Serverless AI Architectures: The Future of Scalable and CostEffective Cloud AI Services
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V2I4P101Keywords:
Serverless computing, AI architectures, cloud computing, scalability, state management, cold start optimization, event-driven computing, multi-cloud deployment, security and privacy, orchestration frameworksAbstract
The rapid advancement of artificial intelligence (AI) has led to an increasing demand for scalable and costeffective cloud services. Traditional cloud architectures, while powerful, often suffer from issues related to scalability, cost, and complexity. Serverless computing, a cloud computing model where the cloud provider dynamically manages the allocation of machine resources, offers a promising solution to these challenges. This paper explores the concept of serverless AI architectures, highlighting their benefits, challenges, and potential applications. We delve into the technical details of serverless computing, including its underlying mechanisms, and discuss how these can be leveraged to build efficient AI systems. We also present case studies and empirical evaluations to demonstrate the effectiveness of serverless AI architectures. Finally, we outline future research directions and discuss the implications of these architectures for the broader AI community
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