Security experts have urged people to be cautious with the viral agentic AI tool, known for being highly capable but also wildly unpredictable. Last month, Jason Grad issued a late-night warning to the 20 employees at his tech startup. "You've likely seen Clawdbot trending on X/LinkedIn. While cool, it is currently unvetted and high-risk for our environment, he wrote in a Slack message with a red siren emoji. "Please keep Clawdbot off all company hardware and away from work-linked accounts." Grad isn't the only tech executive who has raised concerns to staff about the experimental agentic AI tool, which was briefly known as MoltBot and is now named OpenClaw. A Meta executive says he recently told his team to keep OpenClaw off their regular work laptops or risk losing their jobs. The executive told reporters he believes the software is unpredictable and could lead to a privacy breach if used in otherwise secure environments. He spoke on the condition of anonymity to speak frankly.

While significant progress has been made in research and development on open-source and cost-efficient large-language models (LLMs), serving scalability remains a critical challenge, particularly for small organizations and individuals seeking to deploy and test their LLM innovations. Inspired by peer-to-peer networks that leverage decentralized overlay nodes to increase throughput and availability, we propose GenTorrent, an LLM serving overlay that harnesses computing resources from decentralized contributors. We identify four key research problems inherent to enabling such a decentralized infrastructure: 1) overlay network organization; 2) LLM communication privacy; 3) overlay forwarding for resource efficiency; and 4) verification of serving quality. This work presents the first systematic study of these fundamental problems in the context of decentralized LLM serving. Evaluation results from a prototype implemented on a set of decentralized nodes demonstrate that GenTorrent achieves a latency reduction of over 50% compared to the baseline design without overlay forwarding. Furthermore, the security features introduce minimal overhead to serving latency and throughput. We believe this work pioneers a new direction for democratizing and scaling future AI serving capabilities.

Ishai et al. (FOCS'06) introduced secure shuffling as an efficient building block for private data aggregation. Recently, the field of differential privacy has revived interest in secure shufflers by highlighting the privacy amplification they can provide in various computations. Although several works argue for the utility of secure shufflers, they often treat them as black boxes; overlooking the practical vulnerabilities and performance trade-offs of existing implementations. This leaves a central question open: what makes a good secure shuffler? This survey addresses that question by identifying, categorizing, and comparing 26 secure protocols that realize the necessary shuffling functionality. To enable a meaningful comparison, we adapt and unify existing security definitions into a consistent set of properties. We also present an overview of privacy-preserving technologies that rely on secure shufflers, offer practical guidelines for selecting appropriate protocols, and outline promising directions for future work.

We would like to thank all the reviewers for their insightful comments. Changes mentioned in our responses below have been incorporated in the revised version of the paper. Regarding the contribution of the paper, our Level-1 theory of mind (section 2.2) was similar to Ref [23] That is not true for the opposite case. POMDP model always generates a deterministic policy. It only changes the likelihood function of the model. Therefore, we don't need any new parameters to measure the accuracy of our model.

"Not affecting me at all, to be honest," a White House aide tells WIRED. WASHINGTON, DC - OCTOBER 20: The facade of the East Wing of the White House is demolished by work crews on October 20, 2025 in Washington, DC. The demolition is part of U.S. President Donald Trump's plan to build a ballroom reportedly costing $250 million on the eastern side of the White House. White House staffers don't appear to care all that much about the ongoing demolition of the East Wing occurring in the middle of the government shutdown . "Not affecting me at all, to be honest," a White House aide tells WIRED.

Sudan's Khartoum targeted by RSF drones for third day after airport reopens The paramilitary Rapid Support Forces (RSF) have targeted Sudan's capital Khartoum and its main airport with drones, a day after the first passenger flight in two years landed in the city amid the civil war. The government-aligned Sudanese Armed Forces (SAF) intercepted the drones on Thursday, which caused no damage, a military official who spoke on condition of anonymity told The Associated Press news agency. The RSF and SAF did not immediately acknowledge the attack. The airport has come under repeated drone attacks blamed on the RSF since Tuesday. Al Jazeera's Hiba Morgan said "both sides seem to be stepping up the use of drones, with the RSF using them here in the capital, Khartoum, to target facilities such as the airport".

If you are going to promise users privacy, then you really need to follow through. Tea Dating Advice, a service that advertised itself as a safe space for women to anonymously share information about former partners--to warn others about abuse and cheating--says that it is locked down. Users are not allowed to take screenshots, and the app says it verifies that its users are women. So why did Tea let me, a middle-aged man, create an account just a few days after suffering two major security breaches? Last month, hackers wormed their way into Tea and accessed sensitive user data; 70,000 user images and more than 1 million private messages reportedly were leaked, including communications about abortions, users' driver's-license photos, and phone numbers that had been shared in private messages.