Chapter
Evolution of Neural Networks
01:52 - 08:57 (07:05)
The evolution of neural networks has led to the discovery of powerful techniques such as the Hessian Free Optimizer and the convolutional neural network, making it possible to train large neural networks on a lot of supervised data, which can represent very complicated functions.
Clips
A discussion about the power of deep neural networks and how they can be trained end to end with backpropagation.
01:52 - 05:03 (03:11)
Summary
A discussion about the power of deep neural networks and how they can be trained end to end with backpropagation.
ChapterEvolution of Neural Networks
Episode#94 – Ilya Sutskever: Deep Learning
PodcastLex Fridman Podcast
This transcript covers a discussion on the differences between human brains and artificial neural networks, as well as the possibility of using the human brain as an intuition builder for creating better neural networks.
05:03 - 08:25 (03:22)
Summary
This transcript covers a discussion on the differences between human brains and artificial neural networks, as well as the possibility of using the human brain as an intuition builder for creating better neural networks.
ChapterEvolution of Neural Networks
Episode#94 – Ilya Sutskever: Deep Learning
PodcastLex Fridman Podcast
The success of spiking neural networks in simulating non-spiking neural networks depends on the simulation of non-spiking neural networks in spikes, specifically around questions of backpropagation and deep learning.
08:25 - 08:57 (00:32)
Summary
The success of spiking neural networks in simulating non-spiking neural networks depends on the simulation of non-spiking neural networks in spikes, specifically around questions of backpropagation and deep learning.