IBM Machine Learning leverages parts of Watson to help train and deploy analytics models in the private cloud, to first be used with the IBM z System Mainframe.
IBM will soon bring some of the core machine learning technology from IBM Watson to mainframes and the private cloud, the company announced on Wednesday. The new cognitive platform, simply called IBM Machine Learning, will make its debut on the z System mainframe.
In a press release, IBM described IBM Machine Learning as a platform for "continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores." The service could help enterprise data scientists more quickly get to valuable insights.
"IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides," Rob Thomas, general manager for IBM Analytics, said in a press release. "As clients see business returns on private cloud, they will expand for hybrid and public cloud implementations."
The z System mainframe handles billions of transactions every day from organizations in retail, banking, insurance, government, and more, IBM noted in the release. For example, retail could use the machine learning service to examine the day's trends in real-time, or healthcare could use it to better tailor offerings to patients, the release said.
Operational analytic models can be created and trained through IBM Machine Learning using any language, any popular machine learning framework, and any transactional data type, according to the release. The platform will also make use of IBM Research's Cognitive Automation for Data Scientists, which can help data scientists choose the proper algorithm for their work.
The IBM z Systems mainframe can process 2.5 billion transactions per day, and the release said that IBM Machine Learning for z/OS could lead to more valuable insights into that data. To get these insights, the data remains on the system, so latency and risk are reduced.
While only available on z/OS now, the new service will eventually be available to IBM POWER systems in the future.
In late 2016, IBM also launched the Watson Discovery Service to make big data analytics more accessible to companies with limited data science resources. With the launch of IBM Machine Learning, IBM is positioning itself as an enterprise provider than can fill in a company's machine learning and big data gaps, or help them remain competitive without dedicated in-house talent. IBM has also showcased how this strategy affects other aspects of an organization outside of business intelligence, as it has dedicated Watson capabilities to cybersecurity as well.
The 3 big takeaways for TechRepublic readers
- IBM recently launched IBM Machine Learning, a new resource to help businesses train and deploy analytics models based on their vast data stores.
- The new platform will help businesses more quickly get insights from their data, and will speed up the work of data scientists.
- IBM Machine Learning will first come to the z System Mainframe and z/OS, but will eventually be available on the IBM POWER systems.
- IBM launches Watson Discovery Service for big data analytics at scale (TechRepublic)
- No hype, just fact: Artificial intelligence in simple business terms (ZDNet)
- IBM uses Watson to fill cybersecurity gaps (TechRepublic)
- IBM adds machine learning knowhow to its mainframes (ZDNet)
- AI might do your taxes this year, courtesy of IBM Watson (TechRepublic)