In this episode, we discover the fascinating world of Transformers. Imagine it's the early days of AI, with RNNs and LSTMs doing the heavy lifting, but struggling with long-range dependencies like forgetful grandparents. Enter the Transformer model—a revolutionary architecture introduced in 2017 by Google’s "Attention is All You Need" paper. Transformers handle long-range dependencies and process data in parallel, making them incredibly efficient. We'll break down their key components like self-attention, positional encoding, and multi-head attention, showing how they transformed the AI landscape. Tune in to discover why Transformers are the shiny new sports car of AI models.

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