Tailoring AI Infrastructure
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In this Issue
In this month’s special issue, we delve into the critical need for a holistic approach to AI infrastructure. As we navigate the complexities of modern AI, it becomes clear that a one-size-fits-all solution is not feasible. Each enterprise has unique requirements, and understanding these nuances is essential for success.
Enterprise decision-makers must evaluate their AI infrastructure needs from multiple perspectives. This includes looking at security and governance in AI infrastructure, what kind of hardware is needed for AI interconnectivity and deciding between on-premises, edge or cloud solutions. These factors, among others, explored in our stories this issue, when considered collectively, will significantly influence the benefits organizations can derive from AI.
Aliyah Mohammed
Associate Managing Editor
From cost center to competitive edge: The strategic value of custom AI Infrastructure
Today’s AI workloads, especially around training and inference for LLMs, require unprecedented levels of computing power.
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Going beyond GPUs: The evolving landscape of AI chips and accelerators
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What’s the minimum viable infrastructure your enterprise needs for AI?
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Fit for Purpose:
From cost center to competitive edge: The strategic value of custom AI Infrastructure
Going beyond GPUs: The evolving landscape of AI chips and accelerators
What’s the minimum viable infrastructure your enterprise needs for AI?
Cloud, edge or on-prem? Navigating the new AI infrastructure paradigm
Building and securing a governed AI infrastructure for the future
AI's middle layer still needs powerful hardware
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AI is changing enterprise computing – and the enterprise itself
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Building and securing a governed AI infrastructure for the future
Read More
AI's middle layer still needs powerful hardware
Read More
Cloud, edge or on-prem? Navigating the new AI infrastructure paradigm
AI is changing enterprise computing – and the enterprise itself
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