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2025 DBT Database 19c January Meet-Up

Welcome to our Database and Technology Database 19c Meet-up calls! We’re excited to have you join us as we connect and share insights. These calls are designed specifically for our valued customer users, fostering a vibrant community where knowledge and experiences are exchanged.

To ensure you can fully participate, please follow these simple steps (if you have an account, skip to step 2):

Step 1: Create a Quest login: 1. Click on the following link: New To Quest

2. Select “New to Quest” on the page.

3. Fill in your personal information as requested, ensuring to select “Customer User” from the dropdown menu under Company Info.

4. Click “Next” to proceed. Once you’ve completed the form, you’ll receive a verification email. Please follow the instructions in the email to activate your account. Step 2: Join the DB&T – Oracle Database 19c Community: After creating your Quest account, join our DB&T – Oracle Database 19c SIG Community and DB&T Community News & Events pages. Stay informed by setting up your notifications for the group, ideally to at least weekly.

Step 3: Register for upcoming events:

1. Navigate to the Upcoming Events menu tab.

2. Click on the event you wish to attend.

3. Enter your full name and email address.

4. Look out for a Zoom meeting confirmation email, and make sure to add the details to your calendar.

 

AI for Data: Vector search in Oracle Database 23ai

 

A key AI feature introduced in Oracle database 23ai is the vector search. A vector is an array of numbers that represent the semantic content of data, instead of the words, pixels in the images. Vectors allow us to do the similarity search of the data based on the semantic contents. In this session, we will take a look at the vector search feature in Oracle 23ai database: how to store vector data in the database and how to do the similarity search using vector_distance function in a simple select query. We also will discuss how the vector search improves Generative AI and LLM and address the hallucination issue by augmenting prompts with private database content. we will discuss the two vector embedding generations methods that we can use to generate vectors to the Oracle 23ai database for the unstructured data such as words , images etc: 1) Database native DBMS_DATA_MINING procedure to import ONNX(Open Nural Network eXchange embedding models ; 2) embedding models in LangChain. Using some examples, we will discuss using the LangChain framework for developing applications with Large Language Models (LLMs) and Using Oracle AI Vector Search to store and search vectors in Oracle Database 23ai.

 

Bio:

 

Kai has worked in Dell Technologies as a Distinguished Engineer leading the Oracle database solutions engineering for more than 22 years. Kai has more than 30 years of experience in tech industry, specializing in Oracle Database, Cloud and AI and Machine Learning. Kai is a frequent speaker at global Oracle and IT conferences and co-authored two Apress books: “Expert Oracle RAC 12c “ and “Machine Learning for Oracle Database Professionals”. Kai has been an Oracle ACE Director since 2010. Currently Kai is an independent principal consultant focusing on Oracle database and AI/ML.

 

We can’t wait to see you at our next meet-up! If you have any questions or need assistance at any point, don’t hesitate to reach out.