Citation :

Kushal Walia, 2024. "Accelerating AI and Machine Learning in the Cloud: The Role of Semiconductor Technologies" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 2: 34-41.

Abstract :

This paper explores the pivotal role of semiconductor technologies in accelerating artificial intelligence (AI) and machine learning (ML) applications within cloud computing environments. As the demand for advanced AI capabilities continues to surge, the computational, energy, and efficiency requirements of AI operations have become increasingly critical challenges. Semiconductor innovations, particularly AI-specific chips such as Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), and Field-Programmable Gate Arrays (FPGAs), offer promising solutions to these challenges by enhancing the performance, scalability, and energy efficiency of cloud-based AI services. Through a comprehensive review of recent advancements in semiconductor technologies and their applications in cloud AI, this paper highlights the significant performance improvements and sustainability benefits these innovations provide. Additionally, it addresses the role of semiconductor-based hardware in enhancing the security of cloud AI applications, a concern of growing importance. Despite the promising advancements, the paper also discusses the challenges facing the semiconductor industry, including manufacturing complexities, material limitations, and supply chain vulnerabilities, while suggesting future directions for research and development. Ultimately, the paper underscores the critical importance of semiconductor technologies in enabling the next generation of efficient, secure, and scalable cloud AI services, marking a significant step forward in the realization of advanced AI and ML capabilities.

References :

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Keywords :

Artificial Intelligence, Cloud Computing, Graphics Processing Units (GPUs), Machine Learning, Semiconductor Technologies.