Science

New research reveals the fundamental role of stochastic processes in subdiffraction laser writing, impacting the scalability of integrated quantum photonics.

Researchers have developed a novel quantization method that dramatically reduces model size with minimal loss of accuracy, pushing the boundaries of efficient large language model deployment.

As more complex tasks are delegated to groups of AI agents, understanding how errors spread and amplify within these systems becomes critical.

New research reveals that popular evaluations of artificial intelligence safety have limited academic impact, raising questions about how we measure progress in this crucial field.

New research pushes the boundaries of computable structure theory, demonstrating conditions for constructing computable models of theories extending Peano Arithmetic.

A new benchmark assesses the ability of artificial intelligence agents to identify, fix, and exploit vulnerabilities within smart contracts.

Researchers have successfully employed machine learning to predict the entanglement properties of complex, disordered quantum systems, offering a new path to understanding their behavior.

A new system allows multiple AI agents to maintain context and respond faster by storing key information directly on device, rather than relying solely on short-term prompts.

This review explores how restricting the tools of propositional and modal logic impacts what we can express, and how easily we can reason with those limited systems.

Researchers are leveraging the power of quantum computers and spin chain models to explore the behavior of confining strings in quantum chromodynamics at extremely strong coupling.