// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM

Multi-Modal

AI models that can understand and generate content across different types of data, such as text, images, audio, and video, not just one type.

TECHNICAL DEFINITION

Multi-modal AI models are capable of processing, interpreting, and generating information across multiple distinct modalities, such as text, images, audio, and video, enabling a holistic understanding and interaction with diverse data types.

BACKGROUND

Prompt injection is a cybersecurity exploit and an attack vector in which innocuous-looking inputs are designed to cause unintended behavior in machine learning models, particularly large language models (LLMs). The attack takes advantage of the model's inability to distinguish between developer-defined prompts and user inputs to bypass safeguards and influence model behaviour. While LLMs are designed to follow trusted instructions, they can be manipulated into carrying out unintended responses through carefully crafted inputs.

READ MORE ON WIKIPEDIA

SYNONYMS & ALIASES

  • Cross-modal AI
  • Multi-sensory AI
  • Unified AI

USAGE NOTE

Multi-modal models are advancing applications like image captioning, video summarization, and AI assistants that can see and hear.

RELATED TERMS IN PROMPTING & LOGIC