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The Rise of Generative AI: Evaluating Large Language Models for Code and Content Generation

Mohit, Mittal · 2023
PhilArchive · Papers · 2023
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philosophy
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
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