Analysis the Principle of AI Chips and the State-of-art Applications

Authors

  • Qi Zheng

DOI:

https://doi.org/10.54097/18b99n12

Keywords:

AI chips, neural networks, parallel architecture.

Abstract

In recent years, the artificial intelligence (AI) chips have emerged as indispensable components specialized for executing AI computations, which is considered as a new era for integrate circuit industry. On this basis, this study comprehensively examines the underlying principles, performance characteristics, diverse applications, limitations, and prospective directions in AI chip research. The parallel architecture, sparsity, quantization, and adaptability of AI chips empower the expeditious and efficient processing of AI tasks. These chips find versatile applications in computer vision, healthcare, and intelligent robotics, amplifying their transformative impact. Nevertheless, challenges persist in terms of scalability, versatility, and the rapid pace of technological evolution. As a matter of fact, ongoing research endeavors should prioritize the symbiotic optimization of hardware and software, the creation of energy-efficient designs tailored to specific domains, and the seamless integration of emerging technologies. These results offer a lucid depiction of the prevailing state and the anticipated trajectory of AI chip development.

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Published

31-12-2023