Large Language Model
A neural network model with billions of parameters trained on vast amounts of text data, capable of understanding and generating human-like text across a wide range of natural language tasks.
In plain language
A massive AI trained on enormous amounts of text that can understand and generate human-like language. ChatGPT, Claude and Gemini are examples. They're called "large" because they have billions of parameters or weights.
Why this matters
Large language models present unique governance challenges due to their broad capabilities, potential for misuse and tendency to generate plausible-sounding but false information. Your AI governance framework must address LLM-specific risks including hallucination, prompt injection, data leakage, bias amplification and inappropriate content generation.
Relevance
GovernanceLLMs' broad capabilities and susceptibility to harmful use require governance controls tailored to their specific risks.
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