Chip design with machine learning: a survey from algorithm perspective

He, Wenkai; Li, Xiaqing; Song, Xinkai; Hao, Yifan; Zhang, Rui; Du, Zidong; Chen, Yunji

doi:10.1007/s11432-022-3772-8

Cited by 2 publications

(1 citation statement)

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“…Traditional AI methods also encompass heuristic search algorithms, which are used to find solutions to problems by exploring possible paths in a search space [16]. Algorithms like depth-first search, breadth-first search, and A* search are examples of heuristic search techniques employed in problem-solving.…”

Section: Traditional Artificial Intelligence Methodsmentioning

confidence: 99%

In-depth Analysis of Artificial Intelligence for Climate Change Mitigation

2024

Preprint

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Due to the major impact of climate change on the world's environment, political and economic systems, climate change mitigation has become a pressing priority for the international community and requires rapid action from the whole society. With the continuous advancement of artificial intelligence research, the integration of AI and other technologies makes it more and more used in the whole society. It has become a promising and innovative avenue in the field of climate change mitigation. This paper comprehensively considers the key role of AI technology in the field of climate change mitigation, such as climate modeling, the optimization of renewable energy systems, the development of intelligent solutions for sustainable practices and CSS technology, and affirms its future prospects. It also describes the challenges of AI in the field of climate change mitigation. As researchers, policymakers, and industries collaborate to refine AI methodologies and integrate them into practical applications, a concerted effort is required to establish ethical guidelines, transparency standards, and inclusive governance frameworks.

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Section: Traditional Artificial Intelligence Methodsmentioning

confidence: 99%