Hold on, we’re entering the age of the AI-accelerator

Technology accelerators speed things up, obviously. But then so does extra processing power, additional server space and drinking too much coffee - we are talking about the more considered use of IT accelerators in the new world of AI and ML.

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Technology accelerators speed things up, obviously. But then so does extra processing power, additional server space, GPU-charged super boosting and drinking too much coffee.

Simply pumping more juice into an enterprise IT system is not regarded to be an accelerator per se. We are talking about the more considered use of IT accelerators in the new and far more algorithmically advanced world of Artificial Intelligence (AI) and Machine Learning (ML).

Industry accelerators have actually been around for most of our post-millennial existence. SAP has championed their use in its various platform guises as a means of getting customers running with live production systems faster. Through the use of templates, pre-architected application and data services design, customers can start with what clearly is rather more than a blank first sheet of paper.

Sometimes using obfuscated and anonymised datasets to run at system test stage, accelerators can get organisations to market faster, but only if used prudently, as not necessarily as some sort of blanket deployment panacea.

The weight of a thousand clouds

Among the firms now tabling accelerator-flavoured enrichment is Accenture. As part of an extended relationship with AWS, the IT services and consulting gurus at Accenture claim to have had experience working on ‘thousands of cloud projects’ in recent times. This, the company says, gives it the ability to understand the ‘human and business dimensions’ of cloud change at scale with greater speed and certainty

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