Quantum computing people have been selling this exact spiel (including the convoluted talking points) for decades and it keeps working at getting funded. It has not produced any results for the rest of us, though.
One difference is that baking mathematical models into electronic analogs is older than integrated circuits. The reason we deviated from that model is because the re-programmability and cost of general purpose, digital computers was way more economical than bespoke hardware for expensive and temperamental single purpose analog computers. The unit economics basically killed analog computing. What Extropic (and others) have identified is that in the case of machine learning, the pendulum might have to swing back because we do have a large scale need for bespoke hardware. We'll see if they're right.
Quantum computing has been exploring an entirely new model of computation for which it's hard to even articulate the problems it can solve. Whereas using analog computers in place of digital is already well defined.
Arguably yes, in a commercial sense. To give the fusion folks some credit, they haven't been promising that commercial products are "just around the corner" for the last 30 years the way QC people have, and the quacks (cold fusion) were excised from the field for making those false promises. I do think that if your field as a whole continually makes huge promises and never delivers, it should probably tarnish that field's reputation.
However, if you're thinking about research grants, no. That's the point of research grants.
Quantum computing has been exploring an entirely new model of computation for which it's hard to even articulate the problems it can solve. Whereas using analog computers in place of digital is already well defined.