That is the central open question. That's what Scott means when he talks about asymptotics, and the conclusion of the Google paper is that we have probable evid

That is the central open question. That's what Scott means when he talks about asymptotics, and the conclusion of the Google paper is that we have probable evidence that with enough qubits and a big enough problem it will be faster for a very specific problem compared to a non-optimal classical algorithm (we have ones that are for sure better). This probably sounds like a somewhat useless result (quantum computer beats B-team classical algorithm), but it is in fact interesting because D-Wave's computers are designed to perform quantum annealing and they are comparing it to simulated annealing (the somewhat analogous classical algorithm). However they only found evidence of a constant (i.e. one that 4000 qubits wouldn't help with) speed up (though a large one) compared to a somewhat better algorithm (Quantum Monte Carlo, which is ironically not a quantum algorithm), and they still can't beat an even better classical algorithm (Selby's) at all, even in a way that won't scale. Scott's central thesis is that although it is possible there could be a turning point past 2000 qubits where the D-Wave will beat our best classical alternative, none of the data collected so far suggests that. So it's possible that a 4000 qubit D-Wave machine will exhibit this trend, but there is no evidence of it (yet) from examining a 2000 qubit machine. Scott's central gripe with D-Wave's approach is that they don't have any even pie-in-the-sky theoretical reason to expect this to happen, and scaling up quantum computers without breaking the entire process is much harder than for classical computers so making them even bigger doesn't seem like a solution. My personal frustration with D-Wave's marketing is that the fact that their computers are super specialized often gets lost; these computers fail the equivalent quantum notion of a complete set of digital logic gates.