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In this episode, we discuss the problem of predicting the future from not only recent events but also from the distant past using Recurrent Neural Networks (RNNs). A example RNN is described which learns to label images with simple sentences. A learning machine capable of generating even simple descriptions of images such as these could be used to help the blind interpret images, provide assistance to children and adults in language acquisition, support internet search of content in images, and enhance search engine optimization websites containing unlabeled images. Both tutorial notes and advanced implementational notes for RNNs can be found in the show notes at: www.learningmachines101.com .

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"LM101-036: How To Predict The Future From The Distant Past Using Recurrent Neural Networks" is available for download from The Internet Archive in "audio" format, the size of the file-s is: 24.23 Mbs, and the file-s went public at Mon Mar 29 2021.

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