
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:
Support the show to get full episodes and join the Discord community. David runs his lab at NYU, where they stud`y auditory cognition, speech...
Kanaka and I discuss a few different ways she uses recurrent neural networks to understand how brains give rise to behaviors. We talk about...
Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver...