Large Language Models in AI: Opportunities and Limitations in Real-World Applications

Abstract

Large language models (LLMs) have emerged as powerful tools in artificial intelligence (AI), capable of performing a wide array of natural language processing (NLP) tasks with remarkable proficiency. This paper examines the opportunities and limitations of LLMs in real-world applications, highlighting their transformative potential across various industries such as healthcare, finance, and education. LLMs facilitate advancements in areas like automated content generation, customer service, and language translation, driving efficiency and innovation. However, their deployment also presents significant challenges, including ethical concerns related to bias, data privacy, and transparency, as well as practical issues such as computational demands and environmental impact. By exploring both the opportunities and limitations of LLMs, this paper aims to provide a comprehensive understanding of their role in modern AI and to propose strategies for maximizing their benefits while mitigating associated risks.