Stanford CME295 Transformers & LLMs | Autumn 2026 | Lecture 1 - Transformers

Hello everyone and welcome to CME 295 transformers and large language models. My name is Afin and I'll be teaching this class with Shervin who's in the back. So before we start, I just want to say a few words about ourselves. So Shervin and I are twin brothers and we have very similar backgrounds.

So we both went to a school in France called Central Pari and then we came to the US for grad school. So on my end I went to MIT and then Shervin came here at Stanford in the ICM department and then after that we both went to the tech industry. So we first both went to Uber

and then we went to Google and now we're both at Netflix. So Shervin and I, we like LLMs. So we've been working in the field of LLM, I would say since the early 2020s. And so that's one of the reasons why we're so lucky to be teaching this class. We've been teaching it since 2021 under various formats. But

as attention gained towards LLM, we have actually made it an actual Stanford class since last year. And this session is the third instance. And so if you're here wondering if this class is good for you. So the goal of this class is to tell you how LLM's work and in particular understand the

underlying mechanism of its architecture. So we're going to see the transformer but also how LLM are trained, how we can use them, where what they're good at, what they're not good at. So hopefully you'll be able to get a sense of all of that in this class. And in terms of the target audience, I

would say it's a pretty wide audience. So in case you want to go and be a research scientist, I would say it could be a great class to just open up the set of things that you are able to see in terms of you know what are the different techniques that are being used, what are