VentureBeat November 16, 2024
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.
How our brains already think in vectors
Think of vectors as GPS coordinates for ideas. Just as GPS uses numbers to locate places, vector databases use mathematical coordinates to map concepts, meanings and relationships....
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