Machine learning is rapidly transforming the chemical domain into a truly data-driven science. At the same time, high-throughput experimentation and robotic execution opens the possibility for algorithms to take over synthesis planning and experimental execution. This acceleration of research produces the data required for artificial intelligence operation, and shifts the boundaries of what is possible to synthesize by classical methodologies. The emergency of these technologies are discussed, and how they will affect the future of chemical research.