Tech Xplore on MSN

Reinforcement learning accelerates model-free training of optical AI systems

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

Scientists build a ‘periodic table’ for AI models

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

Before AI Can Answer Your Questions, Someone Has to Train It

Scale AI, Surge AI, and the billion-dollar gig-work industry shaping everything from chatbots to self-driving cars ...

True agentic AI is years away - here's why and how we get there

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.

Brain-inspired AI: Human brain separates goals and uncertainty to enable adaptive decision-making

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

AI might not need huge training sets, and that changes everything

For a decade, the story of artificial intelligence has been told in ever larger numbers: more parameters, more GPUs, more ...
Devdiscourse

AI can cut emissions and congestion in urban transport by nearly 50%

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

Artificial Intelligence in Game Development and Reinforcement Learning

The role of artificial intelligence in game development has expanded significantly over the past decade, merging sophisticated reinforcement learning techniques with innovative game design to create ...