AI models like artificial neural networks and language models help scientists solve a variety of problems, from predicting the 3D structure of proteins to designing novel antibiotics from scratch.

Kirill Solodskih, PhD, is the Co-Founder and CEO of TheStage AI, as well as a seasoned AI researcher and entrepreneur with ...

A team of researchers has programmed these infomorphic neurons and constructed artificial neural networks from them. The special feature is that the individual artificial neurons learn in a self ...

Neural networks have a remarkable ability to learn ... data that they are able to learn from without having to start from scratch. The algorithm, called a functionally invariant path (FIP ...

Often, each node in a layer is connected to every node in the subsequent layer to send information forward in the network. “When you write code to build an artificial neural network, you're basically ...

Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they ...

Researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have developed a neural network model based on self-attention mechanisms to rapidly predict radiation ...

Swiss Federal Institute of Technology (EPFL) researchers are unraveling the secrets of the fruit fly brain to advance robotics. A team from the institution’s Neuroengineering Laboratory have used ...

How can we characterize the dynamics of neural networks with recurrent connections? How do the time-varying activities of populations of neurons represent things? How are synapse strengths ...

One option is to develop processors that are a better match to the sort of computational needs of neural networks, which require many trips to memory and a lot of communication between artificial ...