Empowering Language Models Through Advanced Prompt Engineering: A Comprehensive Bibliometric Review
Keywords:
Artificial intelligence, Bibliometric analysis, Ethics, Generative pre-trained, Language models, TransformersAbstract
This review examines the transformative impact of prompt engineering on language models in artificial intelligence. Language models have advanced from simple probabilistic frameworks to sophisticated neural networks like the Generative Pre-trained Transformer series, enhancing machine understanding and generating human-like language. Prompt engineering customizes these models for specific tasks, improving human-AI interaction. This technique has expanded the capabilities of language models, making them useful in healthcare for better diagnostics and in education for interactive learning. The review, based on publications from January 2022 to February 2024 from the Scopus database, highlights significant advancements in prompt engineering. Network visualization with VOSviewer underscores its central role in AI's progress. The findings advocate integrating prompt engineering with quantum computing and updating educational programs to include advanced AI technologies. Establishing ethical standards and promoting open access to research are also recommended to foster innovation and responsible AI usage.
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