Artificial intelligence is not flash in the pan — it is here to stay. Gartner says more than 80% of enterprises will have used some form of generative AI APIs or applications by 2026. If you plan to be among those 80%, then you have to determine the best way to train and deploy it, on premises or in the cloud.
AI training requires specialized hardware that is very, very expensive compared to standard server equipment. It starts at the mid-six figures and can run into the several-million-dollar range. And that hardware cannot be repurposed for other uses such as databases.
In addition to purchasing and maintaining the AI hardware, there is the model on which your AI application is based. Training is the difficult part of AI and the most process intensive. Training can take weeks or even months, depending on the size of the data set. That could be months you don’t have.
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Artificial intelligence is not flash in the pan — it is here to stay. Gartner says more than 80% of enterprises will have used some form of generative AI APIs or applications by 2026. If you plan to be among those 80%, then you have to determine the best way to train and deploy it, on premises or in the cloud.AI training requires specialized hardware that is very, very expensive compared to standard server equipment. It starts at the mid-six figures and can run into the several-million-dollar range. And that hardware cannot be repurposed for other uses such as databases.In addition to purchasing and maintaining the AI hardware, there is the model on which your AI application is based. Training is the difficult part of AI and the most process intensive. Training can take weeks or even months, depending on the size of the data set. That could be months you don’t have.To read this article in full, please click here Read More Computerworld
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