Thomas and I discuss the role of recurrence in visual cognition: how brains somehow excel with so few “layers” compared to deep nets, how feedback recurrence can underlie visual reasoning, how LSTM gate-like processing could explain the function of canonical cortical microcircuits, the current limitations of deep learning networks like adversarial examples, and a bit of history in modeling our hierarchical visual system, including his work with the HMAX model and interacting with the deep learning folks as convolutional neural networks were being developed.
Show Notes:
In this first part of our conversation, Paul and I discuss his approach to understanding how the brain (and intelligence) works. Namely, he believes...
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BI NMA 05: NLP and Generative Models Panel This is the 5th in a series of panel discussions in collaboration with Neuromatch Academy, the...
