Part 3/14:

Despite these progressions, scaling knowledge graphs to keep pace with evolving data remained challenging. Enter large language models (LLMs) and vector search, which started gaining momentum around 2013 and 2020 respectively, culminating in the latest AI-powered search systems.

Embeddings: The Foundation of Semantic Understanding

At the core of modern AI are embeddings—dense numerical vectors that represent words, sentences, images, code snippets, or other data forms in a multi-dimensional space. An embedding captures the meaning or semantics of the data, allowing computational systems to perform similarity comparisons.

What are embeddings?