#Transformer

The story of the deep learning revolution from the AlexNet moment through the development of the Transformer, told as a narrative of rapid, cascading discovery in which one breakthrough enabled the next. The fastest scientific revolution in the history of AI — and what it actually means that machines can now do what only humans could do before.

The full intellectual story of the Transformer architecture — why self-attention was the right idea, how it enabled the pre-training revolution, and why scaling Transformer models produced capabilities that nobody predicted and nobody fully understands. The architecture at the heart of every large language model in existence, and what it reveals about the nature of language, intelligence, and learning at scale.

The full story of the 'Attention Is All You Need' paper — how a Google Brain team developed a new architecture for sequence modelling that discarded recurrence entirely, why it worked better than everything that came before, and how it became the foundation for every large language model in existence. The paper that made GPT possible, and the elegant idea at its heart.