China's mediation could pivot the crisis towards diplomacy, potentially reducing military tensions and influencing global geopolitical dynamics. The post China offers to mediate hormuz crisis, impacting ceasefire odds appeared first on Crypto Briefing.

The attack exacerbates tensions, reducing ceasefire prospects and increasing the likelihood of U.S. military escalation in the region. The post Iran attacks U.S. base in jordan amid escalating conflict appeared first on Crypto Briefing.

The treasury management system, built on Ripple's 2025 acquisition of GTreasury, lets CFOs view and manage digital assets alongside fiat in a single dashboard without separate custody or wallet infrastructure.

The impasse heightens geopolitical uncertainty, affecting market confidence and suggesting prolonged instability without diplomatic progress. The post Iran demands sanctions relief, US force removal before talks appeared first on Crypto Briefing.

The legislation “embraces innovation, protects participants, and empowers internet-native communities to compete with big tech incumbents,” said a16z’s Miles Jennings.

Trump's stance heightens geopolitical tensions, impacting market stability and increasing the likelihood of military engagement with Iran. The post Trump pushes war with Iran, drops ceasefire odds appeared first on Crypto Briefing.

MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

arXiv:2604.00555v1 Announce Type: new Abstract: Enterprise adoption of Large Language Models (LLMs) is constrained by hallucination, domain drift, and the inability to enforce regulatory compliance at the reasoning level. We present a neurosymbolic architecture implemented within the Foundation AgenticOS (FAOS) platform that addresses these limitations through ontology-constrained neural reasoning. Our approach introduces a three-layer ontological framework--Role, Domain, and Interaction ontolo

arXiv:2604.00007v1 Announce Type: cross Abstract: We present Dynin-Omni, the first masked-diffusion-based omnimodal foundation model that unifies text, image, and speech understanding and generation, together with video understanding, within a single architecture. Unlike autoregressive unified models that serialize heterogeneous modalities, or compositional unified models that require orchestration with external modality-specific decoders, Dynin-Omni natively formulates omnimodal modeling as ma

arXiv:2604.00011v1 Announce Type: cross Abstract: The growing prominence of large language models (LLMs) in daily life has heightened concerns that LLMs exhibit many of the same gender-related biases as their creators. In the context of hiring decisions, we quantify the degree to which LLMs perpetuate societal biases and investigate prompt engineering as a bias mitigation technique. Our findings suggest that for a given resum\'e, an LLM is more likely to hire a female candidate and perceive the

arXiv:2604.00025v1 Announce Type: cross Abstract: Standard evaluation protocols reveal a counterintuitive phenomenon: on 7.7% of benchmark problems spanning five datasets, larger language models underperform smaller ones by 28.4 percentage points despite 10-100x more parameters. Through systematic evaluation of 31 models (0.5B-405B parameters) across 1,485 problems, we identify the mechanism as spontaneous scale-dependent verbosity that introduces errors through overelaboration. Causal interven

arXiv:2604.00081v1 Announce Type: cross Abstract: The accelerating displacement of human labor by artificial intelligence (AI) and robotic systems represents a structural transformation whose societal consequences extend far beyond conventional labor market analysis. This paper presents a systematic multi-domain examination of the likely effects on economic structure, psychological well-being, political stability, education, healthcare, and geopolitical order. We identify a critical and underex

arXiv:2604.00186v1 Announce Type: cross Abstract: This paper extends the Acemoglu-Restrepo task exposure framework to address the labor market effects of agentic artificial intelligence systems: autonomous AI agents capable of completing entire occupational workflows rather than discrete tasks. Unlike prior automation technologies that substitute for individual subtasks, agentic AI systems execute end-to-end workflows involving multi-step reasoning, tool invocation, and autonomous decision-maki

arXiv:2604.00189v1 Announce Type: cross Abstract: To support practitioners in understanding how agentic systems are designed in real-world industrial practice, we present a review of practitioner conference talks on AI agents. We analyzed 138 recorded talks to examine how companies adopt agent-based architectures (Objective 1), identify recurring architectural strategies and patterns (Objective 2), and analyze application domains and technologies used to implement and operate LLM-driven agentic

arXiv:2604.00324v1 Announce Type: cross Abstract: Autonomous AI agents are being deployed with filesystem access, email control, and multi-step planning. This thesis contributes to four open problems in AI safety: understanding dangerous internal computations, removing dangerous behaviors once embedded, testing for vulnerabilities before deployment, and predicting when models will act against deployers. ACDC automates circuit discovery in transformers, recovering all five component types from