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In this episode, I discuss Transformers and the role of Attention in Deep Learning and everything one needs to know about them!
Especially how they changed the usual AI research course of aligning towards more inductive bias in neural nets (CNNs with their locality bias, RNNs with their recency bias) and embraced a more general, but data-hungry architecture.
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Check out the previous two videos on Attention and Self Attention that covers a lot of the groundwork behind this video:
• Neural Attention - Thi...
• The many amazing thing...
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Useful papers:
arxiv.org/abs/1706.03762
arxiv.org/abs/1409.0473