Taking the first step toward more data-centric AI is as simple as recognizing the immense value your data holds and the value inherent in curating it carefully. But centralizing and systematizing your approach to AI isn’t enough—nor is it enough to focus on updating and testing the models you deploy at the expense of data quality. Even better than a data-centric approach to AI is a data-driven approach, one that focuses on both the quality of the data collected and the efficacy of the models this data is used to train.
When it comes to digital transformation, retailers are no longer asking, “What if?” They’re saying the time is now. For the retail industry in particular, integrating vision AI applications into traditional store operations can open up a world of fresh insights that empower better decision making.
Spotting relevant information in an image or video feed can feel a little like looking for a needle in a haystack, but it doesn’t have to require so much time and effort. Training AI to detect objects can help by streamlining and automating the process of generating insights from visual data.
While the COVID-19 pandemic continues through its third year, things have largely returned to normal for most Americans. Mask requirements – once a ubiquitous sign of pandemic life – have mostly disappeared as case numbers have decreased. Personal protective equipment of other sorts, however, isn’t going anywhere. Though you may no longer check for a mask before leaving the house, PPE remains vitally important for many businesses.
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