Agentic AI challenges the foundational tenets of our legal frameworks, which have historically relied on clear lines of ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Artificial intelligence (AI) is revolutionising the field of drug discovery and disease modelling, with a significant impact ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

AI-driven attacks leaked 23.77 million secrets in 2024, revealing that NIST, ISO, and CIS frameworks lack coverage for ...

Half the planet lies outside any country’s border. In those waters, rules have long been thinner than the myths: freedom to ...

Abstract: This paper develops a Multi-Agent Deep Reinforcement Learning (MADRL) framework for underwater attack-defense scenarios with constrained sensing/communication. While maintaining balanced ...

Researchers from Marshall University and the University of Missouri have developed G2PDeep, an innovative web-based platform ...

The new reinforcement learning system lets large language models challenge and improve themselves using real-world data instead of curated training sets. Meta researchers have unveiled a new ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...