AI network simulations become unstable following continuous periods of unsupervised learning. When the networks were exposed to states that are analogous to human brain waves during sleep, the stability was restored.
Artificial IntelligenceDeep LearningFeaturedMachine LearningNeurologyNeuroscienceNeurotechOpen Neuroscience Articles··7 min read
A new deep learning algorithm helped researchers identify a powerful new antibiotic compound that kills many of the world's most problematic, disease-causing bacterias, including those which have so far been resistant to common antibiotics.
Artificial IntelligenceDeep LearningFeaturedMachine LearningNeuroscienceNeurotechOpen Neuroscience ArticlesRobotics··3 min read
A biological neural network which is sculpted by evolution provides a scaffolding to facilitate quick and easy learning.
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EmoNet, a new convolutional neural network, can accurately decode images into eleven distinct emotional categories. Training the AI on over 25,000 images, researchers demonstrate image content is sufficient to predict the category and valence of human emotions.
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A convolutional neural network, designed by researchers at MIT, uses MRI datasets to find anatomical structures of the brain. The system could help in diagnosing and treating a range of brain conditions.
A recurrent neural network algorithm demonstrates short-term synaptic plasticity can support short term maintenance of information, providing the memory delay period is sufficiently short.
It might start to get easier to distinguish between real and fake images, thanks to a new deep learning system developed by NYU. The system is able to implant digital watermarks using an artificial neural network and spot manipulated photos and videos.
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Using a Siamese neural network, a new deep learning system dubbed Ghostwriter is able to distinguish the writing styles between different texts. The algorithm compares a student's current written work against past examples of their prose, providing a percentage score for similar writing styles. The new system could be used to determine if a student has plagiarized their work, or if it is an original piece.
Researchers report artificial neural networks contain subnetworks that are considerably smaller, yet capable of being trained to make equally accurate predictions. Many subnetworks can learn to make accurate predictions much faster than the original networks.