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Scientists at Lawrence Berkeley National Laboratory have developed a breakthrough technology that could greatly develop the field of optical computing and devic

A machine learning approach from diffusion tensor imaging (DTI) multi-spectral diffusion weighted imaging (DWI) showed prediction of gait dysfunction in PD according to a study released today at the International

If you are looking to learn more about ChatGPT or AI models in general this list of 100 ChatGPT terms and their meanings might help you under

In the Southwestern Atlantic, the Falkland Current intrudes onto the South American shelf, resulting in the meeting of two water masses which are completely different in temperature and dynamic characteristics, thus generating the Southwestern Atlantic Front (SAF). Therefore, the SAF has prominent characteristics of thermal and dynamics. The current ocean front detection is mainly by performing gradient operations on sea surface temperature (SST) data, where regions with large temperature gradie...

This is the second article in that series, and is associated with our Intro to Deep Learning Github repository where you can find practical examples of many deep learning applications and tactics…

Infants portray suggestive unique cries while sick, having belly pain, discomfort, tiredness, attention and desire for a change of diapers among other needs. There exists limited knowledge in accessing the infants’ needs as they only relay information through suggestive cries. Many teenagers tend to give birth at an early age, thereby exposing them to be the key monitors of their own babies. They tend not to have sufficient skills in monitoring the infant’s dire needs, more so during the ear...

A group of researchers have developed a novel photonic neural network accelerator using a non-volatile Opto-Resistive RAM Switch to attain programmable nonlinear activation functions.

Machine learning techniques are now very common in many spheres, and there is a growing popularity of these approaches in macroeconomic forecasting as well. Are these techniques really useful in the prediction of macroeconomic outcomes? Are they superior in performance compared to their traditional counterparts? We carry out a meta-analysis of the existing literature in order

Embedding Artificial Intelligence onto low-power devices is a challenging task that has been partly overcome with recent advances in machine learning and hardware design. Presently, deep neural networks can be deployed on embedded targets to perform different tasks such as speech recognition, object detection or Human Activity Recognition. However, there is still room for optimization of deep neural networks onto embedded devices. These optimizations mainly address power consumption, memory and ...