I will discuss two ideas: (1) virtual laboratories for science and R&D, aiming to introduce an interface between algorithms and domain research that enables AI-driven scale advantages, and (2) AI-based ‘sidekick’ assistants. The purpose of the assistants is to help other agents reach their goals, even when they are not yet able to specify the goal explicitly or it is evolving. Such assistants can help with prior knowledge elicitation, at the simplest, and zero-shot assistance as the worst case. Ultimately they should be helpful for human domain experts in running experiments and solving research problems in virtual laboratories. I invite researchers to join the virtual laboratory movement: domain scientists by hosting a virtual laboratory in their field, methods researchers by contributing new methods to virtual laboratories, and human-in-the-loop ML researchers by developing the assistants.