Locality-Sensitive Hashing (LSH) tackles one of computing's toughest challenges—efficiently finding similar items in massive, high-dimensional datasets. By intentionally maximizing hash collisions for 'near neighbors,' LSH slashes search times, powering everything from recommendation engines to cybersecurity tools. This probabilistic technique reshapes how developers handle similarity search in AI, genomics, and beyond.