I think trying to scale out compute + mutable state across multiple CPUs on a single box has somewhat fallen by the wayside outside of specialized applications like databases and distributed query engines, as a local maximum avoided in favour of scalability via more boxes.

There's several forces behind this. Applications are more likely to be web-based or services - i.e. inherently distributed - and less likely to be desktop or traditional client/server, where almost all compute happened on a single server. As distributed services, maximizing statelessness and avoiding mutable shared memory is key to solving a lot of problems: scaling out (no shared memory), redundancy (keep a second copy of the application logic running somewhere, no sync required), recovery and idempotence (if something fails, try again until it succeeds - repeated attempts are safe).

Reliable persistent queues are part of that. They let you bring services up and down and switch over without down time, or restart after a failure and resume where they left off.

The problems of shared mutable state are best kept in specialized applications: databases, queuing systems, distributed caches, consistent key-value stores. Keeping state consistent in a distributed system is a genuinely hard problem, and STM isn't much help, except perhaps as an implementation detail in some of those specialized applications.