UNBINDING THE POTENTIAL OF LARGE LANGUAGE MODELS IN GENERATIVE AI
Keywords:
Large Language Models, Generative AI, Natural Language Processing, GPT-3, BERT, Transformer ArchitecturesAbstract
LLMs, or large language models, have created new opportunities for natural language processing and conversation production, transforming the area of Generative Artificial Intelligence (AI). This study explores LLMs' capabilities, obstacles, and innovative possibilities related to Generative AI applications, demonstrating their revolutionary influence. We explore how major developments in LLM technologies, including Transformer, BERT, and GPT-3 architectures, have transformed text production, conversation quality, and context-aware answers. We examine maximizing performance and boosting output variety while fine-tuning pre-trained LLMs for generative tasks. Additionally, this paper explores the moral issues related to the use of LLMs in generative AI, stressing the significance of equity, openness, and prejudice reduction. We demonstrate the many uses of LLMs in improving tailored replies, intelligent conversation systems, and natural language interactions by providing case studies and real-world examples. By highlighting the unrealized potential of large language models to advance the field of generative artificial intelligence, this research hopes to set the stage for next developments and breakthroughs in conversational technology.
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