Eventually Scott Aaronson will be wrong. Call it a reverse black swan, but we will all remember it as the day the quantum computing era began.
'Super position' and 'entanglement' have been overly mystified in QM in general and the implications of probabilistic Turing machines vs the typical non-deterministic Turning machine examples is important.
While probabilistic Turing machines are non-deterministic, they don't work the way that most examples offer.
Same problem with elementary descriptions of entropy so it isn't just the quantum fields problem.
I work in this field as I find it compelling and the challenges of finding a worthy business case that applies beyond the fantastical potentials is one I feel worth my efforts/years. But equally open to failure where such yields an advance in our learning.
Aaronson is always an entertaining voice in the industry, although his focus on AI means less than I would hope to nudge us along at times. But he was in fine form at Q2B conference in Santa Clara recently, and I'm not anywhere near close to my contributions to the industry to ignore his thoughts as valuable to the discourse. Especially when pushing back on the emotional velocity we might have at times.
To me it seem quite wild to have quantum sensing separated from the rest of quantum information science. It would be like saying that classical SNR considerations are unrelated to Shannon's introduction of error correcting codes (the birth of information science). But if that is your preference, it does not make much sense to argue. Either way, most scientist who work on quantum information science also see their work apply specifically to sensing.
Similarly, it seems strange to me to insist on specifically focusing on quantum computing, when the majority of technology developments in quantum information science apply both to sensing and to computing (one of which is simply easier thanks to its analog nature).