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.

Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

The paper addresses the AI shutdown problem, a long-standing challenge in AI safety. The shutdown problem asks how to design AI systems that will shut down when instructed, will not try to prevent ...

Duke University engineers are using artificial intelligence to do something scientists have chased for centuries; turn messy, ...

From structure confirmation to methodology improvements, making complex natural products has driven innovation in organic ...

How My Winter Car Builds on a Cult Classic To understand why this sequel matters, you have to go back to My Summer Car, the ...

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

A team of researchers at Penn State have devised a new, streamlined approach to designing metasurfaces, a class of engineered ...

Annals of Mathematics, a distinguished journal of research papers in pure mathematics, was founded in 1884. Annals of Mathematics is published bimonthly with the cooperation of Princeton University ...

Researchers identified a major decline in neural activity and retention when students used AI for writing. We need to empower ...

A new technical paper titled “Making Strong Error-Correcting Codes Work Effectively for HBM in AI Inference” was published by researchers at Rensselaer Polytechnic Institute, ScaleFlux and IBM T.J.