Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals

Fusing explainable artificial intelligence (X-AI, AI with decipherable decision making process) and exascale computing ― 1018, or a quintillion, floating-point operations per second (flops) level of performance ― can help plant and computational biologists achieve breakthroughs in designing multi-criteria crop ideotypes (i.e. crops with the optimal combination of traits for a given environment), mapping global climatypes, revealing the underlying biologically relevant interactions (e.g. SNP correlation network, 3D-interactome network) and, consequently, accelerating food and energy plant breeding programs widely recognized as critical to achieving the United Nations Sustainable Development Goals.