A scientist combines attention neural networks with graph neural networks to better understand and design proteins. The approach couples the strengths of geometric deep learning with those of language models to predict existing protein properties and envision new proteins that nature has not yet devised. The model turns numbers, descriptions, tasks, and other elements into symbols for neural networks to use.