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However, this explosion of demand comes with significant challenges.
Together, these factors make achieving the economies of scale seen in traditionalcloud servicesa significant hurdle.
Inside a data center where storage servers populate dozens of racks
Co-founder and Director of Hyve Managed Hosting.
The key trends driving the AI tipping point
1.
Advances in hardware and efficiency
Specialized AI hardware is evolving rapidly, reducing energy consumption and improving cost-effectiveness.
These innovations make hosting AIapplicationsmore efficient, reducing costs while maintaining the high-performance business’s demand.
As hardware continues to improve, the barrier to hosting AI workloads at scale is gradually being lowered.
The rise of AIaaS models will change the game, letting SMEs harness AI without breaking the bank.
This is particularly important for AI, where high-performance hardware often sits idle between workloads.
For AI, this reliance is even greater.
This shift will profoundly impact industries across the board.
For businesses, AI-powered solutions will streamline operations, automate tasks, and significantly reduce costs.
Ultimately, the marriage of AI and managed cloud will not just overcome existing hurdles it will redefine them.
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The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
