Units: 4
Hours: Lecture, 3 hours; research, 3 hours
Catalog page 357
Prerequisites: EE 228, EE 242A, CS 224, CS 228; graduate standing; or consent of instructor
Description: Explores key concepts in foundation models and recent advances in AI. Covers model architectures such as attention, transformers, and state space models; training pipelines including pretraining, fine-tuning, and reinforcement learning from human feedback; data acquisition strategies; tool augmentations; multimodal models; and techniques for efficient training and inference.