Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for your GenAI Apps

1 | © Copyright 2024 Zilliz
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1 | © Copyright 9/25/23 Zilliz
1 | © Copyright 9/25/23 Zilliz
Speaker
Jiang Chen
Ecosystem & Developer Experience
jiang.chen@zilliz.com
@jiangc1010

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Introduction to Milvus Lite
A lightweight vector database as Python library
Jiang Chen @ Zilliz

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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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01 Why We Built Milvus Lite
CONTENTS
02 How Does It Work
RAG in action with Milvus Lite
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Scalability is great, but I don’t want Docker or K8s yet

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How about this dead simple setup?

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How it works？

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Let's see it in action!

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T H A N K Y O U

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for your GenAI Apps

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Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for your GenAI Apps