And there's not much reason to make one "desktop size" until one of the laboratory size quantum computers actually does a useful calculation faster than a traditional computer could have.
AWS has machines available right now. Translating from qiskit to braket isn't rocket science either, but no one is clamoring to use them. It is hard to convince someone to take QC seriously for at-home use we can't even guarantee 1 logical qubit.
Still, every step counts and I'm really excited to see this one.
D-Wave is seeing really promising results with optimization problems and materials simulation. The real barrier to entry right now is not access to the machines, or the middleware needed to use them - it's the ability to actually harness Binary Quadratic Model or Discrete Quadratic Model problems to apply to something that delivers real ROI.
There is a lot of training material available, but there's still a difficult road between systems that mathematicians and computational physicists can work with, and systems that are turn-key enough for a business analyst with a stats background to integrate into a reporting or planning workflow. Of course, anything in software that is a 'difficult road' is also potentially a goldmine for anyone that pulls it off.