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AI&B have similarities (and differences); (i) many processing units (ii) are highly interconnected by weights (iii) that are learned from data (everything else about AI&B is different). What can we learn for both from the similarities and differences that power computations in AI&B? We will address (a) this question, (b) AI&B opportunities at WU and (c) AI&B results from a specific question in vision research.

This lecture was made possible by the William C. Ferguson fund.

  • Justine Craig-Meyer
  • Nayong Quan
  • Maricela Alvarado

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