Great piece. Sadly, data sets relevant to quantum computing are still relatively un available. Maybe when we start running sophisticated physics experiments in quantum computers - 10 years from now- shall we truly see their relevance.
Indeed, the kinds of “practical” Data sets using quantum ML would make sense aren’t very well understood. That said, it also doesn’t necessarily seem so clear (at least, to me) whether/what frameworks are used in purely classical ML to assess and evaluate, e.g., different kernel functions.
In that sense, it may be the case for a while that someone uses Quantum ML because they find -- at least within the context of the work they are doing -- doing so “makes sense”, not necessarily because there is some principled reason for doing so.
Great piece. Sadly, data sets relevant to quantum computing are still relatively un available. Maybe when we start running sophisticated physics experiments in quantum computers - 10 years from now- shall we truly see their relevance.
Thank you for the comment and the kind words!
Indeed, the kinds of “practical” Data sets using quantum ML would make sense aren’t very well understood. That said, it also doesn’t necessarily seem so clear (at least, to me) whether/what frameworks are used in purely classical ML to assess and evaluate, e.g., different kernel functions.
In that sense, it may be the case for a while that someone uses Quantum ML because they find -- at least within the context of the work they are doing -- doing so “makes sense”, not necessarily because there is some principled reason for doing so.