A team of computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks--the engines that ...

Johns Hopkins electrical and computer engineers are pioneering a new approach to creating neural network chips—neuromorphic accelerators that could power energy-efficient, real-time machine ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...

A team led by Northwestern University and Shirley Ryan AbilityLab scientists have developed a new technology that can eavesdrop on the hidden electrical dialogues unfolding inside miniature, lab-grown ...

Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

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 ...