Prompt chaining system for generative artificial intelligence systems

#Aspects of the present disclosure generally relate to generative models, and more specifically to systems and methods for resolving ambiguity in text prompts for generative models.

#Generative models, such as generative artificial intelligence (AI) models, exemplify the capabilities of AI models trained on extensive datasets of pre-existing content (hereinafter referred to as “training data”). Based on this training, generative AI models may discern intricate patterns and establish meaningful connections within the training data and/or input data. When provided with a prompt, a generative AI model may create content in the form of text, images, and/or music in accordance with the training data and/or previous input data.

#The rapid advancements in generative AI models have made them more accessible to individuals without specialized expertise. However, there are cases where obtaining a desired output from a generative AI model can be challenging due to an inadequate prompt. To tackle this issue, prompt engineering may be used to craft effective prompts that produce the desired outcomes. In some scenarios, natural language processing (NLP) techniques are utilized to formulate these effective prompts.

#The features, nature, and advantages of the present disclosure will become more apparent from the detailed description set forth below when taken in conjunction with the drawings in which like reference characters identify correspondingly throughout.

#FIG. 1 is a block diagram illustrating an example of a system generating content via a generative artificial intelligence (AI) model, in accordance with aspects of the present disclosure.

#FIG. 2 is a diagram illustrating an example of a hardware implementation for a system, in accordance with aspects of the present disclosure.

#The detailed description set forth below, in connection with the appended drawings, is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the various concepts. It will be apparent to those skilled in the art, however, that these concepts may be practiced without these specific details. In some instances, well-known structures and components are shown in block diagram form in order to avoid obscuring such concepts.

#Based on the teachings, one skilled in the art should appreciate that the scope of the present disclosure is intended to cover any aspect of the present disclosure, whether implemented independently of or combined with any other aspect of the present disclosure. For example, an apparatus may be implemented, or a method may be practiced using any number of the aspects set forth. In addition, the scope of the present disclosure is intended to cover such an apparatus or method practiced using other structure, functionality, or structure and functionality in addition to, or other than the various aspects of the present disclosure set forth. It should be understood that any aspect of the present disclosure may be embodied by one or more elements of a claim.

#The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects.