2024-04-12: Matrix Minds: RNNs Level Up
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💊 Matrix Minds: RNNs Level Up
The Transformer architecture, the bedrock of AI since 2017, is starting to show its limitations. While undeniably powerful, its reliance on self-attention mechanisms leads to a critical bottleneck: quadratic scaling of computational resources as the input sequence length increases. This means that processing longer pieces of text, code, or any sequential data requires much more compute power, energy, and time.
