I generally recommend PhD-level study in biology (that's 7 years on top of undergrad) but I think a really smart person could learn most of what's required in 2-3 years if they are in a good lab.
No, we will not all be killed by a virus in the next 10 years; that's just media alarmism. Remember, even if coronavirus becomes a worldwide pandemic, some fraction of people will survive who will be genetically immune. We're much more at risk of wars, climate change, and driving cars.
I've had this argument with folks before and some people seem fine learning in other ways, but I really prefer the textbook approach, especially textbooks which are basically just summaries of the current understanding of the field, with direct links to the detailed review articles.
They're not gaming things. DeepMind is good at games, and CASP is a competition, but everybody who does well at CASP is already doing the same sorts of things that DeepMind did to score well. And they really did come up with a good system that was demonstrably better (I want to give them credit, I just don't think 'breakthrough' is really correct). But one thing I know about CASP (I competed one year) is that after 2 years, whatever the previous winning team did is duplicated by the other top teams, and 2 years after that, everybody can do it.
I think ML is moving protein folding competitions like CASP to be faster now, because you can put your code, training data generator (much of the hard work in protein folding is coming up with good training data), a materialized copy of the training data the generator generates, and a trained model checkpoint on github, so after 2 years, everybody will be able to do what DM did at the previous competition. I think this has been one of the really important improvements in the last few years in protein folding- the computational infrastructure, both the training data, the systems to train on, and the tools to do training, have all gotten much better, and lots of people have gotten good at using them. That's a really promising sign and I hope it takes over more quantitative science.