The concept of AI has existed for decades. But now, machine learning (ML), and a subset of ML called deep learning (DL), makes it possible to train AI software faster and help it to deliver far greater accuracy. ML algorithms learn from the data, which empowers the software to make predictions and act on them. These algorithms are now even improving over time, based on the data they collect.

This data-validated paper describes the results that businesses are achieving by deploying AI on modern compute infrastructure. The survey behind the research reflects responses from 750 global respondents—all of them IT professionals employed at organizations using AI today or planning to deploy AI in the next 24 months. All the respondents had to be familiar with the IT infrastructure underpinning their AI workloads, as well as the business initiatives and processes that AI is (or will be) augmenting.

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