Example Concept: The `multiprocessing` module in Python creates separate processes for each task, allowing them to run concurrently on multiple CPU cores. Each process has its own Python interpreter and memory space, which means the GIL is not shared between them, thus enabling true parallel execution for CPU-bound tasks. This is particularly useful for tasks that require significant computation and can benefit from parallel processing.