transparent glassboard representations, where a virtual glassboard is comprehensively integrated with presentation content. An exemplary transparent glassboard representation provides a layered configuration of content layers in an ordered arrangement to maximize integration of a virtual glassboard within presentation content. Some examples of the present disclosure comprise those where a graphical user interface (GUI) object is managed during the design of presentation content. In further examples, the present disclosure pertains to management for rendering of a transparent glassboard representation within a GUI of a host application/service endpoint during real-time (or near real-time) presentation. Further non-limiting examples apply trained artificial intelligence (AI) processing to efficiency automate management of transparent glassboard representations both in a design phase and presentation phase for managing presentation content. Representations of presentation content, comprising a transparent glassboard representation, may be synchronized through a plurality of different host applications/services.

Management of presentation content including generation and rendering of a transparent glassboard representation

The present disclosure relates to management of synthetic media detection determinations and automatic generation of notifications thereof. Processing of the present disclosure provides a synthetic media detection component, able to be integrated with a plurality of host application/services, where the synthetic media detection component is adapted to work as a trust factor that automatically generates predictive determinations as to whether digital content has been digitally altered. In doing so, trained artificial intelligence processing is applied that executes a contextual analysis of digital content and generates a determination as to whether digital content (or a portion thereof) may be synthetic media. Notifications are automatically generated and provided for rendering across any host application/service endpoints that provide a representation of the digital content including future representations of digital content. Automated generation and transmission of synthetic media detection determinations are aimed at combatting disinformation and subsequent presentation of untrusted/unauthenticated digital content.

Synthetic media detection and management of trust notifications thereof

A method and system for providing real time video collaboration production may include receiving a first video content portion from a first collaborator, the first video content portion being associated with a first sequence indicator, receiving a second video content portion from a second collaborator, the second video content portion being associated with a second sequence indicator, determining an order for the first video content portion and the second video content portion based on the first sequence indicator and the second sequence indicator, automatically integrating the first video content portion with the second video content portion based on the order to create an integrated video content portion, and providing the integrated video content portion for real-time display to the first collaborator and the second collaborator.

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Redmond, WA, United States of America

Rolly Seth