Introduction to Transformers

Dive into a comprehensive lecture on the fundamentals of Transformer models, delivered by Daniel Hsu from Columbia University as part of the Special Year on Large Language Models and Transformers: Part 1 Boot Camp at the Simons Institute. Explore the architecture, mechanisms, and applications of these groundbreaking neural network models that have revolutionized natural language processing and beyond. Gain insights into the key components of Transformers, including self-attention and positional encoding, and understand their impact on various AI tasks. This 70-minute talk provides a solid foundation for both beginners and intermediate learners looking to grasp the core concepts behind one of the most influential innovations in modern machine learning.