AI and HPC: Inferencing, Platforms & Infrastructure

This feature continues our series of articles that survey the landscape of HPC and AI. This post focuses on inferencing, platforms, and infrastructure at the convergence of HPC and AI. Inferencing is the operation that makes data derived models valuable because they can predict the future and perform recognition tasks better than humans. Inferencing works because once the model is trained (meaning the bumpy surface has been fitted) the ANN can interpolate between known points on the surface to correctly make predictions for data points it has never seen before--meaning they were not in the original training data. Without getting too technical, during inferencing, ANNs perform this interpolation on a nonlinear (bumpy) surface, which means that ANNs can perform better than a straight line interpolation like a conventional linear method.