The volume, variety, velocity and veracity of data is pushing how we think about computer systems. IBM Research's Data Centric Solutions organization has been developing systems that handle large data sets shortening time to solution. This group has created a data centric architecture initially delivered to the DoE labs at the end of 2017 and being completed in 2018. As various features to improve data handling now exist in these systems, we need to begin to rethink the algorithms and their implementations to exploit these features. This data centric view is also relevant for Artificial Intelligence (AI) and Machine Learning (ML). In this talk, I will describe the architecture and point out some of hardware and software features ready for exploitation. I will show how we are using these data centric AI/cognitive computing systems to address some problems in new ways as case studies.