AI tagged posts

As artificial intelligence and deep learning techniques become increasingly advanced, engineers will need to create hardware that can run their computations both reliably and efficiently. Neuromorphic computing hardware, which is inspired by the structure and biology of the human brain, could be particularly promising for supporting the operation of sophisticated deep neural networks (DNNs).

Researchers at Graz University of Technology and Intel have recently demonstrated the huge potential of neuromorphic computing hardware for running DNNs in an experimental setting...

Artificial intelligence (AI) algorithms trained on real astronomical observations now outperform astronomers in sifting through massive amounts of data to find new exploding stars, identify new types of galaxies and detect the mergers of massive stars, accelerating the rate of new discovery in the world’s oldest science.

But AI, also called machine learning, can reveal something deeper, University of California, Berkeley, astronomers found: Unsuspected connections hidden in the complex mathematics arising from general relativity—...

New approach paves the way for larger, more complex metalenses. Compact and lightweight metasurfaces — which use specifically designed and patterned nanostructures on a flat surface to focus, shape and control light — are a promising technology for wearable applications, especially virtual and augmented reality systems. Today, research teams painstakingly design the specific pattern of nanostructures on the surface to achieve the desired function of the lens, whether that be resolving nanoscale features, simultaneously producing several depth-perceiving images or focusing light regardless of polarization.

If the metalens is going to be used commercially in AR and VR systems, it’s going to need to be scaled ...

Huge amounts of data are needed to train machine-learning models to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, these data are not always easy to come by. Datasets may cost millions of dollars to generate, if usable data exist in the first place, and even the best datasets often contain biases that negatively impact a model’s performance.

To circumvent some of the problems presented by datasets, M...