Stacking the Blocks: Building Deep Understanding

A single Transformer Block is powerful, but true comprehension requires depth. To achieve this, models stack these blocks one on top of the other, forming multiple layers. The output of the first block becomes the input for the second, and so on.

Each layer in the stack refines the model's understanding at a different level of abstraction. Think of it like a team of editors reviewing a document:

• Early Layers (The Copyeditors): The first few blocks focus on local patterns and basic grammar. They figure out that in "the rocket landed," "rocket" is the subject of the verb "landed."
• Middle Layers (The Content Editors): These blocks build on that foundation to understand semantic meaning. They ask, "What is this sentence actually about?" and form a coherent picture of events.
• Later Layers (The Senior Analysts): The final blocks in the stack integrate context from across the entire document. They grasp abstract themes, nuance, and long-range connections.

By passing the text through this multi-layered stack, the model builds an incredibly rich understanding. A model like GPT-3 has a stack of 96 layers (blocks)! This depth is the key to its powerful reasoning abilities.