Evolution allows life to explore almost limitless diversity and complexity. Scientists hope to recreate such open-endedness in the laboratory or in computer simulations, but even sophisticated computational techniques like machine learning and artificial intelligence can’t provide the open-ended tinkering associated with evolution. Here, common barriers to open-endedness in computation and biology were compared, to see how the two realms might inform each other, and ultimately enable machine learning to design and create open-ended evolvable systems.