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# 2018 SMLT 3607A |
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The Supervised Machine Learning Trainer 3607A (SMLT-3607A) is a speculative maintenance and training device for the future smart city maintenance person. The project is aimed at exposing the mundane human-machine interactions that will define the future smart city. Any maintenance person, regardless of familiarity with machine learning, can use the SMLT to interface with abnormally behaving smart infrastructure, such as a surveillance camera. The SMLT acts as an industrial grade controller that allows a maintenance person to re-train the smart camera by recording new examples in real time. In ‘conversation’ with his SMLT unit, the maintenance worker will teach the camera what it is seeing and curate the training data set to improve its performance.
Keyur is an interaction designer based in Stuttgart, and has a background in mechanical engineering. He is interested in applying design as a means to bring clarity towards the relationship between people and technology.more
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James is an interaction designer at IDEO and Copenhagen Institute of Interaction Design alumni with a background in philosophy. He is interested in the intersections where design meets impact, tangible meets intangible, and human meets AI.more
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Benedict Hübener is a Berlin based Interaction Designer and recent graduate of CIID. He is especially interested in exploring problems and questions that don't have an easy answer. His goal is to work with people from different professional backgrounds to find the creative and sometimes unexpected solutions to those questions.more
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