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Ethan Caballero–Broken Neural Scaling Laws
The Inside View
How to Predict Double Descent in Deep Neural Networks
Double descent is the most famous example of non-monotonic scaling for deep neural networks. Future systems are probably going to have non-Monotonic scaling as one that scales far enough to approach AGI so you want some kind of like functional form that's able to express and extrapolate it. In my experience double descent only happens in like toy experiments.
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