Q&A: DisruptDC co-founder sees the need for a government/tech nexus

On the same day tech leaders took part in the inaugural summit of the White House’s American Technology Council, former Apple manager Sarah Bonk, who spent more than 14 years at the company, helped launch DisruptDC, a nonprofit, nonpartisan alliance of business leaders she co-founded to improve government and elections.

DisruptDC’s president and CEO, Charles Kolb, served in the Ronald Reagan and George H.W. Bush administrations and was longtime leader of the Committee for Economic Development. He plans to advance reform at the federal, state and local levels by making elections competitive, aligning incentives in policymaking and upgrading government with modern technology. The alliance sees dysfunction in government as bad for business and the overall economy.

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Service Providers

Netflix Climbs the Growth Wave as Cable TV Slides

A few short years ago, Netflix was nothing more than a mail order Blockbuster-type video rental business. Since then, it has been growing rapidly and changing. Believe it or not, Netflix today has more U.S. subscribers than cable TV. That’s an amazing accomplishment for Netflix — and a major hit to traditional cable television. Netflix and cable TV are on opposite sides of the growth wave.

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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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