The Rise of Generative AI: Evaluating Large Language Models for Code and Content Generation
Abstract
Large language models (LLMs) lead a new era of computational innovation brought forth by generative
artificial intelligence (AI). Designed around transformer architectures and trained on large-scale data, these models shine
in producing both creative and functional code. This work examines the emergence of LLMs with an emphasis on their
two uses in content generation and software development. Key results show great mastery in daily activities, balanced
by restrictions in logic, security, and uniqueness. We forecast future developments, therefore concluding with
ramifications for industry, education, and society. Particularly with the progress of Large Language Models (LLMs),
Generative Artificial Intelligence (AI) has seen explosive expansion recently. From sophisticated software code to plain
language writing, these models have shown amazing capacity in content creation. Focusing on the performance, problems,
and consequences of LLMs in code and content creation, this work investigates the advent of generative artificial
intelligence. We assess these models' accuracy, efficiency, and inventiveness while also attending to ethical issues and
social effects. We also go over the direction LLMs will take and their possible uses in several sectors.