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September 13-16, 2022
Dublin, Ireland + Virtual
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Friday, September 16 • 14:50 - 15:30
The Evolution of Milvus: A Cloud-Native Vector Database - Frank Liu, Zilliz

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The total amount of digital data generated worldwide is increasing at a rapid rate. Simultaneously, approximately 80% (and growing) of this newly generated data is unstructured data - data that does not conform to a table- or object-based model. Examples of unstructured data include text, images, protein structures, geospatial information, and IoT data streams. Despite this, the vast majority of companies and organizations do not have a way of storing and analyzing these increasing large quantites of unstructured data. Embeddings - high-dimensional, dense vectors which represent the semantic content of unstructured data - can remedy this. Armed with this knowledge, it's clear that the mobile/IoT era necessitates a new type of cloud-native, fully distributed database purpose-built to store, search, and index large quantities of embedding vectors: Milvus.

In this presentation, we'll introduce the design of Milvus 2.0 - the world's most popular open-source vector database trusted by over 1000 organizations. Milvus 2.0 represents a complete paradigm shift in the underlying vector database architecture - cloud-native, horizontally scalable, and fully distributed. We will also briefly discuss the evolution from Milvus 1.0 to 2.0 and share various real-world use cases and applications.
Speakers
avatar for Frank Liu

Frank Liu

Director of Operations & ML Architect, Zilliz
Frank Liu is the Director of Operations and ML Architect at Zilliz with over 8 years of industry experience in machine learning and hardware engineering. Prior to joining Zilliz, Frank co-founded an IoT startup based in Shanghai and worked as a ML Software Engineer at Yahoo in San... Read More →

2022 oss eu milvus pdf
Friday September 16, 2022 14:50 - 15:30 IST
Wicklow Meeting Room 2 (Level 2)
  Open AI & Data Forum, Data (Versioning + Format + Pipeline Management + Stream Processing + SQL Engines + Feature Engineering + Visualization + Governance + Labeling)