From analog hobbies to tech curfews, these Gen Zers are experimenting with science-backed ways to help their brains feel a little less foggy. Doomscrolling has taken over our screen time, and ...

American veteran and adventure guide Joe Fleming reflects on wrestling with mental health, the men’s movement he created, and the wild South African landscapes that helped save his life. Aspen is a ...

Last month, my husband, our 6-year-old daughter, and I flew from Nashville to San Francisco for our yearly visit with my brother and his family. Every time, my nervous system exhales amid the city’s ...

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 ...

Ben Dowson has spent his life in motion — climbing, skiing, gymnastics — and testing the limits of what the human body can do. Along the way, he sustained injuries that led him down a path of ...

Your browser does not support the audio element. The backpropagation algorithm is the cornerstone of modern artificial intelligence. Its significance goes far beyond ...

MEXICO CITY (AP) — More than 14,000 mainly Venezuelan migrants who hoped to reach the United States have reversed course and turned south since U.S. President Donald Trump’s immigration crackdown ...

Jake Peterson is Lifehacker’s Tech Editor, and has been covering tech news and how-tos for nearly a decade. His team covers all things technology, including AI, smartphones, computers, game consoles, ...

YouTube is updating monetization policies to target inauthentic content. This change will impact channels publishing mass-produced and repetitious videos. Violations could result in removal from the ...

ABSTRACT: This paper proposes a unique approach to load forecasting using a fast convergent artificial neural network (ANN) and is driven by the critical need for power system planning. The Mazoon ...

Abstract: Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these ...

Abstract: This study proposes theories and applications of probabilistic divergences to neural network training. This theory generalizes the cross-entropy method for backpropagation to the ...