Conscious Engines
Story of Attention - Part 1: Before the Transformer
From n-gram counting and RNNs to the first attention mechanisms.
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Experiments in model architecture, training, evaluation, and efficient inference
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Story of Attention - Part 1: Before the Transformer
Conscious Engines
From n-gram counting and RNNs to the first attention mechanisms.
guide
Story of Attention - Part 2: Attention All You Need
Conscious Engines
How scaled dot-product attention, multi-head attention, and positional encoding built the Transformer.
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Story of Attention - Part 4: Sparse Attention, Then and Now
Conscious Engines
How sparse attention makes long-context processing more efficient.
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Story of Attention - Part 3: KV-Cache Bottleneck: MQA and GQA
Conscious Engines
How MQA and GQA reduce the memory cost of Transformer inference.
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Story of Attention - Part 5: Linear Attention: Kernels, Decay, and Gating
Conscious Engines
How kernels, decay, and gating make attention scale linearly.
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Story of Attention - Part 6: Where Attention Stands Today
Conscious Engines
How latent compression and differential attention shape modern language models.
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