It's a simple word that has developed a sinister connotation: algorithm. For many of us, algorithms help determine what we watch, read and listen to — in the process, confirming our tastes and biases, ...

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 ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

ABSTRACT: Rainfall-induced landslides threaten mountainous regions globally, yet existing models face challenges in real-time, large-scale prediction due to dependency on post-event data. This study ...

We present systematic computational analyses to investigate the influence of Matthew’s effect (i.e., “rich gets richer”) in the development, testing, and application of machine learning algorithms for ...

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