any static prediction will do worse in case A on any branch which changes and will do much worse in C case while always doing worse in the B case if the branch occurs in a loop. It doesn't matter how 'smart' the static predictions are and whether they come from some guided optimization or otherwise; static predictions are worse in the vast majority of cases.
So when he talks about how he is going to build branch prediction into the ISA and load it asynchronously from memory this simply isn't going to improve performance. I might also point out that the claim that context switching hurts branch prediction performance results from the changed behavior of the branches in a new context and not from the processor not being able to reuse old predictions.
I think the Mill design isn't feasible and this is a good example of one problem: a massive new hardware investment of a cpu unit that caches and manipulates predictions in main memory while adding complexity to the internal pipeline that ends up performs demonstrably(in most cases) worse.