GenAI LLMs rely on data-driven learning, leveraging vast datasets to model language patterns, semantics, and contexts through unsupervised or semi-supervised methods. This enables scalability and adaptability, unlike rule-based systems or human-dependent approaches. Large datasets drive generalization, though they introduce security challenges like data quality control. Exact extract: "A key concept of GenAI LLMs is data-driven learning with large-scale datasets, enabling robust language modeling." (Reference: Cyber Security for AI by SISA Study Guide, Section on GenAI Development Principles, Page 60-63).