Technology

In the era of big data, traditional computational methods often struggle to process and analyze massive data sets due to memory constraints. However, a breakthrough algorithm developed at Los Alamos National Laboratory is set to revolutionize data analysis by overcoming these limitations. This highly scalable machine-learning algorithm has demonstrated the ability to process data sets
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Google, the technology giant that transformed the way we search the internet, is currently facing its most significant legal challenge in a Washington court. Accused by the US government of acting unlawfully to establish its overwhelming dominance in online search, Google is now embroiled in a landmark antitrust case. With over ten weeks of testimony
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In recent years, researchers have made significant progress in the field of soft robotics, creating robots that can navigate through mazes without human or computer direction. Now, a new study published in the journal Science Advances presents a “brainless” soft robot that can navigate even more complex and dynamic environments. This innovative soft robot is
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Artificial Intelligence (AI) tools have become increasingly prevalent in classrooms, with the potential to revolutionize education. However, the United Nations Educational, Scientific and Cultural Organization (UNESCO) is calling for strict regulations and guidelines to be put in place to protect students from potential harm. In its recent guidance, UNESCO warns that the ethical implications of
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Precisive real-time prediction of the movement of nearby vehicles or the future trajectory of pedestrians is essential for safe autonomous driving. A research team from the City University of Hong Kong (CityU) has recently developed an innovative AI system that significantly improves predictive accuracy in dense traffic scenarios. This breakthrough technology also offers increased computational
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In the field of machine learning, label distribution learning (LDL) has emerged as a promising approach to tackle the challenges posed by label ambiguity. Traditional supervised learning scenarios often rely on single-label annotations, which can be costly and time-consuming. However, with LDL, the annotation process becomes more complex and costly due to the distribution of
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