Distinguishing Human Written and LLM’s Generated Text
REST Journal on Data Analytics and Artificial Intelligence · 2025
The field of Artificial Intelligence (AI) in Large Language Models (LLMs) for text generation will continue to revolutionize the way human-like content is created.Leveraging advanced AI capabilities, future LLMs will produce text with remarkable fluency, coherence, and contextual under-standing.As the adoption of AI-generated content becomes more widespread, differentiating between AI-generated and human-generated text will become increasingly crucial.This differentiation will play a pivotal role in combating misinformation ensuring academic integrity, and safeguarding intellectual property rights.With the proliferation of AI technologies, the challenge of distinguishing AI-generated content from authentic human expression will intensify.Popular LLMs such as GPT-3, LLaMA 3.1, Perplexity.ai, and Google Gemini will continue to evolve, enhancing their generative capabilities.In response to this growing need, we aim to develop an AI-powered tool capable of accurately identifying AI-generated content.This tool will utilize advanced algorithms to analyze linguistic patterns, semantic structures, and contextual cues, ensuring reliable detection and contributing to ethical AI usage across various domains.