Vector Databases Demystified

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Join us on Wednesday, 10/25 at 2pm ET (11am PT) for a Data Demo about vector databases!

Vector databases are specialized databases designed to store and manage vector data, often in the form of embeddings.

Crucially, these embeddings capture the semantic essence of the content, ensuring that items with similar meanings are represented by vectors that are closely positioned in the embedding space. Vector databases also support large-scale vector operations such as similarity search and comparison, enabling the next generation of AI applications.

Instructor Brian Spiering will guide you through the basics of vector databases and a few use case scenarios, so don’t miss it!

Key Takeaways:

• Learn the basics of vector databases
• Query OpenAI’s API to retrieve vector embeddings
• How to use those embeddings to solve real business problems
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Great lecture. Is it possible to recreate the original input from the embedding, if you lose the original input?

gecarter
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Does the fixed vector size, limit the size of the input string to be embedded?

gecarter