Quantum annealers are near-term adiabatic quantum computing devices that are already of significant size. In this talk I discuss how they can be used as laboratories to implement genuine tunnelling in Quantum Field Theories. I also discuss how they can be used to embed and train a general neural network in a quantum annealer without introducing any classical element in training. This approach opens a novel avenue for the quantum training of general machine learning models which can incorporate virtually limitless and changing training data. The talk will include a pedagogical introduction to quantum annealing.