Uploaded September 2026 | Updated September 2026, 2 weeks ago

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How do you generate vector embeddings for an AI application?
In this Ask TOM Live session, the Oracle team explains what vectors are, how embeddings are generated, and which ONNX embedding models can be used directly with Oracle AI Database.

You will learn how to:
- Understand what vectors and embeddings represent
- Generate embeddings from text
- Display and inspect vector values
- Follow the workflow from source data to vector data
- Identify available ONNX embedding models
- Prepare for similarity search and retrieval applications

This session is designed for developers who are getting started with vector search and want to understand the embedding workflow before building an AI application.

Get started:

Getting Started with AI Vector Search LiveLab: livelabs.oracle.com/ords/dbpm/r/livelabs/view-workshop?wid=4166

Oracle AI Vector Search documentation: docs.oracle.com/en/database/oracle/oracle-database/26/vecse/ai-vector-search-users-guide.pdf

Oracle AI Database: oracle.com/database/ai-database

After watching, run the LiveLab to create embeddings and begin experimenting with vector search.

Chapters

00:00 Introduction to Oracle AI Vector Search
03:41 What is a vector?
10:43 Generating vector embeddings
17:42 Displaying a vector
23:40 The vector-generation workflow
28:58 Available ONNX embedding models
37:51 Getting started with the AI Vector Search LiveLab