2800 - 向量数据库和检索增强生成 (RAG)：利用 Milvus 和 WatsonX 为 AI 赋能.pdf

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1、 2025 IBM Corporation1Dale McInnisIBM,Principal Data&AI Technical SpecialistAn Introduction to Vectors with Db2,Milvus and watsonx.data 2025 IBM Corporation2What are Vector databases?It is a database designed to store,manage,and search vector data,allowing for highly efficient and fast similarity se

2、arches With an image or audio search,data with similar characteristics to a vector can be retrieved quicklyWhats the difference between a Whats the difference between a Vector DB vs Regular DB?Vector DB vs Regular DB?A vector database is a collection of data stored as mathematical representations.Ve

3、ctor databases make it easier for machine learning models to remember previous inputs,allowing machine learning to be used to power search,recommendations,and text generation use-cases.2025 IBM Corporation3157,153,174,161,155,156DimensionsTypes of Embeddings1.1.ImagesImages2.2.TextText3.3.AudiosAudi

4、os4.4.VideosVideos5.5.Multimodal dataMultimodal dataHow can my client create How can my client create vector embeddings today?vector embeddings today?Clients may convert their data into embeddings using AI models from open-source frameworks like PyTorchVector Embedding Concepts A vector embedding is

5、 the internal representation of input data in a deep learning modelThey are a way to convert words and sentences and other data into numbers that capture their meaning and relationships DimensionsThe dimensionality of a vector embedding is equivalent to the lengthof a vector Segment SizeTo easily pr

6、ocess data,Milvus segments the data into smaller segmented data filesThe segment size is determined by the index file size of the embeddings Index ParametersSetting key parameters with Milvus for operations(e.g.,creating a table)The number of parameters can affect search performance.2025 IBM Corpora