"Attention Is All You Need." -- Vaswani, 2017

The Path So Far

We started with a single neuron drawing a line. Added hidden layers to bend it. Taught the network to learn its own weights. Scaled training with mini-batches and Adam. Fought overfitting with dropout. Built filters for images. Gave networks memory for sequences. Replaced compression with attention.

Each architecture solved a problem the previous one couldn't. Each carried forward what worked and discarded what didn't.

The Personal Connect

In Attention blog post, I described how I used to compose sentences in Tamil first, then translate word by word into English. It was slow, sequential, and lossy. When I finally started thinking directly in English, everything changed. I wasn't translating anymore. I was processing meaning, grammar, and context all at once, shaped by everything I'd read and heard before.

That shift, from sequential translation to parallel understanding, is exactly what the Transformer does.…