Generative and Predictive AI for Innovative Harmony

Generative AI has taken over the world with a buzz. It is so new of a technology that everyone including me is confused with what will make use of this new and emerging technology. Some very fundamental differences between Generative AI and Predictive AI are what people fail to list out speaking from my very own experiences. After making my very own Udemy course on using Azure OpenAI titled “Mastering Azure OpenAI (Generative AI): From Zero To Hero”, I myself struggled to answer when bombarded with these seemingly fundamental and very basic questions.

In short, Generative AI and Predictive AI can prove to be a force to reckon with. Generative AI in the front end and Predictive AI running in the back end are for sure going to change the way we perceive things.

Let us take an example to understand my argument a bit better and more in-depth. Let’s say the problem statement is that you work at a company and have a large number of PDF invoices at hand. You want to automate the process of going through the invoices, fetching important details such as “merchant name”, “merchant address”, “billing address”, “subtotal value” etc., and then create a “.csv” file containing all these entries.

A possible solution to this problem would be to use Microsoft Azure’s Document Intelligence resource (formerly called “Form Recognizer”) to extract all the required details from the unstructured invoice and then you can use your GPT engine to pass in all those details in the form of a prompt to your GPT-engine and then tell it to make a “.csv” file containing all those details. In this way, you made use of both Predictive AI (Microsoft Azure Document Intelligence) and Generative AI (GPT-engine) to automate this particular process which otherwise would have taken up a lot of your precious time.

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