SAMSUNG SDS
“ Annotation or labeling is the principal obstacle in making AI models , which can be reduced 90 % by AI ”
PATRICK BANGERT TITLE : VP OF AI LOCATION : SAN JOSE , CALIFORNIA
PATRICK BANGERT VP OF AI , SAMSUNG SDS
Patrick heads the AI Division at Samsung SDSA . He is responsible for Brightics AI
Accelerator , a distributed ML training and automated ML product , and AutoLabel , an automatic image data annotation and modelling tool primarily targeted at the medical imaging community . Among his other responsibilities is to act as a visionary for the future of AI at Samsung . Before joining Samsung , Patrick spent 15 years as CEO at algorithmica technologies , a machine learning software company serving the chemicals and oil and gas industries . Prior to that , he was assistant professor of applied mathematics at Jacobs University in Germany , as well as a researcher at Los Alamos National Laboratory and NASA ’ s Jet Propulsion Laboratory . Patrick obtained his machine learning PhD in mathematics and his Masters in theoretical physics from University College London .
EXECUTIVE BIO dataset of images . We want to create such datasets and models in a partnership with Samsung SDS . The skin , in addition to being the largest organ , is also the most visible . This accessibility has resulted in an exponential increase in the number of images . The skin is , and will likely continue to be , the most imaged organ . While there is potential for democratising diagnosis for the general public , the impact to mental health through image distortion cannot be overstated .”
Samsung ’ s ultimate AI toolkit : the Brightics AI Accelerator The jewel in the crown of Samsung ’ s AI efforts is the AutoLabel facility in the Brightics AI Accelerator platform . Dr . Hankyu Moon , the leader of team behind AutoLabel answers in three parts why this toolkit is so crucial : “ Firstly , in the case of imaging , for example , an annotation is typically a manual drawing of an outline around something that ' s important and assigning the category name to it . We see this in street scenes for autonomous vehicles , where we might draw an outline around people to say ‘ okay , this is a person who denotes an obstacle that the car must not hit ’.”
These annotations , he explains , are made very quickly by the AutoLabel facility , which
aimagazine . com 35