From the course: Introduction to Spring AI
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Spring AI: Embedding models AI - Spring Framework Tutorial
From the course: Introduction to Spring AI
Spring AI: Embedding models AI
- [Instructor] What are embedding models? Embedding models are a type of AI model trained to convert textual data into numerical representations, called vectors. These vectors capture the semantic meaning and relationships within the text data in a way that facilitates efficient search, retrieval, and analysis. There are a few benefits of embedding models in Spring AI, so let's walk through the three that come to mind. And that starts off with customizable AI solutions. So unlike pre-trained models, embedding models allow you to train them on your own data. This is major. This enables you to create functionalities tailored to your specific domain or application needs. So just think, you could build a search engine for your company's internal documents, or a chat bot trained on your product knowledge base. The next is enhanced search and retrieval. By converting text data into vectors, embedding models allow for efficient similarity search. You can search for documents or concepts…
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