<![CDATA[This study explores the impact of Artificial Intelligence (AI) and Natural Language Processing (NLP) on the field of digital linguistics, with a focus on syntactic and semantic analysis, machine translation, and sentiment analysis. The research aims to evaluate the performance of three advanced AI models GPT-3, BERT, and RoBERTa in these areas. The study employs a mixed-methods approach, combining both qualitative and quantitative analyzes to assess the models' abilities to process complex sentence structures, understand word meanings, translate between languages, and detect sentiments in text. The results indicate that GPT-3 outperforms BERT and RoBERTa in most tasks, achieving the highest accuracy in syntactic analysis, semantic analysis, and machine translation. However, all models face challenges, particularly in handling semantic ambiguity, figurative language, and culturally specific contexts. Despite these limitations, the findings highlight the potential of AI in advancing linguistic research and the need for further development to address the complexities of human language, including its social, cultural, and emotional dimensions.]]>
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