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Backpropagation, introduced in 1986, is a widely used and effective method for training neural networks, but it has drawbacks like high memory usage and limited parallelism. Researchers at the University of Oxford have now proposed a new algorithm that trains neural networks without relying on backpropagation, potentially overcoming these limitations. More details


Backpropagation, introduced in 1986, is a widely used and effective method for training neural networks, but it has drawbacks like high memory usage and limited parallelism. Researchers at the University of Oxford have now proposed a new algorithm that trains neural networks without relying on backpropagation, potentially overcoming these limitations. More details

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