I'm a professional MR physicist. I genuinely think the profession is hugely up the hype curve with "AI" and to a far lesser extent low field. It's also worth saying that the rigorous, "proper" journal in the field is Magnetic Resonance in Medicine, run by the international society of magnetic resonance in medicine -- and that papers in nature or science generally nowadays tend to be at the extreme gimmicky end of the spectrum.
A) Many MR reconstructions work by having a "physics model", typically in the form of a linear operator, acting upon the required data. The "OG" recon, an FT, is literally just a Fourier matrix acting on the data. Then people realised that it's possible to I) encode lots of artefacts, and ii) undersample k-space while using the spatial information using different physical rf coils, and shunt both these things into the framework of linear operators. This makes it possible to reconstruct it-- and Tikhonov regularisation became popular -- so you have an equation like argmin _theta (yhat - X_1 X_2 X_3.... X_n y) + lambda Laplace(y) to minimise, which does genuinely a fantastic job at the expense, usually, of non normal noise in the image. "AI" can out perform these algorithms a little, usually by having a strong prior on what the image is. I think it's helpful to consider this as some sort of upper bound on what there is to find. But as a warning, I've seen images of sneezes turned into knees with torn anterior cruciate ligaments, a matrix of zeros turned into basically the mean heart of a dataset, and a fuck ton of people talking bollocks empowered by AI. This isn't starting on diagnosis -- just image recon. The major driver is reducing scan time (=cost), required SNR (=sqrt(scan time)) or/and, rarely measuring new things that take too long. This almost falls into the second category
The main conference in the field has just happened and ironically the closing plenty was about the risks of AI, as it happens.
B) Low field itself has a few genuinely good advantages. The T2 is longer, the risks to the patient with implants are lower, and the machines may be cheaper to make. I'm not sold on that last one at all. I personally think that the bloody cost of the scanner isn't the few km of superconducting wires in it -- it's the tens of thousands of phd-educated hours of labour that went into making the thing and their large infrastructure requirements, to say nothing of the requirements of the people who look at the pictures. There are about 100-250k scanners in the world and they mostly last about a decade in an institution before being recycled -- either as niobium titanium or as a scanner on a different continent (typically). Low field may help with siting and electricity, but comes at the cost of concomitant field gradients, reduced chemical shift dispersion, a whole set of different (complicated) artefacts, and the same load of companies profiteering from them.