Abstract: The present teaching relates to auto response via large language models (LLMs) and application thereof to generate personalized auto responses on behalf of public figure users in response to fan communications. Each auto response responsive to an incoming fan communication directed to a public figure user is generated by LLMs according to a prompt dynamically created based on general instructions for general guidelines for the auto response as well as personalized instructions for personalizing the auto response for the public figure user and the fan. The personalized instructions are created based on relevant information associated with the public figure user and the incoming fan communication.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) training, by a processor, a machine learning model to create composite images from background scenes and foreground objects, (ii) identifying, by the processor, a digital image file that comprises a background scene and an additional digital image file that comprises a foreground object, (iii) compositing, by the machine learning model executed by the processor, the digital image file that comprises the background scene and the additional digital image file that comprises the foreground object to produce a composite digital image file that comprises the foreground object and the background scene by performing at least one of a channel concatenation step and a reverse diffusion sampling step, and (iv) causing display, by the processor, of the composite image file that comprises the foreground object and the background scene.

Abstract: In some implementations, the techniques described herein relate to a method including: identifying, by a processor, a digital image file that includes a background scene and an additional digital image file that includes a foreground object; compositing, by a machine learning model executed by the processor, the digital image file and the additional digital image file to produce a composite digital image file that includes the foreground object placed in front of the background scene by: identifying a location within the background scene in the digital image file for placement of the foreground object from the additional digital image file; transforming at least one aspect of the foreground object to harmonize with the background scene; and creating a composite image file that includes the harmonized foreground object in the location within the background scene; causing display, by the processor, of the composite image file.