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University of Cambridge > Talks.cam > Wednesday Seminars - Department of Computer Science and Technology > The Quarks of Attention
The Quarks of AttentionAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Ben Karniely. Attention plays a fundamental role in both natural and artificial intelligence systems. In deep learning, several attention-based neural network architectures have been proposed to tackle problems in natural language processing (NLP) and beyond, including transformer architectures which currently achieve state-of-the-art performance in NLP tasks. In this presentation we will: 1) identify and classify the most fundamental building blocks (quarks) of attention, both within and beyond the standard model of deep learning; 2) identify how these building blocks are used in all current attention-based architectures, including transformers; 3) demonstrate how transformers can effectively be applied to new problems in physics, from particle physics to astronomy; and 4) present a mathematical theory of attention capacity where, paradoxically, one of the main tools in the proofs is itself an attention mechanism. Link to join: https://cl-cam-ac-uk.zoom.us/j/97767639783?pwd=T09GcVJxZUNEUFEvRnZnbWwxeEwzQT09 A recording of this talk is available at the following link: https://www.cl.cam.ac.uk/seminars/wednesday/video/ This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series. This talk is included in these lists:
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