How to afford AI (Without Being Tony Stark)

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How to afford AI (Without Being Tony Stark)

AI technology is recognized for its potential to enhance decision-making, efficiency, and customer relations, but it comes with a hefty price tag. Training advanced models like ChatGPT requires extensive financial resources, including thousands of GPUs and significant daily operational costs. Businesses must find ways to manage these expenses to remain competitive and profitable in the evolving tech landscape.

Cloud infrastructure plays a crucial role in AI development, enabling the use of machine learning and automation. By leveraging Data Protection as a Service (DPaaS), companies can optimize their cloud operations and reduce costs associated with AI development. This approach not only supports ongoing business optimization but also facilitates reinvestment into AI technologies.

• AI training requires significant financial investment and resources.

• Cloud infrastructure is essential for AI development and cost management.

Key AI Terms Mentioned in this Article

Data Protection as a Service (DPaaS)

DPaaS helps businesses reduce operational costs while ensuring data integrity and security.

Total Cost of Ownership (TCO)

Evaluating TCO is crucial for companies considering DPaaS to manage AI-related expenses.

Large Language Models (LLMs)

Training LLMs like ChatGPT requires substantial computational resources and financial investment.

Companies Mentioned in this Article

Commvault

Commvault's solutions support businesses in optimizing their data management strategies, particularly in the context of AI.

Microsoft

Microsoft emphasizes the importance of AI in driving technological advancement and competitiveness.

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