So far I've built a first pass of the pipeline using C++/CUDA and used it to power a SaaS and desktop photogrammetry app (free for personal non-commercial use). Got some useful feedback from the initial release of the desktop app back in January and I'm hoping to spend some time iterating to improve further later in the year (currently contracting to generate some funds).
It's possible that some deep learning generative AI network will take over all 3d model generation from photos tasks in the future but I'm hoping/betting that a) classical techniques will give higher resolution, more accurate results for a while yet and b) even if deep learning matches in accuracy and resolution it will always be possible to get better efficiency for big chunks of the pipeline using classical techniques.