Generally, if one googles "quantum machine learning" or anything similar the general gist of the results is that quantum computing will greatly speed up the learning process of our "classical" machine learning algorithms. However, "speed up" itself does not seem very appealing to me as the current leaps made in AI/ML are generally due to novel architectures or methods, not faster training.
Are there any quantum machine learning methods in development that are fundamentally different from "classical" methods? By this I mean that these methods are (almost*) impossible to perform on "classical" computers.
*except for simulation of the quantum computer of course