Page 39 - Red Hat PR REPORT - FEBRUARY 2024

2/8/24, 4:03 PM Riyadh Daily
The dynamic nature of AI workloads, characterised by varying computational needs during different phases of development,
demands a flexible infrastructure. Cloud services excel in scalability, allowing users to scale resources up or down in alignment
with demand, eliminate the need for customers to install, configure, and manage infrastructure, while providing a consistent
development and deployment experience across hybrid and multi cloud environments. This frees up developers to focus on
building and scaling applications without having to worry about upgrades, security and compliance updates, monitoring and
logging, or support. Whether it is handling peaks in training AI models or managing lower workloads during periods of inactivity,
the scalability of cloud services ensures efficiency and cost-effectiveness, making AI development more accessible and
responsive to real-world demands.

Cost-Efficiency: Democratising AI Development:

The cost associated with procuring and maintaining high-performance computing resources was a barrier to entry for many
organisations seeking to venture into AI. However, the pay-as-you-go model offered for cloud services has opened up access to
robust computing resources. This allows businesses, researchers and startups to experiment, innovate and deploy AI solutions
without the need for significant upfront investments, fostering a more inclusive AI landscape.

Global Accessibility and Collaboration: Breaking Down Geographical Barriers

Another feature of cloud services is its capacity to facilitate global accessibility to AI resources, enabling collaboration and
knowledge-sharing among geographically dispersed teams. This interconnectedness accelerates the pace of AI development, as
researchers and developers from different corners of the world can collaborate seamlessly. Furthermore, cloud-based AI solutions
can be accessed from anywhere, breaking down geographical barriers and creating a collaborative ecosystem that thrives on
diverse perspectives and expertise.

Data Storage and Management: Centralising Resources for Enhanced Efficiency

Since AI relies heavily on data, it underscores the necessity for efficient data storage and management for further development.
This can be solved by utilising the centralised storage solutions offered by cloud services that facilitate seamless access to data,
ensuring that AI models are supported with relevant and up-to-date information. The centralisation streamlines the development
process, allowing for more efficient data handling and management, which is essential for training accurate and effective AI
models.

The integration of cloud services into the realm of AI is a transformative strategy, democratising access to computational power,
fostering scalability, promoting cost-efficiency and facilitating global collaboration. As the synergy between cloud services and
AI continues to evolve, the future promises a landscape where AI development is not only technologically advanced but also
accessible to a broader audience, driving innovation across diverse sectors and shaping the way we interact with technology.

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