Intersect360 Research Examines Spending Trends in Machine Learning Market

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Intersect360 Research has released a pair of new reports examining major technology trends in AI and machine learning, including the worldwide market, spending trends, and impact on HPC.

In Worldwide AI and Machine Learning Training Market Model: 2018 Spending and Future Outlook, Intersect360 Research reports spending on infrastructure for training machine learning models has grown over 50% per year the past two years, and will soon surpass $10 billion.

Machine learning has been in a very high growth stage,” says Intersect360 Research CEO Addison Snell. “In addition to that $10 billion, many systems not one hundred percent dedicated to machine learning are serving training needs as part of their total workloads, increasing the influence that machine learning has on spending and configuration.”

However, it is critical to understand that while AI is a major IT trend, it does not constitute a “market” in the normal sense of the word, explains Snell. “The number-one question we’ve gotten for years is, ‘What is the size of the AI market?’ Intersect360 Research has taken a careful approach, looking at industry dynamics across HPC and Hyperscale to provide the guidance in this report.”

Snell explains, “The temptation is to rush to market with a new product or solution. This should be done carefully—not every user is ready to spend extra money on a new set of tools dedicated to machine learning. This report provides a roadmap to where the spending is.”

In its second report, HPC User Budget Map Survey, Special Report: Machine Learning’s Impact on HPC Environments, the analyst firm reports on how HPC sites are spending their budgets, and the impact machine learning has on those budgetary trends.

Almost two-thirds (61%) of Intersect360 Research survey respondents report that they are currently running machine learning programs as part of or in addition to their HPC environments, while another 10% plan to implement machine learning programs within the year.

Machine learning is already bringing additional revenue into the HPC market and is poised to bring more. “Budgets are shifting. This is indicative of additional revenue entering the market and a further commitment to machine learning algorithm development,” explains Snell.

He continues: “For-profit companies are racing forward toward AI leadership. There is money to be made, a lot of it, and quickly.”

Both reports are available for purchase and download at

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