AI Deconstructed
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EP20 - The Transformer Architecture: Attention is All You Need

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This episode deconstructs the 2017 paper that revolutionized AI. We go "under the hood" of the Transformer architecture, moving beyond the sequential bottleneck of RNNs to understand its parallel processing and the core mechanism of self-attention. Learn how Queries, Keys, and Values enable the powerful contextual understanding that powers all modern Large Language Models.

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