Here’s a list of some commonly used generative AI terms in context of our tooling.
Generative Pre-Trained Transformer (GPT): A family of language models developed by OpenAI generally trained on a large corpus of text data such that they can generate human-like text.
Grounding: The process through which domain-specific knowledge and customer information is injected into the prompt. Human In the Loop (HITL): a model that requires human interaction.
Intent: A user’s goal for interacting with the AI-Assistant.
Large Language Model (LLM): A language model consisting of a neural network with many parameters trained on large quantities of text.
Prompt: A natural language description of the task to be accomplished. An input to the LLM.
Prompt Management: The suite of tools used to build, manage, package, and share prompts, including the prompt templates and the prompt template store.
Prompt Template: A string with placeholders/tags that can be replaced with custom values to generate a final prompt. The template includes the hyperparameters associated with that prompt, and model/vendor choice if not using default values.
Prompt Chaining: The method to select the right prompt engineering, which is a break-up of complex tasks into several intermediate steps, and then tie it back together in the hope that the AI generates a more concrete, customized, and thus better result. To get the best prompt in this pilot, use the “Retry” option to regenerate code.
Semantic Retrieval: A scenario that allows a large language model to utilize all the knowledge that exists in a customer’s CRM data. Each CRM user has access to a personalized generative AI.