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Navigant Report Highlights Key Advantages of Machine Learning

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Navigant Report Highlights Key Advantages of Machine Learning

A report shows that machine learning is rapidly replacing traditional analytics methodologies. The future of ML is still ambiguous because it continues to evolve at a faster pace every year.

· AI Zone ·
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Machine learning algorithms have evolved substantially over the last few years. Despite the advances, some organizations have been reluctant to invest in them. A recent report from Navigant may alter their perspective.

Navigant: Machine Learning Is an Overlooked Type of Disruption Technology

The new report, Machine Learning for the Digital Utility, assessed several use cases of machine learning. The authors concluded that a number of organizations have benefited from machine learning more than traditional utility analytics techniques.

“Machine learning is an AI technology that is rapidly moving into the mainstream and is high on the agenda of many utilities. This report discusses machine learning in the context of other AI and analytics technologies, provides a brief description of how it works, and examines some recent high profile achievements. While machine learning is not new in parts of the utility value chain, despite some inherent limitations to the technology, various drivers will bring it out of pockets of excellence and thrust it into many other areas of the business,” the authors write in their synopsis.

Navigant points out that most technology pundits have focused their discussions on cryptocurrencies and other AI applications. They have dedicated fewer posts to the ongoing developments in machine learning. However, machine learning has some incredible advantages that organizations can no longer afford to overlook. 

Primary Benefits of Machine Learning

The history of machine learning can be traced back to at least 1957, when Frank Rosenblatt created the first neural network for computers. Rosenblatt’s brainchild was revolutionary at the time but was only the beginning of something much larger.

Almost 30 years later, Terry Sejnowski developed the NetTalk application. It took another decade before IBM developed a machine that could beat the world’s reigning chess champion.

Suffice to say, it has taken a long time for machine learning to progress as far as it has. Some of the biggest milestones have been overlooked by industry observers as these gaps passed. However, Navigant states that the benefits must be assessed. Here are some of the biggest changes that machine learning has created in recent years:

  • Clustering
  • Regression
  • Classification

Machine learning is invaluable in many fields, but the Machine Learning for the Digital Utility report emphasizes the mounting contributions to the energy industry.

“The utilities industry is already using self-learning algorithms, particularly in the field of asset monitoring and predictive maintenance, and several reasons suggest the use of machine learning will expand to many more use cases and its adoption will accelerate,” Stuart Ravens, principal research analyst with Navigant Research stated in a Business Wire press release. “During the past decade, it has become easier for companies to deploy machine learning thanks to falling costs, new technological advancements, a softening of conservative attitudes, and a fresh approach to analytics procurement.”

What other applications does machine learning have? The opportunities are endless. Artificial intelligence plays a major role in workplace management tools. Applications such Workfront integrate with third-party applications to share data about how teams collaborate. They depend on machine learning to better understand the nature of these collaborations.

Although the Navigant report is one of the most comprehensive on the benefits of machine learning, it wasn’t the first to investigate it. Other organizations have studied the impact of machine learning in other fields. Orion Healthcare published a report citing its use cases in the healthcare industry. 

The Orion report shows that physicians have less than 15 minutes to perform a diagnosis of their patient. They simply don’t have the time to analyze all relevant variables during a standard appointment. Machine learning is changing this reality.

What Is the Future of Machine Learning?

The Navigant report shows that machine learning is rapidly replacing traditional analytics methodologies. The future of machine learning is still ambiguous because it continues to evolve at a faster pace every year.

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Topics:
machine learning ,ai ,data analytics

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