Chapter
The Importance of Feedback and Recursive Inference in Neural Networks
1:06:06 - 1:12:58 (06:52)
The speaker discusses the importance of feedback connections, recursive inference, lateral connections, and coming to the best explanation of a scene as the problems to solve while also tackling recognition, segmentation, top-down attention, and higher level cognition.
Clips
The paper highlights the importance of feedback connections, recursive inference, lateral connections, and coming to the best explanation of a scene to solve recognition and segmentation problems.
1:06:06 - 1:09:15 (03:08)
Summary
The paper highlights the importance of feedback connections, recursive inference, lateral connections, and coming to the best explanation of a scene to solve recognition and segmentation problems. It argues that current deep learning systems take a lot of training data, and the model presented in the paper trains quickly with very little data.
ChapterThe Importance of Feedback and Recursive Inference in Neural Networks
Episode#115 – Dileep George: Brain-Inspired AI
PodcastLex Fridman Podcast
Despite advances in AI research, there is often a gap between the hype of what's being marketed and the reality of what's actually being researched.
1:09:16 - 1:09:55 (00:39)
Summary
Despite advances in AI research, there is often a gap between the hype of what's being marketed and the reality of what's actually being researched.
ChapterThe Importance of Feedback and Recursive Inference in Neural Networks
Episode#115 – Dileep George: Brain-Inspired AI
PodcastLex Fridman Podcast
Laypeople and journalists often misunderstand and sensationalize the capabilities of neural networks, leading to unfair criticisms of the researchers who work with them.
1:09:56 - 1:12:58 (03:02)
Summary
Laypeople and journalists often misunderstand and sensationalize the capabilities of neural networks, leading to unfair criticisms of the researchers who work with them.