Transformer Architecture

Let’s start with a basic question: How can a computer ‘understand’ and generate text? Over the years, we’ve relied on various neural network structures—such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)—to tackle language problems. Then a new architecture arrived: the Transformer. It revolutionized the field so dramatically that most cutting-edge Large Language Models (LLMs) today, including GPT, BERT, and T5, are built with some variation of the transformer.

That said, it’s important to note that not all state-of-the-art LLMs use the same transformer layout:

• GPT (Generative Pre-trained Transformer) is primarily decoder-only.

• BERT is an encoder-only model.

• T5 (and many other text-to-text models) still employs a full encoder-decoder approach.