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 goal of a numerical optimization problem is to find a vector of values that minimizes some cost function. The most fundamental example is minimizing the Sphere Function f(x0, x1, .. xn) = x0^2 + ...

AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottleneck ...

VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...

Algorithms have taken on an almost mythical significance in the modern world. They determine what you see on social media and when browsing online, help form people’s belief systems, and impact the ...

Inspired by a theoretical model of particles moving around on a chessboard, new robot swarm research shows that, as magnetic interactions increase, dispersed 'dumb robots' can abruptly gather in large ...

The world of computing is full of buzzwords: AI, supercomputers, machine learning, the cloud, quantum computing and more. One word in particular is used throughout computing – algorithm. In the most ...