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Top 3 cloud computing trends of 2024

AI As A Service (AIaaS)

In the forthcoming years, significant growth is foreseen in the integration of AI services into cloud solutions. Cloud infrastructure plays a crucial role in opening up AI’s economic and social benefits to enterprises. Training AI models, such as the robust large language model (LLM) powering ChatGPT, demands extensive data and substantial computing resources. 

Enterprises are shifting away from constructing their own AI infrastructure and opting for AI-as-a-service provided by cloud platforms. This transition allows them to harness the transformative power of AI without the constraints of managing resources. AI as a Service offers pre-built AI models, tools, and APIs hosted on cloud platforms, enabling enterprises to seamlessly implement AI functionalities, even without specialized AI expertise and infrastructure.

Hybrid & Multi-Cloud Strategies

Multi-cloud and hybrid solutions have become incredibly popular among enterprises across the globe. The hybrid multi-cloud approach incorporates public cloud services from multiple providers, enabling portability across diverse cloud infrastructures. This enhances flexibility and reduces dependency on a single vendor, thus mitigating the risk of vendor lock-in. 

Besides, hybrid cloud solutions offer a flexible approach to managing data storage complexities. By integrating public and private cloud environments, organizations can leverage existing infrastructure while gaining scalability, security, and redundancy. This approach optimizes storage resource allocation, strengthens disaster recovery capabilities, and fosters agility in response to evolving business requirements. 

Moreover, hybrid cloud solutions provide enhanced control over IT infrastructure and bolstered security compared to alternative cloud options. Cloud vendors employ expert security professionals to ensure data protection, adhering to stringent protocols and compliance measures.

Edge AI Computing

The edge computing landscape is expected to witness significant traction in the forthcoming years. In the traditional cloud model, data transfers to a remote server for processing. In contrast, edge computing establishes a compact computing environment near the data source. 

This reduces latency and enables real-time analysis and decision-making. The deployment of advanced networks like 5G, along with energy-efficient processors and algorithms, is expected to further bolster edge computing’s viability for evolving application needs by 2024.

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