Exploring Weight Agnostic Neural Networks
Unpopular quote from my image and video processing professor - “The only problem with machine learning is that the machine does the learning and you don’t.”While I understand that is missing a lot of nuance, it has stuck with me over the past few years as I feel like I am missing out on the cool machine learning work going on out there.There is a ton of learning about calculus, probability, and statistics when doing machine learning, but I can’t shake the fact that at the end of the day, the output is basically a black box. As you start toying with AI you realize that the only way to learn from your architecture and results is by tuning parameters and trial and error.Of course there are many applications that only AI can solve, which is all good and well, but I’m curious to hear from some heavy machine learning practitioners - what is exciting to you about your work?This is a serious inquiry because I want to know if it’s worth exploring again. In the past university AI classes I took, I just got bored writing tiny programs that leveraged AI libraries to classify images, do some simple predictions etc.