Google Adds TPUs to ML Engine, Updates Kubernetes
As the amount of machine learning training data soars, so too does demand for new tools that will accelerate the process. With that in mind, Google Cloud announced the beta release of a new feature that allows users to speed training by running Tensor processing units (TPU) on its machine learning engine.
The company also announced general availability of the latest release of Google Kubernetes Engine, its platform for managing applications containers at scale. Among the goals is expanding enterprise adoption of the popular cluster orchestrator.
The TPU capability released to Google Cloud Platform customers this week is the latest in a steady stream of cloud offerings design to contrast its platform from its public cloud rivals. The cloud TPU was released this time last year as part of Google’s “AI-first” strategy.
Google said Monday (May 21) the latest version of its Kubernetes Engine released this week adds support for shared virtual private clouds. The new feature is intended to improve control of enterprise networks as well as regional clusters and persistent storage.
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