IBM today announced IBM Machine Learning, the first cognitive 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.
Even using the most advanced techniques, data scientists – in shortest supply among today’s IT skills – might spend days or weeks developing, testing and retooling even a single analytic model one step at a time.
IBM has extracted the core machine learning technology from IBM Watson and will initially make it available where much of the world’s enterprise data resides: the z System mainframe, the operational core of global organizations where billions of daily transactions are processed by banks, retailers, insurers, transportation firms and governments.
“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, 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.”
IBM Machine Learning allows data scientists to automate the creation, training and deployment of operational analytic models that will support:
- Any language (eg. Scala, Java, Python),
- Any popular Machine Learning framework like (eg. Apache SparkML, TensorFlow, H2O)
- Any transactional data type
- Without the cost, latency or risk of moving data off premise.
The IBM z Systems mainframe is capable of processing up to 2.5 billion transactions – the equivalent of roughly 100 Cyber Mondays – 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. It continuously analyzes the data and models to provide better predictions and optimization of behavioral models, speeding time to insights.
IBM Machine Learning will first be available on z/OS and will be available for other platforms in the future, including IBM POWER Systems.
