Paper Breakdowns
Plain-language walkthroughs of the papers that shaped modern AI — the core idea, the results that mattered, and how it connects to what you already know.
Attention Is All You Need — the transformer, explained
Attention Is All You Need
The 2017 paper that replaced recurrence with self-attention and set the template for every large language model since.
Read breakdownBERT — bidirectional pretraining for language understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
How masked-language-model pretraining gave encoders deep bidirectional context and reset the NLP benchmark board.
Read breakdownGPT-3 — language models are few-shot learners
Language Models are Few-Shot Learners
The paper that showed scale alone lets a single frozen model learn new tasks from a few in-context examples.
Read breakdown