工程和人工智能:促进协同作用
Ramalingam Chellappa1,2, Guru Madhavan3, T E Schlesinger1
1Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
PNAS nexus
|March 12, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在改变工程,但在准确性,偏见和安全性方面面临挑战. 这篇论文探讨了AI.
科学领域:
- 工程和计算机科学 工程和计算机科学
- 人工智能和机器学习
背景情况:
- 由数据和计算能力推动的AI和ML的进步,影响了各种领域.
- 关键的挑战包括准确性,可信度,安全性,偏见,可解释性和性能漂移.
- 在数据稀缺领域的影响是有限的.
研究的目的:
- 检查AI和ML对工程系统的影响.
- 在人工智能驱动的工程中解决安全和性能保证问题.
- 分析进展和挑战,以增强工程-人工智能协同作用.
主要方法:
- 关于工程中的AI/ML应用的文献综述.
- 分析当前的进展和发现的挑战.
- 检查安全和绩效保证策略.
主要成果:
- 人工智能/机器学习越来越多地被整合到工程领域,如自动驾驶汽车和材料发现.
- 在AI/ML系统的可靠性,安全性和偏见方面,仍然存在重大挑战.
- 工程原理和AI/ML之间的协同作用需要进一步开发强大的应用程序.
结论:
- 加强工程-人工智能协同作用对于可靠和安全的部署至关重要.
- 解决AI/ML挑战对于在数据有限的工程领域的更广泛采用至关重要.
- 未来的研究应该专注于针对工程应用的强大的AI/ML方法.
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