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The Diversity in Faces (DiF) is a large and diverse dataset that seeks to advance the study of fairness and accuracy in facial recognition technology.The first of its kind available to the global research community, DiF provides a dataset of annotations of one million human facial images. How do we measure and ensure diversity for
For computer vision and facial recognition systems to work reliably, they need training datasets that approximate real-world conditions. So far, researchers have had access to only a small number of image datasets, many of which are heavily populated with still pictures of fair-skinned men. This limitation impacts the accuracy of the technology when it comes
IBM recently unveiled what it claimed was the world’s first commercial quantum computer. While the announcement of the Q System One wasn’t scientifically groundbreaking, the fact that IBM sees this as a commercial product that organisations (if not individuals) will want to use is an important breakthrough. IBM has taken a prototype technology that has