What is the nature of Intelligence? How can we build intelligent machines? What is the role for humans in an AI world? While neuroscience, philosophy, and psychology all provide insights into these questions, this course will focus on the Big Ideas based the last 60+ years of AI research. We will seek to understand the foundations of machine learning (supervised, unsupervised, and self-supervised), state-space search, representation languages, the power of scale up, and other Big Ideas leading up to the new generation of models such as GPT-4.

Disclaimer: this course is being offered for the second time. It’s very different from previous offerings by a different instructor.

General information

• Instructor: Oren Etzioni, email: etzioni@cs
• TA: Kevin Farhat, email: kevinf7@cs
• Time: Tuesdays, 3:30 PM - 4:50 PM
• Location: CSE2 Room 271, except on 10/29, which will be in CSE2 G04

Expectations

1. Complete the readings before class.
2. Post writing assignments on the discussion board (use of a “GPT” is completely ok).
3. Be physically and mentally present in all class meetings (can miss at most 1).
4. Contribute to class discussions (including follow up on the discussion board).
5. No screens (phone or laptop) in class.

Topics/questions (evolving)

1. AI, The Big Questions
2. Computational Thinking—what is AI thinking?
3. GPT---what are the key AI ideas here?
4. Supervised learning
5. Scaling
6. Self-supervised learning
7. What’s next for AI?