2017 will be the year the data science and big data community engage with AI technologies

The O’Reilly Data Show Podcast: A look at some trends we’re watching in 2017.

By Ben Lorica
December 29, 2016
The Tulip Stairs and lantern at the Queen's House in Greenwich by Inigo Jones. The Tulip Stairs and lantern at the Queen's House in Greenwich by Inigo Jones. (source: Mcginnly on Wikimedia Commons)

This episode consists of excerpts from a recent talk I gave at a conference commemorating the end of the UC Berkeley AMPLab project. This section pertained to some recent trends in Data and AI. For a complete list of trends we’re watching in 2017, as well as regular doses of highly curated resources, subscribe to our Data and AI newsletters.

As 2016 draws to a close, I see the big data and data science community beginning to engage with AI-related technologies, particularly deep learning. By early next year, there will be new tools that specifically cater to data scientists and data engineers who aren’t necessarily experts in these techniques. While the AI research community continues to tackle fundamental problems, these new sets of tools will make some recent breakthroughs in AI much more accessible and convenient to use for the data community.

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