Our brains are vector databases — here's why that's helpful when using AI
In 2014, a breakthrough at Google transformed how machines understand language: The self-attention model. This innovation allowed AI to grasp context and meaning in human communication by treating words as mathematical vectors — precise numerical representations that capture relationships between ideas. Today, this vector-based approach has evolved into sophisticated vector databases, systems that mirror how our own brains process and retrieve information. This convergence of human cognition and AI technology isn't just changing how machines work — it's redefining how we need to communicate with them.