研究中的下一代人工智能语言模型：有前景的前景和有效的关注点

English | 2024 | ISBN: 9781032667911 | 702 pages | True PDF,EPUB | 26.77 MB

In this comprehensive and cutting-edge volume, Qureshi and Jeon bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised.

The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies, and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionize their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem-solving abilities, and evidence-based decision-making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation.

This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book’s discussions on both the technical and ethical aspects of this rapidly growing field.

中文| 2024 | ISBN:9781032667911 | 702页| True PDF，EPUB | 26.77 MB在这本全面而前沿的书中，Qureshi和Jeon汇集了来自世界各地的专家，共同探索人工智能模型在研究中的潜力，并讨论了该领域快速发展带来的潜在利益、关切和挑战。 国际章节贡献者小组提供了大量关于人工智能不同方面的技术信息，包括人工智能的关键方面、人工智能的深度学习和机器学习模型、自然语言处理和计算机视觉、强化学习、道德和责任、安全、实际实施和未来方向。内容在理论、方法和技术方面是平衡的，贡献者提供案例研究，以清楚地说明整个过程中的概念和技术讨论。读者将获得宝贵的见解，了解人工智能如何彻底改变他们在数据分析和模式识别、医疗保健研究、社会科学研究等领域的工作，并提高他们的技术技能、解决问题的能力和循证决策。此外，他们将认识到与语言模型相关的局限性和挑战、伦理影响和安全问题，这将使他们能够就其实施做出更明智的选择。 对于想要了解人工智能模型、该领域的最新趋势以及人工智能的技术和伦理方面的本科生和研究生来说，这本书是一个宝贵的资源。参与人工智能开发或在各个领域实施人工智能的公司也将从这本书对这一快速增长领域的技术和道德方面的讨论中受益。

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