Business software companies have been embedding artificial intelligence into their applications as the technology continues to advance in the enterprise. SAP SE earlier this year created a new title to oversee this effort, naming Feiyu Xu, a former Lenovo Group Ltd. AI executive, as its global head of artificial intelligence. In this newly created position, Ms. Xu oversees what she calls "a holistic AI strategy," integrating the technology into SAP's enterprise-resource planning, supply chain, human-capital management and...

From there, we'll analyze the data using a Jupyter notebook with Brunel visualizations. Finally, we'll use Spark machine learning library to create a model that predicts customer churn risk. The model will be deployed as a web service and used for inference in an application. This code pattern demonstrates the use of a Jupyter notebook to interact with Db2 Warehouse, Brunel visualizations, and Spark machine learning library -- from the creation of database objects to advanced analytics and machine learning model development and deployment. This code pattern is built on IBM Cloud Pak for Data, an open, cloud-native information architecture for AI.

Few terms are hotter today than "artificial intelligence" -- but what exactly does it mean in the real world? On one hand, AI conjures up images of The Terminator, HAL 9000, or other sci-fi scenarios. On the other hand is AI as a force of supreme good or intellectual curiosity, something like IBM's Watson or chess-playing supercomputers. The reality, of course, is somewhere in between. Artificial intelligence is already powering the programs behind many commonplace tools and activities. For example, Google includes machine learning within its search algorithm now, allowing the search engine to tweak itself over time.