Revolutionizing Industries with Generative AI Applications

Posted by: Prof. R. Gopal

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Revolutionizing Industries with Generative AI Applications

Generative AI, or generative artificial intelligence, is the use of AI to create new content such as text, images, music, audio, and video. Generative AI makes use of machine learning (ML) models to find patterns and correlations in a dataset of human-generated information. After that, it uses the patterns it has discovered to create new material.


The most common approach to training generative AI models is supervised learning, which involves providing the model with a set of human-generated content along with labels. It then learns to generate material with labels that are both the same as and similar to stuff created by humans.


Typical uses of generative AI

Massive amounts of data are processed by generative AI, which then outputs answers and insights in the form of text, graphics, and easily navigable formats. Using generative AI, one can:

Popular Generative AI applications


Risks of generative AI

The risks associated with generative AI are substantial and rapidly changing. A variety of threat actors has already used the technology to create “deep fakes” or product copies, as well as artifacts that enable increasingly intricate schemes.


Practical uses of generative AI today

The areas of generative AI, science, and technology commercialization will advance at a rapid pace. However, applications such as generative design, generative engineering, artificial intelligence, and content enrichment are already starting to take shape. High-level practical applications that are now in use include the following.


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