So far, we have discussed three quintessential categories of generative AI’s use cases, which are generation, translation and summarisation. In this segment, we segment, we will continue that discussion and talk about the next two categories: editing and classifying.
Kshitij will discuss the next category – editing or rewriting.
The editing functionality of generative AI models finds many use cases as highlighted in the video. It can be used to improve the grammatical accuracy of a document or match the style in which it is written with a company’s standard style. It can be used to personalise marketing messages for a target audience. Finally, this functionality can also help in correcting and refactoring code.
In the next video, Kshitij will talk about the next category of use cases, which is classification or tagging.
In this video, Kshitij discussed various use cases that come under the category of classifying or tagging. Various pieces of texts such as customer feedback, social media posts and customer tickets can be classified into different categories. Using generative AI models to classify these pieces of text can improve customer operations, marketing, sales and software development.
Kshitij then revisited the example regarding the book reviews. He extended if by providing you with a concrete basis for this discussion. You saw how generative AI models can be easily used to perform sentiment analysis using product feedback as input.
The classification use case also extends to other fields where machine learning algorithms have been used in the past.
So far, you have learned about the five categories of generative AI’s use cases: generation, translation, summarisation, rewriting and continue our discussion on the quintessential categories of these use cases.