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Accelerating generative AI requires the right storage

CIO

In generative AI, data is the fuel, storage is the fuel tank and compute is the engine. All this data means that organizations adopting generative AI face a potential, last-mile bottleneck, and that is storage. Novel approaches to storage are needed because generative AI’s requirements are vastly different.

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The impact of AI on edge computing

CIO

IDC forecast shows that enterprise spending (which includes GenAI software, as well as related infrastructure hardware and IT/business services), is expected to more than double in 2024 and reach $151.1 Edge processing keeps sensitive data local, addressing privacy concerns and ensuring compliance with data protection regulations.

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Prioritizing AI? Don’t shortchange IT fundamentals

CIO

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. In fact, for security, compliance, and efficiency reasons, CIOs will want to carefully manage which data generative AI has access to.

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Should finance organizations bank on Generative AI?

CIO

A lesser-known challenge is the need for the right storage infrastructure, a must-have enabler. To effectively deploy generative AI (and AI), organizations must adopt new storage capabilities that are different than the status quo. With the right storage, organizations can accelerate generative AI (discussed in more detail here ).

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MetalSoft aims to help manage server infrastructure through automation

TechCrunch

MetalSoft allows companies to automate the orchestration of hardware, including switches, servers and storage, making them available to users that can be consumed on-demand. Hostway developed software to power cloud service provider hardware, which went into production in 2014. ” Roh said.

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Multicloud by design approach simplifies the cloud experience

CIO

The complexity of multiple environments gives rise to multiple challenges from limited control and visibility to inconsistencies in security and compliance. Even businesses that manage to successfully adopt a multicloud approach are often unable to unlock the full potential of their investment.

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Cloud Data Security: Encryption at Rest Best Practices

Xebia

For all those reasons, compliance and controls are usually very robust. On the other hand, they pose the same physical security concerns as any other data facility: no bureaucracy will protect stolen or improperly destroyed storage. Your Cloud resources may share the same bare-metal hardware as other customers.

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