USE CASES FOR GENERATIVE AI: EFFECTS ON INDUSTRIES AND SOCIETY

Muhammad Hammad u Salam; Shujaat Ali Rathore; Muhammad Irfan

Authors

Muhammad Hammad u Salam
Shujaat Ali Rathore
Muhammad Irfan

Keywords:

Generative AI, Artificial Intelligence Models, GPT (Generative Pre-trained Transformer), DALL-E, BERT Healthcare Values of an Image-based EHR System in Collaborating Limited Facilities* Jihoon Kim1*, Dongshin Kim2 and Taiwan Chun3 1 Medical University Seoul National Hospital Department of Surgery Division of Cardiovascular surgery Republic Healthcare Imaging approach mainly relies on Text-Oriented Electronic Health Record (FE- HR).

Abstract

Generative AI is a breakthrough technology with far reaching applications across industries from health to creative arts, education and manufacturing. Generative AI is expected to power a new revolution in healthcare, transforming an industry where diagnostics can often be broad and imprecise (leading to false negatives), as well part of personalized treatment plans or drug discovery. In creative areas, generative AI has unleashed new dimensions of digital arts and music as well design collaborations (as shown in Figure 6) between machine introduced creativity with human shaped outputs. One of the other things that this paper discusses is different uses for generative AI, and in education it actually does many automated tasks to create content at firs. Its clears up some time as on-going challenges start after creating CUSTOMIZED learning work! Second is its impact on manufacturing by enabling better product design and efficiency in supply chains. Generative AI has vast implications for society, boosting productivity and efficiency while driving breakthroughs in creativity. However, it also presents a number of concerning ethical issues- from AI content biases to data privacy laws and workforce displacement as well unresolved tech ethics questions related to IP. The paper discusses possible near and far future trends in generative AI, as well as long term challenges for industries, economies or even societies. It ends by highlighting that making AI responsibly is essential to make the best of generative AI and at the same time deal with its difficulties.