Huma.AI Glossary

Output refers to the final result or answer produced by an AI system after processing the given input.

Prompt crafting refers to the skill of creating effective and specific questions or instructions to guide an AI system's responses.

Prompt engineering refers to the process of designing and refining the prompts or instructions given to an AI model to generate desired outputs or responses.

A prompt framework refers to a structured approach or system that provides guidelines and structure for designing effective prompts to elicit desired responses from AI models.

Reactive AI refers to an approach where an artificial intelligence system reacts to immediate inputs without storing or utilizing past experiences or knowledge.

A recurrent neural network (RNN) is a type of artificial neural network that is designed to process sequential data by incorporating feedback loops, allowing information to persist and be shared across different time steps.

Seed AI refers to an initial artificially intelligent system that possesses the capability to improve its own intelligence iteratively, leading to rapid and exponential growth in its cognitive abilities.

Self-awareness refers to the ability of an artificial intelligence system to possess knowledge and understanding of its own existence, internal state, and cognitive processes.

Theory of mind (ToM) refers to the cognitive ability of an artificial intelligence system to understand and attribute mental states, such as beliefs, desires, intentions, and emotions, to itself and to other entities.

Tokenization refers to the process of breaking down a piece of text into smaller units, known as tokens, to analyze and process them individually.