🤯 IN YOUR FACE. FOR ANYBODY

🖥️ Modern slidedecks for topics in physics and data science

This is a collection of lively, engaging, accessible slidedecks on topics in physics and data science created by Andrew Fowlie (andrew.fowlie@xjtlu.edu.cn) for you to read, enjoy, adapt and share. They are licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence. That means you are free to share and adapt them, provided you give appropriate credit.

They are written in XeTeX using the beamer package, and the full source is provided as a zip file.

⚛️ Quantum Mechanics In Your Face For Anybody

SLIDEDECK

Welcome to my slidedeck on Quantum Mechanics for a non-mathematical audience — Quantum Mechanics In Your Face For Anybody! There are no equations and little maths beyond percentages. The key conceptual differences between Quantum and Classical Physics are here, though, and these topics require attention and serious thought.

The title alludes to two wonderful expositions of quantum mechanics by the masters. Mermin and Coleman are both physicists’ physicists: they aren’t widely known to the public, but they contributed tremendous insight and clarity. Feynman described Mermin’s paper as “one of the most beautiful papers in physics.” You are encouraged to read Bringing Home the Atomic World: Quantum Mysteries for Anybody
and watch Sidney Coleman’s Dirac Lecture: “Quantum Mechanics in Your Face”.

🤖 Chatbots In Your Face For Anybody

SLIDEDECK

I take a fun look at the history and workings of chatbots, starting from the 1960s rule-based models such as ELIZA up to present transformer-based large language models such as ChatGPT. I will explain the principles and working parts of these models as simply as I can, and with as little maths as I can, whilst hopefully retaining substantive and interesting explanations.

No prior knowledge of machine learning or advanced maths is required; some linear algebra would help, but come even if you don’t know any. By the end of the talk, we should have an understanding of the whole pipeline of a GPT from input to output, including how input text is represented in maths, why attention matters, what a transformer is, and why chatbots hallucinate.