QUESTIFY AI

Abstract

The use of Chat Generative Pretrained Transformer (Chat-GPT) and similar Generative AI models
is revolutionizing how artificial intelligence (AI) is accepted and used in a wide range of academic fields and
commercial domains. ChatGPT is very good at having human-like conversations and provides answers to
inquiries that look intelligent and helpful, even though it has been criticized for being a "intelligence without
knowledge or reasoning or the notions of truth." It is very great at summarizing, classifying, extracting, and
generating information. When it comes to text-based interaction, massive AI models in the picture, audio, and
video modalities lack the familiarity and ease of use that a wide audience of ordinary Internet users and
smartphone users enjoys. The widespread use of "standard" chatbot technology for routine chats in task-specific
automation across all industrial sectors serves to emphasize this even more. Leveraging generative AI presents
both benefits and problems because to the unique mix of extremely effective human-like discourse, familiarity
with core technology, and variety of intelligent application. One of the main issues is how AI-generated material
affects the academic integrity of scholarly work, since it may be both beneficial and damaging to research and
education. However, ChatGPT offers a special chance to enhance current ('standard') chatbots with human-like
dialogue for sophisticated intelligent automation in all application fields. The conversational AI capabilities of
ChatGPT and related generative AI models provide the basis for both the possibility to enhance pre-existing
chatbots and the issue of addressing academic integrity, despite their stark differences. In this work, we explore
these formative capabilities and provide best practices for using generative AI models like ChatGPT.