Inference is a significant part of ML software infrastructure. Despite the variety of inference frameworks available, the field as a whole can be considered in its early days. This position paper puts forth a range of important qualities that next generation of inference platforms should be aiming for. We present our rationale for the importance of each quality, and discuss ways to achieve it in practice. We propose to focus on data-centricity as the overarching design pattern which enables smarter ML system deployment and operation at scale.

翻译：推论是ML软件基础设施的一个重要部分。尽管现有各种推论框架多种多样,但整个领域可以在最初的几天内得到考虑。本立场文件提出了下一代推论平台应该追求的一系列重要品质。我们提出了每种质量的重要性的理由,并讨论了在实践中实现质量的方法。我们提议把重点放在以数据为中心的特性上,作为总体设计模式,使ML系统能够更聪明地大规模地部署和运行。