The automation of data collection opens up exciting opportunities for machine learning and data science applications in chemistry, fueling accelerated research progress and discoveries. Looking ahead, we envision even greater possibilities through enhanced communication and collaboration among multiple ChemOS 2.0 platforms, fostering seamless cooperation between different laboratories. ChemOS 2.0 lays a solid foundation for designing novel SDLs, making them more modular, robust and making their units transferable. This advancement supposes an step forward in the quest of revolutionize materials research through streamlined and efficient self-driving laboratories.