Large language models (LLMs) have emerged as a groundbreaking development in AI, akin to a new computing paradigm. LLMs can generate human-like text, perform various tasks like information gathering and data analysis, and showcase evolving capabilities, but they face security challenges and require specialized training for specific tasks.

Neural networks draw inspiration from the brain's structure and are trained to recognize patterns by adjusting their numerous trainable parameters. The Transformer architecture led to significant advancements in AI by introducing residual connections and multi-layer perceptrons for complex problem-solving.