How IT should prep for Apple’s public OS betas

As has become Apple’s standard practice in recent years, the company will soon roll out public betas of iOS 11 and macOS High Sierra. Both are expected to arrive by the end of June.

Public betas can be useful for Apple and other tech companies. They accelerate feedback and can ensure that bugs — including ones that internal testing might not spot — get fixed before the final version of an operating system ships. And because public betas are exciting for early adopters who want to play with new features of an upcoming upgrade before everyone else, they tend to generate useful buzz.

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Google open-sources TensorFlow training tools

Over the past year, Google’s TensorFlow has asserted itself as a popular open source toolkit for deep learning. But training a TensorFlow model can be cumbersome and slow—especially when the mission is to take a dataset used by someone else and try to refine the training process it uses. The sheer number of moving parts and variations in any model-training process is enough to make even deep-learning experts take a deep breath.

This week, Google open-sourced a project intended to cut down on the amount of work in configuring a deep learning model for training. Tensor2Tensor, or T2T for short, is a Python-powered workflow organization library for TensorFlow training jobs. It lets developers specify the key elements used in a TensorFlow model and define the relationships among them.

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