Decision-making often involves trial and error, but conventional models assume we always act optimally based on past ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Throughout their everyday lives, humans are typically required to make a wide range of decisions, which can impact their well ...

"The use of neural networks in the model allows us to detect this type of marker in a more flexible way, solving the problem of lighting for all phases of the detection and decoding process ...

Deep Neural Network (DNN): A multi-layer machine learning model that effectively captures complex, non-linear patterns from high-dimensional data.

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.

To help them explain the shocking success of deep neural networks, researchers are turning to older but better-understood models of machine learning.

Per Bloomberg, the round values Liquid AI at over $2 billion. Liquid AI aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network.