> it was not doing homology modelling as it is generally understood, but ab initio protein structure prediction.
Maybe according to the current definition of the term, which has drifted over the years. Homology modeling and "ab initio" structure prediction have been drifting toward each other for a long time. These days, the categories are separated by (an essentially arbitrary) sequence identity threshold. If you have a protein sequence with high homology to some other protein with a structure, then you're homology modeling. If you have no matches at all, you're doing "ab initio". In the middle, you have a gray area where you can mix the approaches and call it whatever you like.
This is not a pedantic point. If your method requires homology -- however distant and fragmented -- in order to work, then you're always limited to the knowledge in the database. Maybe we've sampled enough of protein space to get the major folds, but certainly, the databases don't have enough information to get the small details right.
I have never been a huge believer in the idea that we can go directly from protein sequence to protein structure simply using a mathematical model of physics, but that is the original meaning of "ab initio structure prediction", and if you could do it, it would be far more valuable than alphafold. At risk of making a trivially nerd-snipable metaphor, it's kind of like the difference between google translate and a theoretical model of human intelligence that understands concepts and can generate language. The latter is obviously immensely more capable than the former.