Neurosymbolic AI combines the learning of LLMs with teaching the machine formal rules that should make them more reliable and energy efficient.

What the Apple paper shows, most fundamentally, regardless of how you define AGI, is that LLMs are no substitute for good well-specified conventional algorithms. (They also can’t play chess as well as ...

This repository is the open source code for my latest work: "Through-the-Wall Radar Human Activity Recognition WITHOUT Using Neural Networks", submitted to arXiv. Fig. 1. Current works in this field ...

What Is Image-to-Video AI and Why It Matters Image-to-video AI is a breakthrough in creative technology. It transforms static ...

Network meta-analyses will further elaborate on these findings by constructing network diagrams that visually compare the efficacy of various interventions. These diagrams will be structured so that ...

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 ...

A new study has revealed compelling evidence that brain criticality—a dynamic balance between neural excitation and ...

Imagine a computer that does not rely only on electronics but uses light to perform tasks faster and more efficiently. A ...

In order to understand the structure and functioning of the brain, neuroscientists need to study the complex, ...

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