The ceasefire highlights shifting geopolitical alliances and may stabilize regional tensions, impacting future diplomatic strategies. The post Iran declares US-Israel defeat after ceasefire brokered by Pakistan, China appeared first on Crypto Briefing.

The intensified SERE training underscores the likelihood of prolonged military engagement, with significant geopolitical and market implications. The post US forces intensify SERE training amid heightened Iran conflict risks appeared first on Crypto Briefing.

Australia passed legislation on April 1, bringing digital asset and tokenized custody platforms under its financial services licensing regime.

The planned talks could stabilize regional tensions, but Iran's demands and military losses may complicate achieving a lasting peace agreement. The post Iran plans US talks in Islamabad, claims war objectives mostly achieved appeared first on Crypto Briefing.

Iran's sustained influence amid military setbacks complicates geopolitical stability, challenging ceasefire prospects and market predictions. The post Iran maintains regional influence despite military setbacks, complicating ceasefire appeared first on Crypto Briefing.

The missile launch underscores escalating tensions, reinforcing the likelihood of U.S. military involvement in Iran, impacting regional stability. The post Islamic Resistance in Iraq targets US bases with Al-Arqab missile launch appeared first on Crypto Briefing.

Congressional approval demand highlights potential checks on executive military power, impacting U.S. foreign policy and market stability. The post Republicans urge Trump to seek Congress approval for Iran military actions appeared first on Crypto Briefing.

AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities, Anthropic said.

Trump's statement significantly alters geopolitical dynamics, increasing market confidence in a sustained US-Iran ceasefire, yet risks remain. The post Trump’s Iran uranium statement boosts ceasefire prospects appeared first on Crypto Briefing.

arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researchers added irrelevant context to mathematical problems, LLM performance degraded by 65% Apple Machine Learning Research, exposing brittle pattern-matching beneath apparent reasoning. This epistemic gap, the inability to ground claims in traceable evidence, limits AI reliability in domains requiring

arXiv:2604.05142v1 Announce Type: new Abstract: As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, in which the traits of AI systems are shaped by the success of earlier AIs in designing and propagating their descendants. There is a rich mathematical theory modeling how behavioral traits are shaped by biological evolution, but AI evolution will be radically different: biological DNA mutations are random and approx

arXiv:2604.05229v1 Announce Type: new Abstract: Agentic AI systems plan, use tools, maintain state, and produce multi-step trajectories with external effects. Those properties create a governance problem that differs materially from single-turn generative AI: important risks emerge dur- ing execution, not only at model development or deployment time. Governance standards such as ISO/IEC 42001, ISO/IEC 23894, ISO/IEC 42005, ISO/IEC 5338, ISO/IEC 38507, and the NIST AI Risk Management Framework a

arXiv:2604.05826v1 Announce Type: new Abstract: Policy makers, scientists, and the public are increasingly confronted with thorny questions about the regulation of artificial intelligence (AI) systems. A key common thread concerns whether AI can be trusted and the factors that can make it more trustworthy in front of stakeholders and users. This is indeed crucial, as the trustworthiness of AI systems is fundamental for both democratic governance and for the development and deployment of AI. Thi

arXiv:2604.05854v1 Announce Type: new Abstract: We present \textbf{Deep Researcher Agent}, an open-source framework that enables large language model (LLM) agents to autonomously conduct deep learning experiments around the clock. Unlike existing AI research assistants that focus on paper writing or code generation, our system addresses the full experiment lifecycle: hypothesis formation, code implementation, training execution, result analysis, and iterative refinement. The framework introduce