Like humans, artificial intelligence learns by trial and error, but traditionally, it requires humans to set the ball rolling by designing the algorithms and rules that govern the learning process.

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

From Toy Story 5 to Nolan’s The Odyssey, here are 2026’s most anticipated Hollywood movies - a blockbuster lineup we can't ...

Wearables, Mobile Health (m-Health), Real-Time Monitoring Share and Cite: Alqarni, A. (2025) Analysis of Decision Support ...

Last time on Neural Dispatch: Agentic AI’s lack of intelligence, a DeepSeek moment, and Nvidia’s AI supercomputer Adobe ...

Abstract: This study proposes a low-level radio frequency (LLRF) feedback control algorithm based on reinforcement learning (RL) using the soft actor–critic (SAC) and proximal policy optimization (PPO ...

At El Paso’s Bronco Swap Meet, that humble $45 isn’t just spending money—it’s a magic key unlocking a labyrinth of treasures where savvy shoppers transform modest budgets into carloads of discoveries ...

Efficiency once made us indispensable. Now it makes us replaceable. In an age of automation, originality is the only job ...

Sharpen your Mains answer-writing skills with GS-3 questions by following the thought process. Do not miss points to ponder ...

Abstract: In today's networked environment, cyber-attacks pose a significant security threat. Traditional port-hopping defense strategies have several limitations: fixed and highly predictable hopping ...

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...