Data Driven models require Big-Data to perform well which is expensive, complicated
to manage and in some cases difficult or impossible to get. However, PIMLᵀᴹ
technology integrates physics and Machine Learning requiring only Small-Data.
Patent Pending Physics Informed Machine Learning (PIML™) Surrogates: Have greater blind tested predictive accuracy than data-driven machine learning methods, Require significantly less data to train than data-driven machine learning methods, Provide greater insight into the underlying dynamics of the system than data-driven machine learning methods, Have been validated for a variety of complex problems
Market trends push for increased product digitalization. These trends include: Customer buying outcomes & experiences rather than products, AI has enabled the design of intelligent product that can tune their behavior to the required operating environment, There is a desire to move from “big data” to algorithms capable of handling the “small data” problems.
Digital twins most important mission may be to keep the human species alive long enough at the start of a pandemic virus that is highly lethal, very transmittable, and with long periods of asymptomatic transmission.
From the CAASE 18 conference, Front End Analytics' Juan Betts discusses implementation of Democratized Simulation in large and complex organizations.