Semantic search in generative AI refers to the system's ability to understand and process user queries based on intent and contextual meaning rather than just relying on keywords. This enables applications to generate content that aligns with the user's intent and context, such as generating a story based on a specific theme. Semantic search plays a vital role in generative AI, streamlining operations, empowering informed decision making, and enriching the overall user experience. It is critical for any system to understand user queries and present them in a more accurate format. The essence of semantic search lies in its ability to capture the subtleties of human language, reshaping our access to and interaction with digital information. Companies such as Amazon, Google, Microsoft, and SingleStoreDB are integrating semantic search functionality into their platforms, enabling applications to perform semantic queries that understand the context and nuance of user queries, delivering precise and relevant results at speed. Semantic search represents a monumental leap in how we interact with the digital world, redefining the boundaries of user engagement and information retrieval, promising a more intuitive, efficient, and contextually aware landscape for users to explore the depths of human knowledge.