Why is It so Difficult for Traditional Industries to Get AI Blessings? — Part3

In the past ten years, most AI research, development, and application have been “software-centric” driven. With massive data support, the software and algorithms are continuously optimizing to obtain higher accuracy. In the case that traditional industries cannot improve the quality and quantity of data, Wu Enda, an AI expert believes that traditional industries should adopt a “data-centric” model. Under this kind of thinking, some good application cases have already emerged in traditional industries. For example, the image recognition AI system in the medical field can help doctors examine CT images, identify tumors and other lesions, and assist doctors in making judgments.


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