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  2. Attentive user interface - Wikipedia

    en.wikipedia.org/wiki/Attentive_user_interface

    Attentive user interfaces (AUI) are user interfaces that manage the user's attention. For instance, an AUI can manage notifications, [1] deciding when to interrupt the user, the kind of warnings, and the level of detail of the messages presented to the user. Attentive user interfaces, by generating only the relevant information, can in ...

  3. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Scaled dot-product attention & self-attention. The use of the scaled dot-product attention and self-attention mechanism instead of an Recurrent neural network or Long short-term memory (which rely on recurrence instead) allow for better performance as described in the following paragraph. The paper described the scaled-dot production as follows:

  4. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    When QKV attention is used as a building block for an autoregressive decoder, and when at training time all input and output matrices have rows, a masked attention variant is used: (,,) = (+) where the mask, is a strictly upper triangular matrix, with zeros on and below the diagonal and in every element above the diagonal.

  5. Transformer (deep learning architecture) - Wikipedia

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

    Multiheaded attention, block diagram Exact dimension counts within a multiheaded attention module. One set of (,,) matrices is called an attention head, and each layer in a transformer model has multiple attention heads. While each attention head attends to the tokens that are relevant to each token, multiple attention heads allow the model to ...

  6. Addenbrooke's Cognitive Examination - Wikipedia

    en.wikipedia.org/wiki/Addenbrooke's_Cognitive...

    The current version of the test is the Addenbrooke's Cognitive Examination-III (ACE-III). This consists of 19 activities which test five cognitive domains: attention, memory, fluency, language and visuospatial processing.

  7. Attention AI experts: The White House wants you - AOL

    www.aol.com/finance/attention-ai-experts-white...

    In a move reminiscent of a wartime recruitment drive, the U.S. government is putting out the call for AI experts and taking steps to fast-track the hiring process. Attention AI experts: The White ...

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  9. Test of everyday attention - Wikipedia

    en.wikipedia.org/wiki/Test_of_everyday_attention

    The Test of Everyday Attention (TEA) is designed to measure attention in adults age 18 through 80 years. The test comprises 8 subsets that represent everyday tasks and has three parallel forms. [1] It assess three aspects of attentional functioning: selective attention, sustained attention, and mental shifting. [2]