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Does this win the Folding@home competition, or is/was that a different goal than what AlphaFold3 and ligo-/AlphaFold3 already solve for?

Folding@Home https://en.wikipedia.org/wiki/Folding@home :

> making it the world's first exaflop computing system

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Folding@home and protein structure prediction methods such as AlphaFold address related but different questions. The former intends to describe the process of a protein undergoing folding over time, while the latter tries to determine the most stable conformation of a protein (the end result of folding).

Folding@home uses Rosetta, a physics-based approach that is outperformed by deep learning methods such as AlphaFold2/3.

Folding@home uses Rosetta only to generate initial conformations[1], but the actual simulation is based on Markov State Models. Note that there is another distributed computing project for Rosetta, Rosetta@home.

[1]: https://foldingathome.org/dig-deeper/#:~:text=employing%20Ro...

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