Electronics Behind Intelligence
Hardware Foundations of AI
DOI:
https://doi.org/10.62596/eir.vd78w591Keywords:
artificial intelligence hardware, semiconductor technology, edge computingAbstract
This paper highlights the crucial role of electronic hardware in enabling the performance and scalability of artificial intelligence systems. It explains how specialized processors, accelerators, and edge computing devices support complex AI computations across modern applications. Advancements in semiconductor technologies and innovative architectures continue to shape the future of intelligent systems.
References
Liu, Z., Xu, X., Qiao, P., & Li, D. (2024). Acceleration for deep reinforcement learning using parallel and distributed computing: A survey. ACM Computing Surveys, 57(4), 1–35.
Sze, V., Chen, Y. H., Yang, T. J., & Emer, J. S. (2017). Efficient processing of deep neural networks: A tutorial and survey. Proceedings of the IEEE, 105(12), 2295–2329.
Wang, J., & Su, J. (2025). A review of object detection techniques in IoT-based intelligent transportation systems. Computers, Materials & Continua, 84(1).
Wang, G., Che, J., Gao, C., Han, Z., Shen, J., Cheng, Z., & Zhou, P. (2025). Integrated neuromorphic photonic computing for AI acceleration: Emerging devices, network architectures, and future paradigms. Advanced Materials, e08029.
Zheng, Y., Xu, H., Li, Z., Li, L., Yu, Y., Jiang, P., ... & Wang, L. (2025). Artificial intelligence–driven approaches in semiconductor research. Advanced Materials, 37(35), 2504378.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 EDUCATION AND INDUSTRY REVIEW

This work is licensed under a Creative Commons Attribution 4.0 International License.




