Embeddings in LLMs Explained: How Text Becomes Meaningful Numbers
Embeddings in LLMs: A Beginner's Guide 1. What is an Embedding? An embedding is a way of converting text into a list of numbers called a vector . For example: "cat" is converted into something like: [0.21, -0.45, 0.78, 0.12, ...] These numbers represent information about the text in a form that a computer can mathematically work with. The important idea is: Embedding converts text into numbers so that computers can compare the meaning of different texts. 2. Why Do We Need Embeddings? Computers cannot directly compare the meaning of sentences the same way humans do. Consider these sentences: "I love dogs." "I really like puppies." The words are different, but their meanings are similar. An embedding model converts both sentences into vectors: "I love dogs." [0.21, 0.45, 0.78,...
