The Open Source Driven Transmutation in Massive Parallel Machine Learning and Artificial Intelligence

Romeo Kienzler (IBM Academy of Technology)
Abstract

The ecosystem a couple of years ago looked very different. A couple of major vendors dominated the relational database market, open source databases have only been used in small scale deployment and academia and Artificial Intelligence was only a research topic for a couple of geeks. Now the world looks completely different. Open Source technologies are powering some of the largest data processing pipelines in to world and open source artificial intelligence technology powered by deep neural networks have been celebrating multiple major break troughs in the last couple of years. In this talk I’ll guide you through the latest historic milestones in this space by technically introducing some of the most promising projects and present their entanglement with startups, academic institutions and large enterprises.

Bio

Romeo Kienzler is a Chief Data Scientist at the IBM Watson IoT Division. In his role he is involved in international Data Mining and Data Science projects to ensure that clients get the maximum out of their data. He works as Associate Professor for Data Mining at a Swiss University and his current research focus is on Cloud Scale Data Mining using Open Source Technologies including R, ApacheSpark, SystemML, ApacheFlink and DeepLearning4J. He also contributes to various open source projects.