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    Dust Claims Transformer Pretraining Without Backpropagation▼Dust: Pretraining Transformers Without BackpropagationYhn2433 min ago

    Researchers at QLabs have introduced Dust, a method for pretraining transformer models without using backpropagation. The announcement has drawn attention in the machine learning community, where alternatives to backpropagation have long been pursued for their potential efficiency and hardware benefits. Readers are debating whether the approach can match the performance of standard gradient-based training at scale.