this post was submitted on 14 Nov 2023
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Machine Learning
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The bottleneck is the total compute budget devoted to training, so while I'm quite certain that stacking a few more layers can be done and would have some benefit, it might well be that spending the same extra compute on a larger context window or 'wider' layers or simply doing more iterations on the same data would have a larger benefit than more layers, and if the people training the very large models think so, they would do these other things instead of stacking more layers.