Achieving Breakthrough Performance for AI Inferencing

The ultimate goal for Philips is to offer artificial intelligence (AI) to its end customers without significantly increasing the cost of the customers’ systems and without requiring modifications to the hardware deployed in the field. Using the Intel® Distribution of OpenVINO™ Toolkit along with efficient multi-core processing from Intel Xeon Scalable processors, Philips was able to achieve a speed improvement of 188.1x for the bone-age-prediction model, and a 37.7x speed improvement for the lung-segmentation model over the baseline measurements.