Transformers

Transformers are the architecture behind ChatGPT, Claude, Gemini and most of the AI tools that have captured public attention since 2022. Introduced in a 2017 research paper famously titled "Attention Is All You Need," transformers solved a fundamental problem: how to process sequences of information - like sentences - while keeping track of how every part relates to every other part. Previous architectures processed words one at a time, left to right, which made it hard to capture long-range connections in text. Transformers process everything in parallel, using a mechanism called "attention" that lets the model weigh the importance of each word relative to all the others simultaneously. This parallel processing also made them much faster to train on modern hardware. The result is models that are remarkably good at understanding and generating language, and the architecture has since been adapted for images, audio, video and even protein structures. If there's one architecture worth understanding today, it's this one - not because it will be the final word, but because it powers the vast majority of products you're likely to encounter right now.