attention

The attention mechanism sits at the heart of modern transformers, enabling models to weigh the importance of different input elements when processing sequences. Yet this powerful mechanism comes with a significant cost: memory consumption that scales quadratically with sequence length. For a sequence of 8,192 tokens, standard attention requires storing an 8,192 × 8,192 attention … Read more

Attention mechanisms represent one of the most transformative innovations in artificial intelligence, fundamentally changing how neural networks process information. While the mathematics behind attention can seem abstract, the core concept mirrors how humans naturally focus on relevant information while filtering out noise. Understanding attention mechanisms explained with real-world examples makes this powerful technique accessible, revealing … Read more