CS 25:
Transformers United V4
Since their introduction in 2017, Transformers have taken the world by storm, and are finding applications all over Deep Learning. They have enabled the creation of powerful language models like ChatGPT and Gemini, and are a critical component in other ML applications such as text-to-image and video generation (e.g. DALL-E and Sora). They have significantly elevated the capabilities and impact of Artificial Intelligence. In CS 25, which has become one of Stanford's hottest and most exciting seminars, we examine the details of how Transformers work, and dive deep into the different kinds of Transformers and how they're applied in various fields and applications. We do this through a combination of instructor lectures, guest lectures, and classroom discussions. Potential topics include LLM architectures, creative use cases (e.g. art and music), healthcare/biology and neuroscience applications, robotics and RL (e.g. physical tasks, simulations, or games), and so forth. We invite folks at the forefront of Transformers research for talks, which will also be livestreamed and recorded through YouTube/Zoom. Past speakers have included Andrej Karpathy, Geoffrey Hinton, Jim Fan, Ashish Vaswani, and folks from OpenAI, Google DeepMind, NVIDIA, etc. Our class includes social events and networking sessions and has a popular reception within and outside Stanford, with around 1 million total views on YouTube. This is a 1-unit S/NC course, where attendance is the only homework! Please enroll on Axess or audit by joining the livestream (or in person if seats are available). Prerequisites: basic knowledge of Deep Learning (should understand attention) or CS224N/CS231N/CS230. Course website: https://web.stanford.edu/class/cs25/
Terms: Aut, Spr
| Units: 1