Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

The device marks a major step forward in transforming how neuroscientists study the brain. By enabling high-resolution, real-time imaging of brain activity in freely moving mice, the miniaturized ...

Researchers at the University of California, Davis, have created a miniaturized microscope for real-time, high-resolution, ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Google LLC today detailed RigL, an algorithm developed by its researchers that makes artificial intelligence models more hardware-efficient by shrinking them. Neural networks are made up of so-called ...

Early detection of ovarian cancer, the deadliest gynecologic cancer, is crucial for reducing mortality. Current noninvasive risk assessment measures include protein biomarkers in combination with ...

Recently, Anhui Zhongji Star Electronic Technology Co., Ltd. submitted a patent application titled "Dynamic Control Method ...

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

More than two decades ago, neural networks were widely seen as the next generation of computing, one that would finally allow computers to think for themselves. Now, the ideas around the technology, ...