Transformers : Attention Is All You Need (The Birth of Transformers)
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Transformers : Attention Is All You Need (The Birth of Transformers)
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About this listen
In this first episode of AI Papers Explained, we explore one of the most influential research papers in the history of deep learning: Attention Is All You Need (Vaswani et al., 2017).
You’ll learn why the Transformer architecture replaced RNNs and LSTMs, how self-attention works, and how this paper paved the way for models like BERT, GPT, and T5.
🎙️ Hosted by Anass El Basraoui, a Data Scientist and AI researcher.
Topics covered:
- Scaled dot-product attention
- Multi-head attention• Encoder–decoder structure
- Positional encoding
- The legacy of the Transformer
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