Azure OpenAI on your own data

With the current previews, the Azure OpenAI services can now also be used for own data. The following example shows the Azure services that are required for this.

Required services:

The following services are required and must be used in combination with each other:

• Azure OpenAI
• Azure Cognitive Search Index

As of June 2023, Azure OpenAI is still in preview and you need to sign up for the preview to use the features. Azure Cognitive Search is available by default.

Azure Cognitiv Search

First, an instance of Azure Cognitive Search needs to be provisioned. How to do this is described here: Create an Azure Cognitive Search service in the portal.

The next step is to configure where the data that should be indexed is located. There are various options for this, all of them results in an index in the newly created Azure Cognitive Search instance. On the Overview page, you will find the link "Connect your data -> Learn more", which provides a good overview of the options:

For testing scenarios, demo data provided by Microsoft can also be used. The "Import" button takes you to the currently available options:

Especially for customers whose data is stored in M365 / SharePoint Online and Teams, the option "SharePoint Online" is very interesting. Currently, this option is still in preview and cannot be used via the UI. How Azure Cognitive Search can currently be used to index data in SharePoint Online is described here: Index data from SharePoint document libraries.

In my example I use the demo data "hotel-sample" that Microsoft provides:

The index contains the following fields:

These fields can now be used in Azure OpenAI.

Azure OpenAI

As soon as an instant of Azure OpenAI is created / available, the Azure OpenAI Studio is also available. This is where you have the options "ChatGPT-Playground":

In the "ChatGPT-Playground" you can now work either with the data from the general Language Model GPT or with your own data:

To use your own data from the first step "Azure Cognitive Search" you have to select the corresponding details:

The "Index data field mapping" in the next step is optional, but recommended because it increases the quality of the answers significantly. In the example with the "hotel-sample" demo data it looks like this:

This can then be used to generate texts based on GPT and the associated data.

Example:

Do we still need metadata when using Azure OpenAI?

Answer: The question is asked incorrectly. The question should be: Does AI have access to all relevant information. This includes metadata. The example shows the problem. Azure OpenAI does not know the information even it is there.

Podcast on the topic of Next Level AI

I was part of two podcasts with Torben Blankertz and Michael Greth on the topic of Next Level AI.

Here are the links to the podcasts:

Einführen von Microsoft Copilot, ChatGPT und AI – mit Nicki Borell:

LINK: https://podcast.blankertz-pm.de/069-einfuehren-von-microsoft-copilot-chatgpt-und-ai-mit-nicki-borell/ 

MikeOnAI DerTalk - S01E02 mit Nicki Borell

LINK: https://youtu.be/vMVmIAL8I5k

Next Level AI

Writing assistance, code generation, and conclusions over data - How machine learning and artificial intelligence generate and understand natural language.

The whitepaper by Dr. Michel Rath and Nicki Borell explains the current state of technology, what OpenAI and Microsoft are doing, and how interested customers can benefit from it.

The first part covers the architecture and technical details of Generative Pre-trained Transformers, or GPT for short. It covers basic concepts such as LLM's - (Large Language Model) and what a Prompt is. The whitepaper explains the difference between OpenAI, Azure OpenAI and the announced Microsoft Copilot feature.

Details:

• Introducing ChatGPT
• Basic terms
• LLM
• Prompt
• GPT3, GPT4 and other models
• The cooperation between Open AI and Microsoft
• Microsoft Copilot
• What is the difference between Microsoft Copilot and Microsoft OpenAI
• Current state of technology - what is available, what is announced?

The second part deals with the legal aspects of the topic. How to create a guideline for employees while respecting the protection of company secrets and what needs to be considered when using ChatGPT with an eye on copyright.

Details:

• Legal Aspects related to ChatGPT & Co.
• ChatGPT and data protection
• Guidelines for employees and the protection of trade secrets
• ChatGPT and Copyright
• The AI Regulation is coming

Download

• Download German version: LINK

• Download English version: LINK

Authors

Dr.Michael Rath is a lawyer, a specialist in information technology law and a partner at Luther Rechtsanwaltsgesellschaft mbH, based in Cologne. He coordinates Luther's Information Tech & Ccommunications practice area. He is also a Certified ISO/IEC 27001 Lead Auditor.

Nicki Borell is co-founder of Experts Inside, a technology consultancy focused on Azure and Microsoft 365, and the head behind the label "Xperts At Work". His focus topics are enterprise collaboration, security and compliance. The Azure OpenAI services and the GPT language model therefore fit perfectly into his work context. They build another integartion between Microsoft 365  and Microsoft's Azure services. Content generation and semantic search are thus also possible for the data within a Microsoft 365 environment in a secure and controllable way.