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BI 129 Patryk Laurent: Learning from the Real World
Support the show to get full episodes, full archive, and join the Discord community.
Patryk and I discuss his wide-ranging background working in both the neuroscience and AI worlds, and his resultant perspective on what's needed to move forward in AI, including some principles of brain processes that are more and less important. We also discuss his own work using some of those principles to help deep learning generalize to better capture how humans behave in and perceive the world.
- Patryk's homepage.
- Twitter: @paklnet.
- Related papers
- Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network.
0:00 - Intro
2:22 - Patryk's background
8:37 - Importance of diverse skills
16:14 - What is intelligence?
20:34 - Important brain principles
22:36 - Learning from the real world
35:09 - Language models
42:51 - AI contribution to neuroscience
48:22 - Criteria for "real" AI
53:11 - Neuroscience for AI
1:01:20 - What can we ignore about brains?
1:11:45 - Advice to past self
View all episodes
By Paul Middlebrooks
4.9
133133 ratings
Support the show to get full episodes, full archive, and join the Discord community.
Patryk and I discuss his wide-ranging background working in both the neuroscience and AI worlds, and his resultant perspective on what's needed to move forward in AI, including some principles of brain processes that are more and less important. We also discuss his own work using some of those principles to help deep learning generalize to better capture how humans behave in and perceive the world.
- Patryk's homepage.
- Twitter: @paklnet.
- Related papers
- Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network.
0:00 - Intro
2:22 - Patryk's background
8:37 - Importance of diverse skills
16:14 - What is intelligence?
20:34 - Important brain principles
22:36 - Learning from the real world
35:09 - Language models
42:51 - AI contribution to neuroscience
48:22 - Criteria for "real" AI
53:11 - Neuroscience for AI
1:01:20 - What can we ignore about brains?
1:11:45 - Advice to past self
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