Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives

Desta Haileselassie Hagos;Rick Battle;Danda B. Rawat
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引用次数: 0

Abstract

The emergence of generative artificial intelligence (AI) and large language models (LLMs) has marked a new era of natural language processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This article explores the current state of these cutting-edge technologies, demonstrating their remarkable advancements and wide-ranging applications. Our article contributes to providing a holistic perspective on the technical foundations, practical applications, and emerging challenges within the evolving landscape of generative AI and LLMs. We believe that understanding the generative capabilities of AI systems and the specific context of LLMs is crucial for researchers, practitioners, and policymakers to collaboratively shape the responsible and ethical integration of these technologies into various domains. Furthermore, we identify and address main research gaps, providing valuable insights to guide future research endeavors within the AI research community.
生成式人工智能和大型语言模型的最新进展:现状、挑战和展望
生成式人工智能(AI)和大型语言模型(llm)的出现标志着自然语言处理(NLP)的新时代,引入了前所未有的能力,正在彻底改变各个领域。本文探讨了这些尖端技术的现状,展示了它们显著的进步和广泛的应用。我们的文章有助于对生成式人工智能和法学硕士不断发展的环境中的技术基础、实际应用和新出现的挑战提供一个全面的视角。我们认为,了解人工智能系统的生成能力和法学硕士的具体背景对于研究人员、从业者和政策制定者共同塑造这些技术在各个领域的负责任和道德整合至关重要。此外,我们确定并解决了主要的研究差距,为指导人工智能研究界未来的研究工作提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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