1) What is the architecture of the generative network and where exactly does it fit in the pipeline?
2) What is the interaction with the database? Is there an encoder being trained with real sequences further augmented with variations using the generative network?
3) What is the structure of the neural network that encodes the sequence? Is it a graph network, LSTM or simple conv-net?
4) The gradient descent step is very vague. Is it a physically based differentiable model (not a neural network) whose parameters are being optimized with gradient descent using automatic differentiation? Or something else? In short, there's some detail on scoring but how are the proposals being generated?
Questions aside, the results speak for themselves and are head and shoulders above all other showings. I wonder what it feels like for someone whose been in the field for years.
Despite the high score, there's still a long way to go before results reach real world utility. It's also worth keeping in mind that from a systems biology perspective, protein folding is only a small part of what makes getting clinically useful results difficult.
I might have missed something but I could not find anywhere indications of an intention to publish further details. That would be disappointing if such were indeed the case.