Physics ML is the term that we use at NVIDIA to talk about solving hard engineering problems using AI: problems like optimizing engineering designs, developing virtual sensors, and building digital twins. Until recently, some of these problems were considered impossible due to the great computational requirements of traditional methods. In this talk, we will discuss how Physics ML is changing what is possible. We’ll share some examples, introduce three different types of Physics ML techniques, the skills required to use them, and discuss what NVIDIA is doing to help reduce the barrier to develop and deploy Physics ML solutions.

• How physics-ML can solve difficult engineering problems using AI

• Different types of physics-ML techniques

• Hands-on example of how to develop and deploy physics-ML solution

Content

content goes here