> For the complete documentation index, see [llms.txt](https://ai-community-iitb-organization.gitbook.io/10-days-realtime-llm-bootcamp/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai-community-iitb-organization.gitbook.io/10-days-realtime-llm-bootcamp/word-vectors-simplified/what-is-a-word-vector.md). # What is a Word Vector Before diving into the intricacies of Large Language Models, it's crucial to understand the building blocks: Word Vectors. Imagine language as a multi-dimensional space; each word takes up a specific point within that space. That's what word vectors do; they represent text in numerical form to make it comprehensible for LLMs. In the accompanying video, Anup Surendran lays down the foundation for understanding LLMs by answering key questions: * What do LLMs stand for? * What exactly are Word Vectors? {% embed url="" %} ## --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://ai-community-iitb-organization.gitbook.io/10-days-realtime-llm-bootcamp/word-vectors-simplified/what-is-a-word-vector.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.