How to Use Generative AI For Any Business
Generative AI is a branch of artificial intelligence that can create new content from scratch, such as text, images, music, and more. It has many applications in various domains, such as marketing, education, entertainment, and research. One of the challenges in genAI field is to figure out how anyone can use it for their business.
In this blog post, I will show you how you can use generative AI with Azure OpenAI and RAG modeling to serve your customers who are using your business website. This focusses mainly on the use-case that users will be able to get the information on your website easily using natural language compared to traditional search and going through links.
RAG stands for Retrieval-Augmented Generation, which is a technique that combines a large-scale pre-trained language model with a knowledge base of documents. The idea is to retrieve relevant documents from the knowledge base based on the user’s query or prompt, and then use them as additional context for the language model to generate the output.
The benefits of using RAG modeling are:
- It can improve the factual accuracy and diversity of the generated content.
- It can reduce the need for fine-tuning the language model on specific domains or tasks.
- It can leverage existing knowledge sources without requiring additional data collection or annotation.
To use generative AI with Azure OpenAI and RAG modeling, you will need to follow these steps:
1. Create a knowledge base from your website or domain. You can use a web crawler tool like Scrapy or BeautifulSoup to scrape the content from your website and store it in a database or a file. Alternatively, you can use an existing knowledge base that is relevant to your domain, such as Wikipedia or a product catalog.
2. Index the knowledge base using Azure Cognitive Search. This is a Azure cloud service that provides fast and scalable search capabilities over structured and unstructured data. You can use it to create an index of your knowledge base documents and enable natural language queries over them.
3. Connect Azure OpenAI to Azure Cognitive Search. Azure OpenAI is a cloud service that provides access to powerful pre-trained language models, such as GPT-3 and DALL-E. You can use it to generate text or images based on your input. To use RAG modeling, you will need to connect Azure OpenAI to Azure Cognitive Search using an API or a SDK. This will allow you to retrieve relevant documents from your knowledge base based on your input and pass them as context to Azure OpenAI for generation.
4. Generate responses to user questions using Azure OpenAI and RAG modeling. You can use any input format that Azure OpenAI supports, such as natural language queries, keywords, images, or sketches. For example, you can ask “How can I download drivers for my webcam” or “compare watch version 1 with version 2”. Azure OpenAI will then retrieve the most relevant documents from your knowledge base using Azure Cognitive Search and use them as context for generating the output. The output will be a text or an image that answers your query or fulfills your prompt.
In this blog, you saw how using generative AI with Azure OpenAI and RAG modeling can help you serve your customers in a better way. This is a modern way of making sure your customers get the information they need quickly. You can also customize the generation parameters, such as the length, tone, style, and format of the output.
If you want to learn more about generative AI with Azure OpenAI and RAG modeling, you can check out these resources:
- https://azure.microsoft.com/en-us/services/openai/
