Researchers at IBM are developing ways to reduce bias in machine learning models and to identify bias in data sets that train AI, with the goal of avoiding discrimination in the behavior and decisions ...

IBM wants to bring machine learning to its traditional mainframe customers, and eventually to any technology with large data stores hidden behind a company firewall in what IBM calls a “private cloud.

Today IBM 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 ...

What we call machine learning can take many forms. The purest form offers the analyst a set of data exploration tools, a choice of ML models, robust solution algorithms, and a way to use the solutions ...

Machine learning is the fastest growing area of computer science, but it's typically the domain of specialists. IBM aims to open it up to domain experts at its Enterprise customers to model their own ...

All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission. TL;DR: A range of online ...

With the ability to revolutionize everything from self-driving cars to robotic surgeons, artificial intelligence is on the cutting edge of tech innovation. Two of the most widely recognized AI ...

IBM on Feb. 15 launched a new product that should fit in nicely with its Watson artificial intelligence service inside a mainframe-based private cloud environment: IBM Machine Learning. The company ...

IBM has fulfilled its promise to open-source SystemML, a machine learning system that’s now been accepted as an Apache Incubator project. It’s a significant milestone for SystemML, which is already ...

IBM on Monday said its machine learning system, dubbed SystemML, has been accepted as an open source project by the Apache Incubator. Machine learning, task automation and robotics are already widely ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.