Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising ...

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Neural architecture search is the task of ...

A new approach to designing AI based on biologically inspired architecture could cut the number of data centers needed to run ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...

Recent advances in neuroscience, cognitive science, and artificial intelligence are converging on the need for representations that are at once distributed, ...

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

Exactly when the process started no one knows, but fossils from the Cambrian period some 540m years ago show life on Earth going through a remarkable period of diversification. The point at which it ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...