Machine learning (ML) models continue to evolve in scale and algorithmically, a trend that burdens system developers with ever-increasing compute and power requirements for training and deployment. How to meet the demands? Tech giant Nvidia’s A100 high-performance graphics processing unit (GPU) dominated the AI accelerator market until Google joined the campaign in 2016 with its Tensor Processing Units (TPUs). This week, Google introduced its newest entry,