This unit turns from human cognition to the machines themselves. You will start with the material basis of computing (materials, electricity, transistors, chips, and logic) and its physical costs in energy, water, minerals, and supply chains, before tracing how AI changed over time, from rules and symbolic AI to learned patterns.

A career bridge midway through connects technological change and labor markets to your life after college, asking how the same forces reshaping computing also reshape the job market you are entering.

We close the unit with the shift from programmed rules to learned patterns: what training, models, prediction, and GPUs actually do, and what generative AI and large language models are doing when they predict, tokenize, and generate.

Fall 2026 dates: Tue, Sep 8 - Thu, Sep 24

Meeting sequence:

1. How Do Computers Compute?
2. Computing Is Physical
3. How Did AI Change Over Time?
4. How Do Technological Change and Labor Markets Shape Life After College?
5. What Changed With Machine Learning and Neural Networks?
6. What Are Generative AI and LLMs Actually Doing?

By the end of this unit, you should be able to describe how computing works materially and historically, and distinguish what generative AI and LLMs are technically doing from what they are popularly claimed to do.