Artificial neural networks learn better when they spend time not learning at all
Researchers discuss how mimicking sleep patterns of the human brain in artificial neural networks may help mitigate the threat of catastrophic forgetting in the latter, boosting their utility across a spectrum of research interests.
A team at Los Alamos National Laboratory has developed a novel approach for comparing neural networks that looks within the "black box" of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants,…
A team has developed a novel approach for comparing neural networks that looks within the 'black box' of artificial intelligence to help researchers understand neural network behavior. Neural networks recognize patterns in datasets; they are used everywhere in society, in applications such as virtual assistants, facial recognition systems and self-driving…
Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and reasoning models like ChatGPT. The principle: during a training phase, the parameters of the network's artificial neurons are optimized in such a way that they can carry out specific tasks, such as…