Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.
https://braininspired.co/series/brain-inspired/
BI 065 Thomas Serre: How Recurrence Helps Vision
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:
- Visit the Serre Lab website.
- Follow Thomas on twitter: @tserre.
- Good reviews that references all the work we discussed, including the HMAX model:
- Beyond the feedforward sweep: feedback computations in the visual cortex.
- Deep learning: the good, the bad and the ugly.
- Papers about the topics we discuss:
- Complementary Surrounds Explain Diverse Contextual Phenomena Across Visual Modalities.
- Recurrent neural circuits for contour detection.
- Learning long-range spatial dependencies with horizontal gated-recurrent units.