Forward-Forward Algorithm is a new type of neural network training algorithm that's supposed to replace backpropagation. It was proposed by Geoffrey Hinton recently.
Link to the paper: https://www.cs.toronto.edu/~hinton/FFA13.pdf
Link to a Twitter thread with a less technical explanation: https://twitter.com/martin_gorner/status/1599755684941557761
Link to the leaderboard: https://paperswithcode.com/sota/image-classification-on-imagenet
If at the end of 2023 there is at least one entry in the leaderboard that uses Forward-Forward Algorithm (FFA), market resolves "Yes". The entry doesn't have to use exclusively FFA, it can use a mix of FFA and backpropagation.
65% accuracy is low, this threshold is to prevent proof-of-concept entries that aren't competitive with backprop at all.
If an entry uses barely any FFA but technically qualifies, I'll ask for help in resolving the market.
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