Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

AI deception is an ugly mirror of the human mind. In teaching machines to think, we're being forced to think more clearly ...

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...

When students joined in virtually, I made sure to affirm their input and invite them to elaborate further,” she recalls.

AI completed its upsized Series E funding round, exceeding the $15 billion targeted round size, and raised $20 billion.

Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...

Here is the AI research roadmap for 2026: how agents that learn, self-correct, and simulate the real world will redefine ...

The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...