A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...
A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...
Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...
In the realm of artificial intelligence and machine learning, neural networks have proven to be a powerful tool for solving complex problems. These networks, inspired by the workings of the human ...
A technical paper titled “Training neural networks with end-to-end optical backpropagation” was published by researchers at University of Oxford and Lumai Ltd. “Optics is an exciting route for the ...
Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...
The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...
Born in London, England on December 6, 1947, Geoffrey Hinton is a British-Canadian cognitive psychologist and computer scientist whose peculiar input has ensured foundational contributions to the ...
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