The brain comprises billions of neurons organized into an intricate network of highly specialized functional areas. This biological cognitive system can efficiently process vast amounts of multi-modal data to perceive and react to its ever-changing environment. Unlike current AI systems, it does not struggle with domain adaptation, few-shot learning, or common-sense reasoning. Inspiration from neuroscience has benefited AI in the past: dopamine reward signals inspired TD learning, modern convolutional networks mimic the deep, nested information flow in visual cortex, and hippocampal replay of previous experiences has brought about experience replay in reinforcement learning. Recent work at the intersection of neuroscience and AI has made progress in directly integrating neuroscientific data with AI systems and has led to learned representations that are more robust to label corruptions, allow for better generalization in some language tasks, and provide new ways to interpret and evaluate what domain-relevant information is learned by deep neural networks. In this workshop, we aim to examine the extent to which insights about the brain can lead to better AI.
Fri 6:30 a.m. - 7:00 a.m.
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Opening remarks
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Talk
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NOTE: Use the zoom link at the top of this page to enter the meeting. |
Vy Vo 🔗 |
Fri 7:00 a.m. - 8:00 a.m.
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Mike Davies, Intel: Constraining the AI solution space with biological principles
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Talk
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Talk by Mike Davies, Intel Introduction: Vy Vo NOTE: Use the zoom link at the top of this page to enter the meeting. |
Mike Davies · Vy Vo 🔗 |
Fri 8:00 a.m. - 9:30 a.m.
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Panel discussion w/ Allyson Ettinger, Alona Fyshe, Andrea Martin, Dmitry Krotov, Kimberly Statchenfeld, Josh Tenenbaum
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Discussion Panel
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Panel Discussion with Allyson Ettinger, Alona Fyshe, Andrea Martin, Dmitry Krotov, Kimberly Stachenfeld, Josh Tenenbaum Moderator: Leila Wehbe NOTE: Use the zoom link at the top of this page to enter the meeting. |
Allyson Ettinger · Alona Fyshe · Andrea E. Martin · Dmitry Krotov · Joshua B Tenenbaum · Kimberly Stachenfeld · Leila Wehbe 🔗 |
Fri 9:30 a.m. - 10:00 a.m.
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Coffee/Lunch
NOTE: Links will redirect to another page. Come join us in the discussion spaces on GatherTown! |
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Fri 10:00 a.m. - 11:00 a.m.
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Spotlights/Poster Session
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Poster Session
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NOTE: Links will redirect to another page.
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Fri 11:00 a.m. - 12:00 p.m.
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Jack Gallant, UC Berkeley: Neuroscience and AI/ML: Examples from studies of navigation and attention
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Talk
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Talk by Jack Gallant, UC Berkeley Introduction: Alex Huth NOTE: Use the zoom link at the top of this page to enter the meeting. |
· Alexander Huth 🔗 |
Fri 12:00 p.m. - 1:00 p.m.
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Coffee/Lunch
NOTE: Links will redirect to another page. Come join us in the discussion spaces on GatherTown! |
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Fri 1:00 p.m. - 2:00 p.m.
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Anima Anandkumar, NVIDIA & Caltech: Bridging the gap between Artificial and Human Intelligence
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Talk
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Talk by Anima Anandkumar, NVIDIA & Caltech Introduction: Mariya Toneva NOTE: Use the zoom link at the top of this page to enter the meeting. |
Anima Anandkumar · Mariya Toneva 🔗 |
Fri 2:00 p.m. - 3:00 p.m.
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Alona Fyshe, University of Alberta: Do we need to understand the brain before AI can benefit?
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Talk
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Talk by Alona Fyshe, University of Alberta Introduction: Shailee Jain NOTE: Use the zoom link at the top of this page to enter the meeting. |
Alona Fyshe · Shailee Jain 🔗 |
Fri 3:00 p.m. - 4:00 p.m.
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Spotlights/Poster Session
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Poster Session
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NOTE: Links will redirect to another page.
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Fri 4:00 p.m. - 5:00 p.m.
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Kenji Doya, OIST: What can we learn from the brain for future AI?
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Talk
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Talk by Kenji Doya, OIST Introduction: Shinji Nishimoto NOTE: Use the zoom link at the top of this page to enter the meeting. |
Kenji Doya · Shinji Nishimoto 🔗 |
Fri 5:00 p.m. - 5:30 p.m.
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Closing remarks
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Talk
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NOTE: Use the zoom link at the top of this page to enter the meeting. |
Shinji Nishimoto 🔗 |