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AutoML Vision: Among the Fastest and Easiest Way to Adopt AI for Your Enterprise

What’s among the largest impediment to the adoption of AI within enterprises? Not enough access to skills. According to 80 percent of business respondents to an EY survey, the top challenge to an enterprise AI program is the lack of requisite talent.

What companies need today is a way to facilitate—and therefore accelerate—the adoption of AI. There are a few challenges that need to be overcome. Two of the most critical challenges include the data science skills required to create customized models, and the right IT skills to power the underlying infrastructure.

Both of these skills are hard and expensive to come by.

There are ways around this problem. Google Cloud’s recently launched AutoML Vision is one such solution. It significantly lowers the amount of IT and data science heavy lifting required to start customized machine learning applications around computer vision.

That’s possibly one of the reasons why Google is the most popular cloud provider for data scientists, according to the State of Data Science.

In this short and simple-to-understand video, Yufeng Guo, Developer and Machine Learning Advocate at Google Cloud, walks you through a real use case of AutoML Vision.

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