Concurrency was actually derived from early work on railroads and telegraphy, which is why names such as semaphore are currently employed. Essentially, there was a need to handle multiple trains on the same railroad system in such a way that every train would safely get to their destinations without incurring casualties.

It was only in the 1960s that academia picked up interest in concurrent computing, and it was Edsger W. Dijkstra who is credited with having published the first paper in this field, where he identified and solved the mutual exclusion problem. Dijkstra then went on to define fundamental concurrency concepts, such as semaphores, mutual exclusions, and deadlocks as well as the famous Dijkstra's Shortest Path Algorithm.

Concurrency, as with most areas in computer science, is still an incredibly young field when compared to other fields of study such as math, and it's worthwhile keeping this in mind. There is still a huge potential for change within the field, and it remains an exciting field for all--academics, language designers, and developers--alike.

The introduction of high-level concurrency primitives and better native language support have really improved the way in which we, as software architects, implement concurrent solutions. For years, this was incredibly difficult to do, but with this advent of new concurrent APIs, and maturing frameworks and languages, it's starting to become a lot easier for us as developers.

Language designers face quite a substantial challenge when trying to implement concurrency that is not only safe, but efficient and easy to write for the users of that language. Programming languages such as Google's Golang, Rust, and even Python itself have made great strides in this area, and this is making it far easier to extract the full potential from the machines your programs run on.