Stanford CS25 Transformers United Overview | Generated by AI
Question: What is the standard CS25 course? Which videos are good?
Answer:
Stanford CS25: Transformers United is a popular seminar course at Stanford University focused on Transformer architectures in deep learning. Introduced since around 2022, it has run multiple iterations (V1 to V5 as of 2025). The course explores how Transformers, since their 2017 debut in the “Attention Is All You Need” paper, have revolutionized fields like natural language processing (NLP), computer vision (CV), reinforcement learning (RL), and beyond—including applications in large language models (e.g., GPT, Gemini), image/video generation (e.g., DALL-E, Sora), biology, robotics, neuroscience, and more.
It is a 1-unit seminar (satisfactorily/no credit) with no exams or heavy homework—attendance at lectures is the main requirement. The format features guest lectures from leading researchers (e.g., Geoffrey Hinton, Ashish Vaswani—one of the original Transformer authors, Andrej Karpathy, and experts from OpenAI, Google, NVIDIA). Lectures are often livestreamed, recorded, and publicly available, attracting millions of YouTube views. Prerequisites include basic deep learning knowledge and understanding of attention mechanisms (or prior courses like CS224N, CS231N, or CS230).
There is no fixed “standard” syllabus across versions, as each iteration (e.g., V4 in 2024, V5 in 2025) updates with the latest breakthroughs and new guest speakers. Topics typically include:
- History and overview of Transformers
- Scaling laws and architecture variants
- Transformers in language, vision, multimodal models, diffusion, audio, etc.
- Advanced topics like Mixture of Experts (MoE), retrieval-augmented generation, decision Transformers, and real-world applications
All recorded lectures are excellent due to the high-caliber speakers, but particularly recommended ones (based on popularity, foundational value, and speaker prominence) include:
- Introduction/Overview lectures: Great starting points (e.g., Andrej Karpathy’s “Introduction to Transformers” from V2, or the overview talks in V4/V5).
- Andrej Karpathy’s talk: Highly engaging intro to Transformers.
- Ashish Vaswani: As a co-author of the original paper, his insights are invaluable (appears in some versions).
- Geoffrey Hinton: Deep perspectives on AI and Transformers.
- Other standouts: Talks on scaling laws, multimodal models, diffusion with Transformers, and specific applications.
The full collection of lectures from all versions is available in one YouTube playlist (continuously updated with new versions).
To get the most out of it, start with an overview lecture, then watch guest talks on topics of interest.
References:
- Official Course Website
- YouTube Playlist: Stanford CS25 - Transformers United
- Andrej Karpathy Introduction (V2 Example)
- Overview of Transformers (V5 Example)
- Overview of Transformers (V4 Example)