Most of our audience is at least familiar with seeing the name TensorFlow appear in our coverage. For the uninitiated, Tensor Flow is a machine learning framework/library created by Google that allows developers to leverage the emerging technology for their own uses. Although v1.0 only landed last year, the team behind the project has continued its work, just recently announcing that a preview for v2.0 of the platform would be coming later this year. This update could break compatibility with v1.0 APIs, but with its "focus on ease of use," developers shouldn't run into too much trouble updating.

TensorFlow 2.0 will support more (unnamed) platforms compared to the previous release while removing deprecated/duplicated APIs—apparently a source of confusion for some new developers as they learn to use it. This new release is built around TensorFlow's existing Eager Execution environment, which should make for even easier use and debugging.

There will also be a conversion tool for updating older v1.0 code to v2.0's APIs. In cases where there is no API equivalent, a compatibility library for the older version will also be an option, though it won't be a beneficiary of any future feature development after v2.0 is finalized, and security updates for the library are only promised for a year.

The new version has likely been long in the planning, but it's still subject to change. As part of the transition, the team is holding a set of public design reviews that allow for interested developers to participate in the process by providing feedback and comments.

If you're currently a developer using TensorFlow, you'll want to make sure you update your apps or services to make use of v2.0 when it arrives. To that end, it may also be good to participate in the development process via the public comments, and follow along with things on the project's mailing list.