Module 2: The Encoder (BERT) vs. The Decoder (GPT)

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Recorded05 Jan 2026

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Handlerec:15129812

Show notes

Shay breaks down the encoder vs decoder split in transformers: encoders (BERT) read the full text with bidirectional attention to understand meaning, while decoders (GPT) generate text one token at a time using causal attention. She ties the architecture to training (masked-word prediction vs next-token prediction), explains why decoder-only models dominate today (they can both interpret prompts and generate efficiently with KV caching), and previews the next episode on the MLP layer, where most learned knowledge lives.

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