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Deep thinking

机译:深层思考

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摘要

Artificial intelligence (AI) is an umbrella term for the methodologies used to make machines behave in a way we would consider'smart. Deep learning is a method of AI, and a subset of machine learning, that enables computers to imitate human learning. The recycling industry continues to be transformed by deep learning because it enables humans' cognitive abilities to be replicated on machines or computers for use in sorting tasks. In classical machine learning, an expert supplies the algorithm with only the most useful data it requires to enable it to separate different materials. In deep learning, the algorithm can be trained using the raw data - thousands of images, for example - to identify material that needs to be separated during the sorting process. Tomra Sorting has used AI in its machines since the early days of sorting, but the technology has evolved significantly over the years. Today, by mimicking the activity of large numbers of layers of neurons in the human brain, deep-learning algorithms can perform clearly defined, complex cognitive tasks in the same way as humans - but much faster and, in some cases, with much greater accuracy.
机译:人工智能(AI)是用于制造机器的方法的伞术语,以便我们考虑的方式。深度学习是AI的一种方法,以及机器学习的子集,使计算机能够模仿人类学习。循环行业继续通过深度学习改造,因为它使人类能够在机器或计算机上复制的人的认知能力,以用于排序任务。在古典机器学习中,专家只能用最有用的数据提供算法,使其能够分离不同的材料。在深度学习中,可以使用原始数据训练算法 - 例如 - 例如 - 以识别在排序过程中需要分离的材料。自从排序的早期分类以来,Tomra Sorting在其机器中使用了AI,但该技术在多年来的显着发展。今天,通过模拟人类大脑中大量神经元的活动,深入学习算法可以以与人类相同的方式进行清晰定义,复杂的认知任务 - 但在某些情况下具有更大的准确性。

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  • 来源
    《Wastes Management》 |2020年第11期|53-54|共2页
  • 作者

    Brian Gist;

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  • 正文语种 eng
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