Ray: Distributed Computing for All, Part 1

Ray is an open-source Python library that makes it easy to scale compute-intensive programs from a single laptop to a multi-server cluster. By adding a simple `@ray.remote` decorator to a function, you can convert it into a parallel task that automatically utilizes all available CPU cores. These remote tasks are then launched and managed by Ray, which can dramatically reduce the runtime for heavy computations. This allows developers to achieve significant performance gains and parallelize their code with only minimal modifications.