How wonderful would it be if you could deposit your skin cells at a medical facility and get an organ you need within weeks, ready to be transplanted? For decades, scientists have relentlessly worked to recapitulate functionally and physiologically relevant human organs in the lab. Some approaches rely on engineering an unfeasible number of genes in cells or on external cues like growth factors and mechanical signals. But these organs are far from overcoming the barriers of complexity, reproducibility, and time sensitivity, and are thus not ready to be applied in the real world. In today's episode, Dr. Mo Ebrahimkhani, a scientist at Pittsburgh Liver Research Center, discusses how his team used a machine-learning algorithm (called CellNet) to engineer genetic nodes in the stem cells, resulting in the generation of human liver organoids in less than three weeks. Importantly, these organoids were able to capture the complexity of a mature liver. Also learn here how the body map of organs can contribute to the rapid advancement of the field of regenerative medicine. Inspired by Kevin MacLeod is licensed under CC BY 4.0.