A US-China AI Hotline Won't Be Ready for a While As the US and China race to become the dominant power in the AI industry, the countries also appear to be figuring out ways to communicate on national security issues. As US president Donald Trump and Chinese president Xi Jinping prepare to meet in Washington for a state dinner at the White House on Thursday, AI has become a top priority . Tech executives from OpenAI and Nvidia have confirmed their attendance at the dinner, as a number of key agenda items are on the table. Chief among them is a US proposal to establish an AI notification system with China, akin to the Cold War hotline with Moscow, which would allow each country to alert the other about national security issues related to AI. Treasury secretary Scott Bessent first announced the notification system on Sunday with Chinese vice premier He Lifeng. But for all the high-level progress, Trump administration officials tell they expect it to still take a number of weeks to finalize an agreement, even if they are optimistic that the hotline could be in place before the year's end.

What's the US-China AI'hotline' that Trump plans to pitch to Xi Jinping? Share What's the US-China AI'hotline' that Trump plans to pitch to Xi Jinping? on social media The United States wants a new "notification mechanism" with China to warn each other when an artificial intelligence incident becomes serious enough to threaten national security. The proposal, effectively an "AI hotline", was discussed on Sunday during talks in New York between US Treasury Secretary Scott Bessent and Chinese Vice Premier He Lifeng, ahead of a summit between US President Donald Trump and Chinese President Xi Jinping in Washington this week. The initiative comes amid an intensifying contest for AI supremacy between the world's top two economies, together with increasing warnings from tech giants that guardrails are necessary around the ever-growing technology. So, what do we know about this so-called hotline, and where is the AI battle between the US and China headed?

As Electric Vehicle (EV) adoption accelerates in urban environments, optimizing charging infrastructure is vital for balancing user satisfaction, energy efficiency, and financial viability. This study advances beyond static models by proposing a digital twin framework that integrates agent-based decision support with embedded optimization to dynamically simulate EV charging behaviors, infrastructure layouts, and policy responses across scenarios. Applied to a localized urban site (a university campus) in Hanoi, Vietnam, the model evaluates operational policies, EV station configurations, and renewable energy sources. The interactive dashboard enables seasonal analysis, revealing a 20% drop in solar efficiency from October to March, with wind power contributing under 5% of demand, highlighting the need for adaptive energy management. Simulations show that real-time notifications of newly available charging slots improve user satisfaction, while gasoline bans and idle fees enhance slot turnover with minimal added complexity. Embedded metaheuristic optimization identifies near-optimal mixes of fast (30kW) and standard (11kW) solar-powered chargers, balancing energy performance, profitability, and demand with high computational efficiency. This digital twin provides a flexible, computation-driven platform for EV infrastructure planning, with a transferable, modular design that enables seamless scaling from localized to city-wide urban contexts.

A nonprofit parents coalition is calling on multiple congressional committees to launch an investigation into Meta for prioritizing engagement metrics that put children's safety at risk. The call is part of a three-pronged attack campaign by the American Parents Coalition (APC), launched Thursday. It includes a letter to lawmakers with calls for investigations, a new parental notification system to help parents stay informed on issues impacting their kids at Meta and beyond, and mobile billboards at Meta D.C. and California headquarters, calling out the company for failure to adequately prioritize protecting children. APC's campaign follows an April Wall Street Journal report that included an investigation looking into how the company's metrics focus has led to potential harms for children. "This is not the first time Meta has been caught making tech available to kids that exposes them to inappropriate content," APC Executive Director Alleigh Marre said. "Parents across America should be extremely wary of their children's online activity, especially when it involves emerging technology like AI digital companions.

An automated approach to identifying offenders in Sri Lanka would be better than the current system. Obtaining information from eyewitnesses is one of the less reliable approaches and procedures still in use today. Automated criminal identification has the ability to save lives, notwithstanding Sri Lankan culture's lack of awareness of the issue. Using cutting-edge technology like biometrics to finish this task would be the most accurate strategy. The most notable outcomes will be obtained by applying fingerprint and face recognition as biometric techniques. The main responsibilities will be image optimization and criminality. CCTV footage may be used to identify a person's fingerprint, identify a person's face, and identify crimes involving weapons. Additionally, we unveil a notification system and condense the police report to Additionally, to make it simpler for police officers to understand the essential points of the crime, we develop a notification system and condense the police report. Additionally, if an incident involving a weapon is detected, an automated notice of the crime with all the relevant facts is sent to the closest police station. The summarization of the police report is what makes this the most original. In order to improve the efficacy of the overall image, the system will quickly and precisely identify the full crime scene, identify, and recognize the suspects using their faces and fingerprints, and detect firearms. This study provides a novel approach for crime prediction based on real-world data, and criminality incorporation. A crime or occurrence should be reported to the appropriate agencies, and the suggested web application should be improved further to offer a workable channel of communication.

In this paper, Mobile notification systems play a major role in a variety of applications we focus our discussion on a near-real-time notification system, to communicate, send alerts and reminders to the users to which can process both near-real-time and offline notifications and inform them about news, events or messages. In this paper, we formulate make decisions in a stream fashion in near-real-time. An example of the near-real-time notification decision problem as a Markov such a distributed near-real-time notification system can be found Decision Process where we optimize for multiple objectives in the in [7]. Note that a near-real-time notification system can process rewards. We propose an end-to-end offline reinforcement learning offline notifications and spread them out over time, for example framework to optimize sequential notification decisions. We using a notification spacing queuing system introduced in [35]. On address the challenge of offline learning using a Double Deep Q-the other hand, a system designed solely for offline notifications network method based on Conservative Q-learning that mitigates may not be able to process near-real-time notifications. the distributional shift problem and Q-value overestimation. We There are a few characteristics of the notification system that illustrate our fully-deployed system and demonstrate the performance make them suitable applications for reinforcement learning (RL).