CNH engaged Agrishow 2025 visitors with a talking robot which answered questions and followed commands of voice prompts offering a glimpse into the future of machinery operation.

This framework could then be integrated with existing neuroscience theories. To develop their framework, they employed artificial neural networks (ANNs) trained via reinforcement learning.

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

Using a neural network trained with simulations of supermassive black holes, astronomers have found that the one at the center of the Milky Way, Sagittarius A*, likely rotates at maximum speed.

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Artificial intelligence (AI) is increasingly becoming integrated into our lives in both our personal and professional environments from virtual assistants, navigation, smart appliances and social ...

Google said in the coming months educators will be able to assign Gems and notebooks grounded in class materials directly to students through Google Classroom through new teacher-led experiences. With ...

Bio-electronic medicine is a new form of therapy that uses electrical pulses to modulate nerve activity. The small implant ...

The purpose of filters’ inverse modeling is to acquire the values of physical or geometrical parameters for the specified electrical response. In this article, a dimensionality reduction (DR) strategy ...

Wafer-scale accelerators for AI applications can deliver far more computing power with much greater energy efficiency.

For the accurate prediction of a complex system, determining how to model well it is essential. A classical simulation modeling method that abstracts causality between inputs and outputs utilizing ...