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Cloud Costs Crushing AI Innovation: Why Companies Are Pulling Out!

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Manage episode 500422151 series 3660640
内容由David Linthicum提供。所有播客内容(包括剧集、图形和播客描述)均由 David Linthicum 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

In a recent article from ITPro Today, new research from Deloitte sheds light on the pressing challenges organizations face as they adopt artificial intelligence (AI) in their operations. As businesses increasingly turn to cloud solutions for their AI needs, they are often unprepared for the skyrocketing costs that come with it. The research uncovers a critical inflection point: when public cloud AI expenses hit 60-70% of the total ownership costs for dedicated infrastructure, organizations find themselves at a tipping point where shifting to private cloud solutions often becomes more sensible.

This rapid evolution from modest AI experiments to significant infrastructure challenges reveals a stark reality; the cloud's initial accessibility can quickly lead to budget constraints as workloads grow more demanding. Meanwhile, technological advancements such as AI-specific processors, including NPUs and TPUs, are changing the landscape of what is possible, necessitating a reevaluation of existing IT setups.

  continue reading

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Manage episode 500422151 series 3660640
内容由David Linthicum提供。所有播客内容(包括剧集、图形和播客描述)均由 David Linthicum 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

In a recent article from ITPro Today, new research from Deloitte sheds light on the pressing challenges organizations face as they adopt artificial intelligence (AI) in their operations. As businesses increasingly turn to cloud solutions for their AI needs, they are often unprepared for the skyrocketing costs that come with it. The research uncovers a critical inflection point: when public cloud AI expenses hit 60-70% of the total ownership costs for dedicated infrastructure, organizations find themselves at a tipping point where shifting to private cloud solutions often becomes more sensible.

This rapid evolution from modest AI experiments to significant infrastructure challenges reveals a stark reality; the cloud's initial accessibility can quickly lead to budget constraints as workloads grow more demanding. Meanwhile, technological advancements such as AI-specific processors, including NPUs and TPUs, are changing the landscape of what is possible, necessitating a reevaluation of existing IT setups.

  continue reading

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