The researchers chose a kind of neural network architecture known as a generative adversarial network (GAN), originally invented in 2014 to generate images. A GAN is composed of two neural networks — ...

By contrast, most humans in the same situation will admit they don't know the answer. Building a more human-like neural network can prevent this duplicity and lead to more accurate answers.

When Bazhenov and colleagues applied this approach to artificial neural networks, they found that it helped the networks avoid catastrophic forgetting. “It meant that these networks could learn ...

NTT discovered how artificial neural networks show human-like responses to sound, aiding in the development of more efficient medical devices.

Biological and artificial neurons recognize 3D objects in similar ways. Spitting Image A team of scientists found a surprising similarity between how human brains and artificial neural networks ...

Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. PLOS Biology, 2023; 21 (12): e3002366 DOI: 10.1371 ...

Neural networks, a type of artificial intelligence, can now combine concepts in a way that's closer to human learning than past models have achieved. (Image credit: imaginima via Getty Images) ...

What can deep neural networks teach us about human thought? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the ...

Over the course of their lives, humans can sometimes acquire fear responses to specific stimuli, animals, objects or situations, typically following adverse experiences or traumatic events.

Heekeren and colleagues review neurophysiological and neuroimaging studies of monkeys and humans making perceptual decisions, highlighting both the similarities and the differences in their ...