Neural networks are computational models inspired by the organisation and function of biological neurons. They consist of layers of interconnected units (neurons), each computing a weighted sum of ...

New study shows that as neural networks learn, they adopt patterns of activity similar to real-life neuron firing patterns in ...

Neural activity during the performance of a stereotyped behavioral task is often described as low-dimensional, occupying only a limited region in the space of all firing-rate patterns. This region has ...

A recurrent neural network is a type of artificial neural network commonly used in speech recognition and natural language processing. Recurrent neural networks recognize data's sequential ...

Much of what makes us human is the power of our brain and cognitive abilities. The human brain is an organ that gives humans the power to communicate, imagine, plan and write. However, the brain is a ...

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, ...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...

The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications - from autonomous driving to robotics. Researchers at the Technical ...

Learning is often thought to require a brain. But learning is a broad concept that does not necessarily depend on neurons. If ...

A new study has used a type of machine learning called a neural network to reveal how different kinds of training can change ...