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 ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
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 ...
Neural networks can be used to classify data and make predictions. For example, you might want to predict the political party affiliation (Democrat, Republican, Independent) of a person based on ...
The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...
For example, the calculus derivative of the hyperbolic tangent function is (1 - y) (1 + y). Because the back-propagation algorithm requires the derivative, only functions that have derivatives can be ...
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