Artificial Intelligence with Big Data

Abstract

Big Data has become a new source of opportunity among applications in Artificial Intelligence. Many design considerations exist in this relatively new field where parallel processing frameworks can be employed in a more economical fashion. Unlike traditional data sources, Big Data applications present their own unique challenges in order to appropriately harness the utility of open source frameworks including Apache Spark and design patterns predicated on the Directed Acyclic Graph. By embracing this new paradigm, parallel processing can be effectively leveraged to support development at a level of scale and performance that was not possible earlier.