Delivering New Outcomes through AI and Machine Learning

While implementations vary, a common thread exists among many successful artificial intelligence use cases and solutions.

ai use cases
Billie Weiss/Boston Red Sox via Getty Images

For us in the Boston area, watching our local sports teams win championships has become commonplace. Last fall, we watched our Red Sox end their 2018 season by celebrating another World Series title. Naturally, much attention went to first-year manager Alex Cora and to the clubhouse culture he built. However, it takes more than culture change to win, and Cora and the Red Sox front office recognize that. We live in a data-driven world, and that includes the world of baseball.

A September 2018 Boston Globe story detailed how the Red Sox use data-driven insights to make in-game decisions. For example, it’s more than luck when outfielder Mookie Betts makes an eye-popping catch. The Red Sox leverage data retrieved through artificial intelligence (AI) and analytics to help Betts better position himself for each batter at the plate. Statistical patterns often dictate where Betts should stand in the outfield, not just his gut instinct.

Baseball is largely played the same way today as it was 100 years ago. However, even the oldest of sports now uses intelligent analysis through AI and machine learning (ML). Modern tools enable a modern twist to strategy and decision making.

At Dell Technologies, we are helping our customers deliver new outcomes through AI and ML. At the same time, we as a company are doing what our customers are doing – leveraging AI and ML to help us make better decisions and improve customer experiences and outcomes. I’d like to share two examples that our Services teams played a key role in delivering.

Targeted healthcare

The medical industry is well-positioned to be a top benefactor of the AI/ML evolution, enabling providers to better evaluate patients and to personalize treatment options. In one example, a regional healthcare provider partnered with Dell Technologies Consulting to develop and implement a robust analytics research platform to enable an extensive community of researchers and innovators to work more efficiently with faster with expanded access to critical data. Data scientists from Dell Technologies Consulting then partnered with the healthcare provider’s data scientists and researchers to conduct research using the new platform.

One use case was research targeted at the alarmingly high number of seizures that occur in hospitals, most of which are only detectable by brain monitoring with EEGs. The learnings from past EEGs can help hospital physicians provide better diagnosis and treatment. However, mining the information is challenging because the patients’ EEG reports and data files are often stored separately and not clearly linked. It’s also difficult to quickly extract useful information from the reports that describe clinically important events. However, by applying AI and machine learning techniques, the joint team was able to develop a highly accurate classifier for pairing report files with the data, as well as extracting information from the reports, providing a more effective data pipeline for clinical operations, quality improvement and neurophysiological research.

Proactively avoiding system failure

The millions of customer systems connected to Dell Technologies around the globe can run trillions of variations of hardware and software configurations. These variations may be further influenced by factors such as geographic location and climate. Given such a vast scope and size, the ability to predict and validate potential faults may seem like an impossible task. However, through the power of AI and ML, and the capacity of today’s graphics processing units (GPUs), our internal data scientists have built solutions that implement machine learning models to open a world of even more possibilities.

Today, SupportAssist, Dell Technologies’ automated proactive and predictive technology, is run on almost 50 million customer systems. Through this connected technology, we can save customers from the potentially disastrous impact of downtime or data loss by alerting and remediating a potential hard drive failure, on average 50 days before the failure occurs. And, as our services technology continues to get smarter, customers will be empowered to make faster, better decisions about their IT, and to address immediate issues while they plan for what’s next.

Summary

These are just a couple of the many, many AI/ML use cases and solutions deployed by our customers, as well as here at Dell Technologies. While implementations vary, there is a common thread tying these outcomes together that equates to success. The right people and processes, combined with these powerful technologies, enable us to define and execute a vision that brings data and insights to life and makes

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