This is one of more than 600 scrolls that could be read afterwards if the method becomes scalable. What's more: "excavations were never completed, and many historians believe that thousands more scrolls remain underground." [0]
the machine learning stuff is cool, but it's important not to discount the apparently pretty manual labour still involved in the virtual unwrapping:
> Early in the summer, a small team of annotators (the “segmentation team”) joined our effort. They began mapping the 3D structure of the scroll using tools initially built by EduceLab and improved by our community. By July we had segmented and “virtually flattened” hundreds of cm2 of papyrus.
So, it sounds like it was about a month or two of work, for a single scroll. Although, it probably could be partially or fully automated too, with some effort. Already they developed some tools to help, and I guess it's the kind of task that gets easier after you do it the first time.
The ability of an ML system to learn to mimic what the manual "virtual unrolling" process is doing, from a small number of examples-to-follow, is growing.
Each bit of success, once confirmed by other experts or correlation with other texts, improves the training data.
Eventually a fully-software pushbutton pipeline of "raw imaging to likely texts" should be possible.
And if, say, some of the scrolls are sufficiently 'read' nondestructively to embolden teams to risk destructive techniques – such as incremental ablation while reading the exact chemicals at every coordinate – even higher-resolution data could become available.
When you are discovering to do a new thing that nobody knows how to do, you first try a bunch of things manually to learn what works and what doesn't.
Only after you have a procedure that reliably works, you automate it.