[wxnx]

There's confounding here that you're ignoring. For reference, I'm a machine learning research scientist who started in bioinformatics, initially lured by the possibility of a machine learning solution to the protein folding problem.

Google's research arm has made leaps and bounds in a particular field (deep learning) and then managed to apply it successfully to a very, very hard problem (protein folding). That other companies failed to adapt Google's successes in deep learning faster than Google is not surprising at all to me.

One might argue that the impact of academic-big pharma collaboration (in the form of funding for research projects related to CASP) is what enabled a company like Google, with no independent desire to collect the massive amounts of wetlab data required to evaluate or develop a tool like AlphaFold, to even participate.

More importantly, AlphaFold hasn't really solved the protein folding problem well enough for drug development. So, the entire debate might be moot.