Description
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What’s actually happening when you chat with an AI? This opening lecture demystifies large language models from the ground up — tokens, neural networks, weights and layers, and the two-stage journey from training to inference that turns raw text into a working chatbot. Along the way we introduce the concepts (context windows, transformers, attention) that explain both what makes modern AI so capable and why it still confidently gets things wrong, including hallucination, sycophancy, and the pull to anthropomorphize a fundamentally statistical tool. No coding or technical background required — by the end, you’ll have a working mental model for what AI can and can’t do, which every later lecture builds on.
Speaker: Cynthia Bailey
Cynthia Bailey is a Senior Lecturer in the Computer Science Department at Stanford University. In 2023-2024, she served as an AI Policy Fellow in the United States Senate through the American Association for the Advancement of Science (AAAS). Her scholarship focuses on computer science education, AI/machine learning, and the social impacts of technology. This work includes creating groundbreaking courses such as Equity and Governance for Artificial Intelligence and Race and Gender in Silicon Valley. Her teaching and research awards include the Lloyd W. Dinkelspiel Award for exceptional contributions to undergraduate education at Stanford, the Lasting Impact Award from the International Computing Education Research conference, a "Top 10 Papers of All Time" award at the 50th anniversary of the ACM SIGCSE Technical Symposium, and the Stanford Society of Women Engineers' Professor of the Year. She has consulted for Apple, NASA, law firms, and machine learning startups. She holds a Ph.D. in Computer Science from UC San Diego.
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