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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    In theory, classic RNNs can keep track of arbitrary long-term dependencies in the input sequences. The problem with classic RNNs is computational (or practical) in nature: when training a classic RNN using back-propagation, the long-term gradients which are back-propagated can "vanish", meaning they can tend to zero due to very small numbers creeping into the computations, causing the model to ...

  3. ELMo - Wikipedia

    en.wikipedia.org/wiki/ELMo

    The first forward LSTM would process "bank" in the context of "She went to the", which would allow it to represent the word to be a location that the subject is going towards. The first backward LSTM would process "bank" in the context of "to withdraw money", which would allow it to disambiguate the word as referring to a financial institution.

  4. Eyewitness News - Wikipedia

    en.wikipedia.org/wiki/Eyewitness_News

    Identified as Eyewitness 7 News from 1974 to 1979, and as 7 Eyewitness News from 1979 to 1994; has identified as 7 On Your Side since 2011. Harlingen / Brownsville / McAllen, TX: KRGV-TV: ABC Used in the mid-1970s; has identified as NewsChannel 5 since 2000 and as of September 2009, it is now known as Channel 5 News. KGBT: Antenna TV ...

  5. Eyewitness (British TV series) - Wikipedia

    en.wikipedia.org/wiki/Eyewitness_(British_TV_series)

    Eyewitness is a documentary series. Each half-hour episode focuses on a single subject in the field of natural science, such as the Solar System or the various functions of the human body, similar in form to the book series on which it was based, with most being based, in part or in whole, off of existing book titles at the time, with few exceptions (though some titles, such as Planets and ...

  6. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [35]

  7. Long-term memory - Wikipedia

    en.wikipedia.org/wiki/Long-term_memory

    Long-term memory (LTM) is the stage of the Atkinson–Shiffrin memory model in which informative knowledge is held indefinitely. It is defined in contrast to sensory memory, the initial stage, and short-term or working memory, the second stage, which persists for about 18 to 30 seconds.

  8. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    [7] [8] In 1933, Lorente de Nó discovered "recurrent, reciprocal connections" by Golgi's method, and proposed that excitatory loops explain certain aspects of the vestibulo-ocular reflex. [ 9 ] [ 10 ] During 1940s, multiple people proposed the existence of feedback in the brain, which was a contrast to the previous understanding of the neural ...

  9. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

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