Uploaded January 2023 | Updated September 2026, 7 hours ago
The Forward-Forward algorithm from Geoffry Hinton is a backpropagation alternative inspired by learning in the cortex. It tackles several issues with backprop that would allow it to be run much more efficiently. Hopefully research like this continues to pave the way toward full-hardware integrated AI chips in the future.
Outline
0:00 - Intro
1:13 - ClearML
2:17 - Motivation
5:40 - Forward-Forward Explained
13:54 - MNIST Example
18:54 - Top-Down Interactions
26:00 - More Examples / Results
27:41 - Sleep & Phased Learning
29:36 - Related Ideas
30:38 - Learning Fast & Slow
32:35 - Mortal Computation
ClearML - bit.ly/3GtCsj5
Social Media:
YouTube - youtube.com/c/EdanMeyer
Twitter - twitter.com/ejmejm1
Sources:
Paper - https://www.cs.toronto.edu/~hinton/FFA13.pdf
The Forward-Forward algorithm from Geoffry Hinton is a backpropagation alternative inspired by learning in the cortex. It tackles several issues with backprop that would allow it to be run much more efficiently. Hopefully research like this continues to pave the way toward full-hardware integrated AI chips in the future.
Outline
0:00 - Intro
1:13 - ClearML
2:17 - Motivation
5:40 - Forward-Forward Explained
13:54 - MNIST Example
18:54 - Top-Down Interactions
26:00 - More Examples / Results
27:41 - Sleep & Phased Learning
29:36 - Related Ideas
30:38 - Learning Fast & Slow
32:35 - Mortal Computation
ClearML - bit.ly/3GtCsj5
Social Media:
YouTube - youtube.com/c/EdanMeyer
Twitter - twitter.com/ejmejm1
Sources:
Paper - https://www.cs.toronto.edu/~hinton/FFA13.pdf
