What are the functions used to chunk and generate embeddings in Oracle Database 23ai?

The functions used to chunk and generate embeddings in Oracle Database 23ai are accurately identified in the choice that refers to VECTOR_CHUNK and VECTOR_EMBEDDING.

VECTOR_CHUNK is designed to divide input data into smaller, manageable pieces, or chunks, which is an essential step for effectively processing large datasets. This function helps ensure that the data can be analyzed or transformed appropriately before moving on to the embedding stage.

VECTOR_EMBEDDING plays a crucial role in the generation of embeddings. It converts the processed data chunks into a numerical format that can be used for various machine learning tasks, such as similarity search and clustering in the context of AI vector searches. This process transforms textual or other types of data into vectors, which are mathematical representations that preserve the context and meaning of the original data.

The combination of these two functions provides a reliable approach to prepare and manipulate data, making them integral to the workflow in Oracle Database 23ai for applications involving AI and data processing.