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

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.

Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...

In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

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.

Humans possess a remarkable balance between stability and flexibility, enabling them to quickly establish new plans and ...