In the world of AI, a key concept is how to train a neural network to perform a particular task efficiently and accurately, then a hardware solution is created that uses the results from that training - and this is called inferencing. The difference between these two concepts - training and inferencing - often creates confusion among people, and that's why, in today's episode, we are diving deep into explaining these two terms and how exactly they differ.  We are also painting a clear picture of the industries that use artificial intelligence and machine learning and what they're working on, so tune in, and find out more!    In this episode, you will learn: The difference between training versus inferencing a neural network. (00:46) Examples of frameworks that help with the training process of a neural network. (01:24) The stage AI & ML is at, currently, in terms of safety-critical applications. (04:42) The industries that are currently using AI & ML, and the types of applications they’re focusing on. (06:52) Connect with Mike Fingeroff: LinkedIn Connect with Ellie Burns: LinkedIn Resources: Catapult High-Level Synthesis Siemens EDA