Introduction to AI

This lecture is designed as a highly interactive, two-part session that balances foundational concepts with hands-on application. The first half features a structured, clinical-lens overview covering the architecture and training of neural networks, Large Language Models (LLMs), and text-to-image models, alongside a comparative analysis of AI versus biological brain structures and Artificial General General Intelligence (AGI). The second half transitions into a collaborative learning studio where participants work in small groups—potentially guided by graduate students—to explore prompt engineering techniques and actively experiment with LLM pitfalls, limitations, and deliberately manipulated responses.