Building state-of-the-art, energy-efficient reconfigurable dataflow chips ("XPUs") for AI training and inference. Their chips are polymorphic (reconfigurable) and optimized for each AI model to improve dataflow and reduce memory movement through localization, instruction fusion, and layer fusion. This delivers superior energy efficiency, versatility, and throughput compared to traditional accelerators like GPUs and TPUs.