PipelineAI Leverages Docker to Simplify AI Model Development - Container Journal

PipelineAI is taking advantage of the community edition of Docker to help organizations develop artificial intelligence (AI) applications faster at less cost. Company CEO Chris Fregly says PipelineAI Community Edition is free, public-hosted edition of the PipelineAI Enterprise Edition, with which developers can employ Apache Kafka streaming software to drive data in real time into an AI models built using Spark ML, Scikit-Learn, Xgboost, R, TensorFlow, Keras or PyTorch frameworks. The PipelineAI platform makes use of graphical processor units (GPUs) and traditional x86 processors to host an instance of Docker Community Edition that makes available various AI frameworks that need to access data in real time, says Fregly. Over time, most AI applications will need to access multiple AI models to automate a process. PipelineAI aims to reduce the cost of creating those AI models by making it less expensive for developers to determine which AI framework will work best during the life cycle of their AI application.