Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.
Explores vacuum energy during inflation and the dynamics of scalar and vector fields, emphasizing the importance of seeking clarification and providing details about upcoming exams.