2026 Thursday Forum References and Notes

Here are the links and notes for the series of lectures on AI given at Coe’s Thursday Forum talks in February 2026. These lectures were created by me for the general public. Any mistakes in them are purely my fault. Feel free to contact me if you have any corrections of comments.

Lecture 01: How did we get here?

Lecture 02: How do Large Language Models work?

This page contains notes, further readings, and general references for the associated lecture. The Lecture Slides for the talk are also available (use your arrow keys to advance the slides) or download a pdf of the slides. If you’re looking for notes to the other lectures, head here. More about Perceptrons While we discussed perceptrons last week, we finally get to see their full power this week once we allow them to have multiple layers. There are tons of great explanations for them online, but my personal favorite is the series by YouTuber 3Blue1Brown. The entire series is worth a watch, but be warned, it’s quite long. ...

Lecture 03: What are the impacts of AI?

This page contains notes, further readings, and general references for the associated lecture. The Lecture Slides for the talk are also available (use your arrow keys to advance the slides) or download a pdf of the slides. If you’re looking for notes to the other lectures, head here. Reliability and Hallucinations We spent a good portion of the first hour discussing why models lie. The technical term is “hallucination,” and it stems from the probabilistic nature of the technology (as discussed in our previous lecture). A recent report by UX Tigers titled AI Hallucinations on the Decline gives a great breakdown of the current error rates (between 0.7% and 3%) for the major frontier models. ...