AI Faces Speed Bumps and Potholes on Its Road From the Research Lab to Everyday Use

IEEE Spectrum  October 1, 2019
According to panelists wrapping up a day of discussions at the IEEE AI Symposium 2019, implementing machine learning in the real world isn’t easy. The tools are available and the road is well-marked—but the speed bumps are many. As the field is changing rapidly – there are new language models coming out every month, and new tools and the foundational elements are shifting so rapidly there aren’t any true experts at this point. And then there is the decision of where exactly machine learning should happen—on site, or in the cloud? Data scientists are building things that might change the ways other people in the organization work hence rolling machine learning technology into operation can hit resistance from across the company…read more.

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