I've long thought that if AI can start solving unsolved math problems we are in for a very weird (or bad) future, since at that point it really can come up with things that no one has thought of before. And perhaps, it would also be able to find new physics or new physical mechanisms very fast.
That said, it sounds like teams are guiding the areas of exploration pretty directly. If I was more cynical, I'd say that Google has a lot of financial incentive to claim it was integral to any breakthroughs the team comes up with.
"Gravity as a fluid dynamic phenomenon in a superfluid quantum space. Fluid quantum gravity and relativity." (2017) https://hal.science/hal-01248015/ :
> [ Bernoulli, Navier-Stokes, Gross-Pitaevskii vortices in a field with curl ]
Shouldn't solving NS also solve for n-body gravity?
This is a fine collection of links - much to learn! - but the connection between flow and gravitation is (in my understanding) limited to both being Green's function solutions of a Poisson problem. https://en.wikipedia.org/wiki/Green%27s_function
There are n-body methods for both (gravitation and Lagrangian vortex particle methods), and I find the similarities and differences of those algorithms quite interesting.
But the Fedi paper misses that key connection: they're simply describing a source/sink in potential flow, not some newly discovered link.
That said, it sounds like teams are guiding the areas of exploration pretty directly. If I was more cynical, I'd say that Google has a lot of financial incentive to claim it was integral to any breakthroughs the team comes up with.