Saikat Ranjan Maity

Conflict of Interest The authors declare no conflict of interest. References 1 , , , , , , , in 2019 Int. Conf. on Engineering, Science, and Industrial Applications (ICESI), IEEE, Tokyo, Japan, August 2019, pp. 1–6. 2 , , , , Procedia CIRP 2020, 94, 565. 3 , , , , , Weld. World 2020, 64, 513. 4 , , , , in Advances in Additive Manufacturing and Metal Joining: Proc. of AIMTDR 2021, Coimbatore, Tamil Nadu 2023, pp. 43–57.

Prompt engineering blends elements of art, coding, logic, and unique modifiers The process of creating excellent prompts that direct machine learning (ML) models to generate precise results is known as prompt engineering. It entails picking the right kind of prompts, arranging and arranging them in the best possible order, and assessing how relevant they are to the work at hand.

The advent of advanced GPT models has created a potential demand for prompt engineers who contribute to making such models more safe and useful Prompt engineering is the process of designing and refining prompts or instructions for machine learning models, particularly language models like GPT-3, to produce specific, desired outputs. This technique is often used to fine-tune the behaviour and output of the model in order to make it more useful and safe for various applications.