Year: 2021
Type: article
Abstract: To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and supervisory AI to effectively design, validate, and continuously improve complex processes, and helps practitioners to gain insight into the operation and justify future investments. While numerous successful applications of simulation in industry exist, such as circuit simulation, finite element methods, and computeraided design (CAD), state-of-the-art simulators fall short of accurately modeling physical phenomena, such as friction, impact, and deformation.
Institutions: Amazon (Germany), Rutgers, The State University of New Jersey, Amazon (United States), Nvidia (United States), McGill University, Mila - Quebec Artificial Intelligence Institute, Carnegie Mellon University, University of Washington, University of California, Berkeley, MIT Computer Science and Artificial Intelligence Laboratory, Stanford University, Technische Universität Darmstadt, Columbia University, OpenAI (United States), University of Alberta
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W3152331843