Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...

Tension: Marketers expect consistent ad performance, but audiences process the same message with decreasing intensity over ...

A new optical device allows researchers to generate and switch between two stable, donut-shaped light patterns called ...

Brookhaven National Laboratory have developed a novel artificial intelligence (AI)-based method to dramatically tame the ...

Abstract: In automated guided vehicle (AGV) magnetic navigation systems, magnetic markers typically serve solely as spatial references, offering limited informational content. This paper presents a ...

Facial emotion representations expand from sensory cortex to prefrontal regions across development, suggesting that the prefrontal cortex matures with development to enable a full understanding of ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

Intrinsic neural attractors and extrinsic environmental inputs jointly steer the dynamic trajectories of brain activity ...

Self Learners, a self-directed learning platform founded by Diego Vera, unveils an innovative learning methodology designed ...