Artificial intelligence workloads often require special infrastructure that previously was not considered needed for other demanding computational jobs.

Salvatore Salamone, Managing Editor, Network Computing

March 15, 2022

1 Min Read
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Businesses have, for decades, changed their infrastructure to support new applications and workloads. That process continues as the use of artificial intelligence becomes mainstream in more organizations. In fact, what many companies find is that even if they have upgraded or recently installed infrastructure for high-performance computing, they still need to do more.

That point was evident in a recently released IDC Worldwide Semiannual Artificial Intelligence Tracker. It found that hardware spending was the smallest of all AI segments (which also includes services and software) but was poised for great growth.

“Of all the spending in the various AI market segments, AI Hardware is by far the smallest,” said Peter Rutten, research vice president, Performance Intensive Computing at IDC. “What this should tell organizations is that nickel-and-diming purpose-built hardware for AI is absolutely counterproductive, especially given the fast-growing compute demand from increasing AI model sizes and complexities.” That situation will change rapidly.

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About the Author(s)

Salvatore Salamone

Managing Editor, Network Computing

Salvatore Salamone is the managing editor of Network Computing. He has worked as a writer and editor covering business, technology, and science. He has written three business technology books and served as an editor at IT industry publications including Network World, Byte, Bio-IT World, Data Communications, LAN Times, and InternetWeek.

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