IBM Puts Watson-Based Machine Learning to Work on z System Mainframes

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IBM Puts Watson-Based Machine Learning to Work on z System Mainframes

IBM announced Feb. 15 that it’s bringing some of Watson’s artificial intelligence to the private cloud with a new cognitive computing platform called Machine Learning. IBM called Machine Learning the “first cognitive platform” to use analytical models to help companies more effectively analyze their operations and make sound, AI-based decisions. Machine Learning, which is designed for both novice and advanced data scientists, will continue to learn as users feed it fresh data. It can also help scientists choose the right algorithms to make decisions and can be put to work in most industries, even those as wide-ranging as retailing or oil exploration. It runs on IBM’s z System mainframes, which are widely deployed in enterprise data centers and, according to the company, can process billions of transactions each day.

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It's Based on IBM Watson Technology

Machine Learning was extracted from Watson and turned into a separate system, according to IBM. While it needed to make some tweaks to get Machine Learning up and running, IBM said the core technology it employs in Watson acts as the framework for Machine Learning.

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It’s All About z System Mainframes

Initially, Machine Learning will be available only on the z System mainframe, which is employed by companies, organizations and governments around the world for “billions of daily transactions.” Offering Machine Learning on z System makes it available to a large market base.

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IBM Machine Learning Is Versatile

IBM Machine Learning can be used by data scientists to support any program language, any Machine Learning framework including Apache SparkML or TensorFlow and any transactional data type. Machine Learning can move into existing corporate infrastructures without any major tinkering.

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It Was Created for Data Scientists

IBM noted the cognitive platform is designed for use by both amateur and expert data scientists. Machine Learning is not designed to be another tool for the business side, but rather a solution that data scientists can use to provide actionable information to corporate decision makers.

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It Supports Smarter Decision-Making

The ultimate goal with Machine Learning is two-fold, according to IBM. The company believes Machine Learning’s use of artificial intelligence will allow companies to make smarter business decisions. IBM also believes the AI support will ultimately save companies money by eliminating waste.

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It Finds the Right Algorithms

IBM Research’s Cognitive Automation for Data Scientists also will be a critical component of the solution, telling data scientists which algorithm to use to give them the best match for their specific corporate needs. The service also tells users how quickly it will produce results.

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Data and Trends Are Always Updated

IBM’s Machine Learning will continually add data and trends to better direct corporate insights and help companies make the most informed decisions.

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It Never Stops Learning

IBM Machine Learning continuously learns from and assesses the data and trends it is fed. It also analyzes other actions a company makes and uses that to automate tasks. IBM believes Machine Learning will help companies transition from technology-driven insights to business-driven insights.

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Machine Learning Can Work in Many Industries

In the retail industry, Machine Learning could forecast sales based on real-time market trends. In health care, it can collect patient data and tailor individual healthcare offerings. Machine Learning also can be used by financial professionals to better target client offerings.

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Machine Learning Will Work on Other Hardware Platforms

IBM plans to extend Machine Learning to other IBM systems. Next up for Machine Learning is IBM Power Systems. Beyond that, IBM didn’t specify, but said plans are in the works.

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