The term "generative AI" talks about the field of technology, which uses machine learning and AI to help computers with the capacity to create new digital texts, audio, images, programmes and videos. A more developed form of generative AI forms improved content by keeping an eye on the real-life environment. It can also make use of mathematical emulation and the previously unobserved patterns that it reveals. These kinds of methods typically rely on the use of sensitivity analysis and stress testing.
In this article, we have listed down the top 5 advantages of generative AI applications. Continue reading to know more about the same.
Benefits of generative AI applications in different fields
Some of the most beneficial aspects of generative AI applications are as follows:
- In the healthcare sector
The usage of the Generative Adversarial Network (GAN) in the early detection of brain tumours and the combination of GAN with variational autoencoders for drug development are two of the most significant advantages of Generative AI. With the help of generative AI, doctors may provide patients with a treatment plan that is more effective than traditional practices. Courtesy of the many viewpoints of the CT scan image that GAN visualises. The potential of generative AI to speed up and lower the cost of drug discovery has been demonstrated. Recently, IBM completed research on COVID-19 antiviral design using generative AI.
- In the manufacturing sector
Generative AI is used to create synthetic chemical materials that are identical to the original materials. Semantic-Image-to-Photo Conversion, an application in Generative AI, can be used to convert concepts from sketches into actual images. As a result, there is a shorter time to market and a better user experience because people can see the final product model before it is created.
- In the media and entertainment sector
Film restoration and image processing are other beneficial aspects of generative AI. By removing noise, sharpening, and enhancing colours, generative AI can raise the resolution of still and moving images. Generative AI can be used to generate an avatar to conceal the interviewees' identity in some delicate news reports.
- In the banking sector
The use of Generative AI enhances data security. Synthetic data sets are created to do the job. Synthetic data sets that resemble real data but lack personally identifiable information about specific individuals serve as data privacy barriers.
- In the security of airports and other areas
Generative AI can also play a big part in ensuring the security of airports, borders and any other area. With this system, you can now generate front-on pictures from photos taken from different angles, and this comes in very handy in the case of face recognition and verification.
To sum up, like any other new technology, generative AI has its share of problems. To generate results, a sizable amount of data is necessary; otherwise, the results could be poor or insufficient. Nonetheless, with these advantages, generative AI applications are making a tangible difference in everyday human lives in almost every aspect.