Why Modern AI Made Attention Cheaper

As Large Language Models scale to longer contexts and more attention heads, one hidden bottleneck starts to dominate: memory. Every attention head stores its own keys and values, and during inference, that data grows rapidly with the sequence length. Without optimization, long conversations would quickly become impractical. In this video, we explore Grouped Query Attention (GQA), a simple but powerful optimization used in modern models like LLaMA 2 and Mistral to dramatically reduce attention memory usage without sacrificing performance. You’ll learn: - Why multi-head attention becomes…