Researchers report they have discovered a way for humans to maintain control over artificial intelligent robots.
As robots become more autonomous, people will regard them as more responsible for accidental wrongdoing.
A new deep learning algorithm is able to identify the gender of a writer based on written text with 80% accuracy.
Artificial intelligence technology can identify early signatures of Parkinson's disease based on images of the retina vasculature taken from a simple eye test.
A newly developed AI tool can identify "deepfakes" of faces by examining the light reflection in the eyes of the images. The system is 94% accurate at detecting deepfakes.
Combining artificial intelligence and computer vision technology, researchers were able to determine anxiety and depression risks from peoples' Twitter profile pictures.
A new computational model predicts how information deep inside the brain could flow from one network to another, and how neural network clusters can self optimize over time.
Machine learning is unable to tell the difference in brain activity between a lab-grown mini-brain and that of a preterm infant who has reached full-term.
A new deep learning algorithm can predict those at risk of psychosis with 93% accuracy by examining the latent semantic content of an individual's speech.
Before the 48-week mark of life, it is easier for an AI algorithm to determine the exact age of a baby, but not its gender based on temperament data. After 48 weeks, gender classification improved for all algorithms, suggesting gender differences in infancy become more accentuated at this point in life.
Researchers have created a hybrid neural network where biological and artificial neurons in different parts of the world were able to communicate via the internet through a hub of memristive synapses.
Combining neuroimaging data with deep convolutional neural networks, researchers were able to predict where people would direct their attention and gaze at images of natural scenes.
