Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for your GenAI Apps
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The document introduces Milvus Lite, a lightweight vector database designed as a Python library, highlighting its role in enhancing semantic search capabilities for unstructured data. It discusses the evolution of AI technologies that have facilitated advancements in semantic analysis, including the use of vectorization techniques. The presentation outlines the ease of setup and operation for developers looking to implement Milvus Lite without complex infrastructure like Docker or Kubernetes.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for your GenAI Apps
- 1. 1 | © Copyright 2024 Zilliz 1 1 | © Copyright 9/25/23 Zilliz 1 | © Copyright 9/25/23 Zilliz Speaker Jiang Chen Ecosystem & Developer Experience jiang.chen@zilliz.com @jiangc1010
- 2. 2 | © Copyright 2024 Zilliz 2 Introduction to Milvus Lite A lightweight vector database as Python library Jiang Chen @ Zilliz
- 3. 3 | © Copyright 2024 Zilliz 3 The evolution of AI made the semantic search of unstructured data possible Search by Probability Statistical analyses of common datasets established the foundation for processing unstructured data, e.g. NLP, and image classification AI Model Breakthrough The advancements in BERT, ViT, CBT etc. have revolutionized semantic analysis across unstructured data Vectorization Word2Vec, CNNs, Deep Speech pioneered unstructured data embeddings, mapping the words, images, videos into high-dimensional vectors
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- 5. 5 | © Copyright 2024 Zilliz 5 01 Why We Built Milvus Lite CONTENTS 02 How Does It Work RAG in action with Milvus Lite 03
- 6. 6 | © Copyright 2024 Zilliz 6 Scalability is great, but I don’t want Docker or K8s yet
- 7. 7 | © Copyright 2024 Zilliz 7 How about this dead simple setup?
- 8. 8 | © Copyright 2024 Zilliz 8 How it works？
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- 11. 11 | © Copyright 2024 Zilliz 11 Let's see it in action!
- 12. 12 | © Copyright 2024 Zilliz 12 T H A N K Y O U