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Learning About Cognitive Capabilities

Valerie Dennis

In October when I attended the IBM World of Watson, I took the opportunity to immerse myself in the full cognitive experience: attending sessions and demonstrations, visiting IBM booths to see what they were showcasing and talking to vendors about how their products play a role in cognitive computing. I even tweeted about the Marchesa cognitive dress, which lights up in different colors based on the sentiment of tweets about it. All of the things that are possible now and being worked on for the future because of cognitive learning are incredible, and I was getting a firsthand look at the next big thing.

IBM has since brought cognitive learning to the mainframe as IBM Machine Learning for z/OS*. Machine learning allows cognitive systems to learn, reason and engage in personalized ways. With IBM Machine Learning for z/OS, organizations and data scientists can quickly create, deploy and continuously monitor analytic models, helping make better decisions faster so they can understand their clients’ needs. Learn more about IBM Machine Learning in “Modeling Machine Learning.” In “A Thoughtful Pairing,” find out why the IBM z Systems* platform—where everything is already on-premises—is poised to take advantage of machine learning.

Australia-based Bankwest is making it easier for its banking customers to do business by having modern technologies in place, including mobile and online solutions. Read about it in “ Accounting for the Future.” Also inside, Java* is creating a connected mainframe capable of modern development, delivering portability, security and other benefits. Read about it in “The Connected Mainframe.”

And starting this month, IBM Hot Topics shifts to year-round coverage. Find new articles in the March/April and July/August print issues and monthly at ibmsystemsmag.com/mainframe/Hot-Topics. The first article, “ Optimized for the Enterprise,” dives into how IBM Machine

Learning is supported by Apache Spark. If what I learned at World of Watson is any indication, what we have seen so far from IBM Machine Learning for z/OS is just the tip of the iceberg. I look forward to continuing to follow and cover what capabilities are possible when machine learning utilizes the power of the z Systems platform.

Valerie Dennis // Managing Editor
vdennis@msptechmedia.com

Valerie Dennis Craven is a Minneapolis-based writer and editor.



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