IBM has announced IBM Machine Learning, a cognitive platform for continuously creating, training and deploying a high volume of analytic models in the private cloud. The company has extracted the core machine learning technology from IBM Watson and will initially make it available on the z System mainframe, due to the significant volume of enterprise data stored on these systems.
“Machine Learning and deep learning represent new frontiers in analytics. These technologies will be foundational to automating insight at the scale of the world’s critical systems and cloud services,” said Rob Thomas, general manager of IBM Analytics. “IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides. As clients see business returns on private cloud, they will expand for hybrid and public cloud implementations.”
The IBM z System mainframe is capable of processing up to 2.5 billion transactions in a single day. IBM Machine Learning for z/OS helps extract greater value from z Systems data without moving the data off of the system for analysis – helping to minimize latency, costly processing and security risks associated with traditional ETL processes, the vendor said. It continuously analyzes the data and models to provide better predictions and optimization of behavioral models, speeding time to insights.
Eventually, IBM Machine Learning will be available for other platforms in the future, including IBM POWER Systems.
To learn more about IBM Machine Learning, please visit https://ibm.biz/machinelearning.