When I started writing this, I thought I’d explain transformers. Maybe build a few models. Call it a day.
That’s not what happened.
Every section led to another question. How do we make it follow instructions? How do we make it think? Can it generate images too? Each answer opened three more doors. (That’s how learning works, I suppose.)
So here’s where we are: you understand transformers. Not the hand-wavy “attention is like looking at things” version. The real thing. You’ve built them, trained them, fine-tuned them, taught them to reason, and used them to turn noise into pictures.
That’s not nothing.
But it’s also not everything. This field moves faster than I can type, and there’s more to explore:
Multimodal architectures (because why limit ourselves to one modality?)
Efficient inference (because not everyone has a data center)
Agentic systems (because generation is just the beginning)
Whatever the next paper drops that changes everything (again)
New sections will appear as I figure them out. That’s the deal. I’m learning too.
If you made it this far, thanks. Seriously. Now go break something interesting.