Maybe I'll just make one comment.
We have a very large team focused on quantum machine learning and quantum AI applications. A large amount of our software stack is actually focused on that.
I would say there are two types of quantum machine or quantum AI. The first is what we do today. That is really only thought to have an advantage when the data itself is quantum, so when you're looking at materials, chemistry and these types of problems, and maybe it'll be in a few other places, but that's what's believed.
The other is what I would call the end game quantum computer, the one we're all dreaming of when we close our eyes. That one will be able to accelerate fundamental basic operations that will actually speed up machine learning and AI applications. However, this is something that is further out than just a fault-tolerant quantum computer. There are a few additional components to that type of quantum computer that probably put it outside the 15- to 20-year type of road map. I'd say for the next decade or two, the impact of quantum and machine learning AI will probably be limited to problems with quantum data.