Artificial Intelligence Is Changing The World Today – SUSE Linux Enterprise for High Performance Computing Handles AI Workloads


Robot butlers and flying cars aren’t quite the norm yet, but it’s easy to start dreaming about future innovations when talking about artificial intelligence (AI). The truth is, AI isn’t just a fun topic for discussions about tomorrow—it’s here today, happening all around us, and swiftly growing into a force for change in business and society.

The AI applications in use today are decidedly less glamorous than walking, talking androids—think software that compiles quarterly earnings reports (Associated Press) or a computer system that identifies and filters out deceptive online merchants (PayPal)—but the implications and results of these fledgling AI applications are exciting.

AI Is Here, It’s Clear, Get Used to It

That businesses worldwide are picking up on this buzz is obvious: AI adoption in enterprise grew a whopping 60 percent in the last year—a 2016 survey showed that 38 percent of respondents had implemented AI in their businesses, and in 2017, that number had risen to 61 percent.[1]

It’s also clear that enterprises are earmarking a significant part of their budgets to AI. The average annual spend of companies across the world is expected to rise 31 percent by 2020 (compared to 2016 figures) to $88 million per company.[2] A small percentage of companies are going far above and beyond that average, as the same survey revealed that 16 of the 835 executives interviewed projected that their firms would spend at least $1 billion each that year on AI initiatives.[3]

Building a Better Enterprise—Today

Another small percentage of tech companies are putting AI dollars toward projects that will become reality in the near-ish future, such as Apple, Microsoft and Tesla investments in autonomous car research. Those projects tend to get the most press, but the majority of AI investments focus closely on bettering the enterprise today. It’s about enhancing productivity, personalizing customer interactions and automating rote tasks. Building practical tools with valuable real-life applications today, right now.

The most common uses for AI today are predictive analytics, machine learning, natural language processing or generation, voice recognition and response, virtual assistants and chatbots, and diagnosis/recommendation engines.[4] Companies large and small are finding all kinds of innovative ways to make these functions work for them: [5]

  • Engineering giant Siemens has used predictive analytics to forecast energy supplies and procurement for many years. It uses a neural network to predict electricity prices up to 20 days in the future to help it pinpoint the best times to purchase.
  • Since 2016, a pilot program at Hilton Worldwide has used a virtual concierge named Connie that interacts with visitors and provides targeted information about local attractions and hotel services.
  • Office supplies retailer Staples uses voice recognition technology to enable business customers to order supplies through a voice-activated automated system, which is accessible via a smartphone app.
  • National Oilwell Varco uses AI to automate oil drilling operations for oil companies in the Gulf of Mexico. The company reports that the AI can work 40 percent faster than humans.


Starting with the Right Foundation

As enterprises find more ways to put AI to work, the need for the right infrastructure grows. By its very nature, AI runs on data, and many applications need an ongoing supply of massive amounts of that data to identify patterns and learn. Which requires a lot of computational power. That’s why many companies are implementing high-performance computing (HPC) infrastructures and putting parallel processing to work to speed up AI applications as they turn high volumes of data into business value.

It used to be that HPC was only pursued by government or academic research organizations, but that, too, is changing. The HPC systems of today are based on Linux clusters running on industry-standard x86 or AArch64 hardware—the same kind of Linux clusters that enterprises are likely already using for their big data and cloud architectures.

With the right foundation for your AI applications, you’re helping your business accommodate new and innovative uses for AI as they emerge down the road. HPC can help you achieve that powerful foundation today.


Check out the High Performance Computing solutions from SUSE at .

Jeff Reser, SUSE HPC



[1] Outlook on Artificial Intelligence in the Enterprise 2018, Narrative Science, 2017.

[2] Getting Smarter by the Day: How AI is Elevating the Performance of Global Companies, Tata Consulting, 2017.

[3] Ibid.

[4] Outlook on Artificial Intelligence in the Enterprise 2018, Narrative Science, 2017.

[5] All examples in this section come from Getting Smarter by the Day: How AI is Elevating the Performance of Global Companies, Tata Consulting, 2017.

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Jeff Reser