From my experience, to be a good applied AI researcher / implementer it’s not very important that you have a PhD in a specific field but it is important that yo

From my experience, to be a good applied AI researcher / implementer it’s not very important that you have a PhD in a specific field but it is important that you have experience working with and debugging complex problems. A PhD is usually a good way to gain such experience as you will work on a challenging problem and have access to people that can teach you how to debug / get unstuck when you’re stuck. Often I see people without such experience getting stuck on something when building a ML model and not being able to get unstuck as they lack the ability to properly debug the issue without external help. I think it’s absolutely possible to teach people how to write models in Keras/Tensorflow etc. but IMHO it won’t do them much good unless they also learn to effectively debug their models.