Slowrun
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Human-Like Neural Nets by Catapulting
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arXiv:2606.03938v2 Announce Type: replace Abstract: Multi-epoch training is becoming the standard now that compute is growing faster than the supply of high-quality text. But pretraining a single model saturates within a few passes, long before the compute budget is exhausted. We argue this calls for a conceptual shift from training a single model toward exploring a population of models and aggregating their predictions.
q0: Primitives for Hyper-Epoch Pretraining
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