FEATURE: CLOUD SOLUTIONS
According to Forrester’ s Infrastructure Cloud Survey in 2023, 79 % of roughly 1,300 enterprise cloud decision-makers said their firms are implementing internal private clouds, which will use virtualisation and private cloud management. Even though not all of these companies will be applying for AI, private cloud offers the certainty in expenditure necessary to justify large investments into cloud computing capabilities.
However, despite their advantages, private clouds are not without their challenges. For instance, specialised hardware is required for large-scale AI operations. This can be cost-prohibitive and require extensive power and cooling systems at a time when sustainability is a necessary consideration for businesses. Furthermore, it doesn’ t last forever. The two major GPU providers, Nvidia and AMD, release new components annually, and businesses can expect to renew their investment in GPUs as the compute requirements to train future models increase.
At the same time, the financial impact of running this type of hardware is yet to be fully understood on account of the relative infancy of large-scale AI. AI requires power beyond what is traditionally expected for data centres – the average server rack consumes 130KW of power and there can be thousands of racks present in one facility.
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