System and method for audience-based customization of generative artificial intelligence (ai)

A system comprising:

• one or more hardware processors;
• and
• at least one memory storing instructions that cause the one or more hardware processors to perform operations comprising:
• receiving a request from a requestor for an artificial intelligence (AI)-generated output;
• determining an intended audience for the AI-generated output based on the request;
• creating an audience-based response to the request by using a trained large language model (LLM) or a combination of the trained LLM and an LLM style-based embedding, wherein using the trained LLM comprises:
• generating a base response to the request using the trained LLM, and
• applying one or more audience-specific transformation systems to the base response to create the audience-based response, wherein the one or more audience-specific transformation systems are configured to modify the base response for the intended audience, and
• wherein using the LLM style-based embedding comprises:
• creating, based on the LLM style-based embedding, a word representation of at least a portion of the request, and
• generating an audience-based response by using the trained LLM to output the audience-based response based in part on the word representation;
• and
• providing the audience-based response as the AI-generated output to the requestor.

A machine-readable medium storing instructions that, when executed by a computer system, cause the computer system to perform operations comprising:

• receiving a request from a requestor for an artificial intelligence (AI)-generated output;
• determining an intended audience for the AI-generated output based on the request;
• creating an audience-based response to the request by using a trained large language model (LLM) or a combination of the trained LLM and an LLM style-based embedding, wherein using the trained LLM comprises:
• generating a base response to the request using the trained LLM, and
• applying one or more audience-specific transformation systems to the base response to create the audience-based response, wherein the one or more audience-specific transformation systems are configured to modify the base response for the intended audience, and
• wherein using the LLM style-based embedding comprises:
• creating, based on the LLM style-based embedding, a word representation of at least a portion of the request, and
• generating an audience-based response by using the trained LLM to output the audience-based response based in part on the word representation;
• and
• providing the audience-based response as the AI-generated output to the requestor.