Message passing is a type of mutable shared state — but one that's restricted in some important way to eliminate a certain class of errors (in Erlang's case, to a thread-safe queue with pairwise ordering guarantees so that all processing on a particular actor's state is effectively atomic). You can also pick other structures that give different guarantees, e.g. LVars or CRDTs make operations commutative so that the ordering problems go away (but by removing your ability to write non-commutative operations). The big win for the actor model is (just) that it linearizes all operations on a particular substate of the program while allowing other actors' states to be operated on concurrently.
Nobody argues that any of these approaches is a silver bullet for all concurrency problems. Indeed most of the problems of concurrency have direct equivalents in the world of single-threaded programming that are typically hard and only partially solved: deadlocks and livelocks are just infinite loops that occur across a thread boundary, protocol violations are just type errors that occur across a thread boundary, et cetera. But being able to rule out some of these problems in the happy case, even if you have to deal with them occasionally when writing more fiddly code, is still a big win.
If you have an actor Mem that is shared between two other actors A and B then Mem functions exactly as shared memory does between colocated threads in a multithreaded system: after all, RAM on a computer is implemented by sending messages down a bus! The difference is just that in the hardware case the messages you can pass to/from the actor (i.e. the atomicity boundaries) are fixed by the hardware, e.g. to reads/writes on particular fixed-sized ranges of memory, while with a shared actor Mem is free to present its own set of software-defined operations, with awareness of the program's semantics. Memory fences are a limited way to bring that programmability to hardware memory, but the programmer still has the onerous and error-prone task of mapping domain operations to fences.
Since I am not familiar enough with Erlang to know, is that actually the same as concurrent code? I can certainly see how it would share many of the same logical issues, but does sharing an actor imply that you can have non-atomic operations on the actor, like inconsistent writes and reads? I was under the impression that it would at least be atomic because actors are single-threaded. It even guarantees message ordering, while memory does not in some widely used hardware architectures.
You can of course rebuild data races inside Erlang with the right set of messages, but it's not surprising that you can emulate a Turing-complete computer in a Turing-complete language.
> a thread-safe queue with pairwise ordering guarantees so that all processing on a particular actor's state is effectively atomic
> The big win for the actor model is (just) that it linearizes all operations on a particular substate of the program while allowing other actors' states to be operated on concurrently.
Came here to say exactly those two things. Your comment is as clear as it could be.