Iran's supply of drones to Russia for its war effort in Ukraine appears to have escalated in recent months after a study released this week found Tehran has modified its drones to employ maximum damage. A January report by Conflict Armament Research (CAR) released publicly Thursday broke down why the affordably made Iranian Shahed-131 single-use drones have been employed to significant effect in Ukraine. Russia has relied on Iranian-supplied unmanned areial vehicles (UAV) in Ukraine for months to help assist with its diminishing missile stockpiles as the war continues into its 11th month, according to the Pentagon. Multipurpose warhead from a Shahed-131 UAV found in research by Conflict Armament Research on Thursday. Iranian drones have been used to hit civilian structures and target Ukraine's critical infrastructure as Russia looks to bombard the war-torn nation in near-daily strikes.

The US Pentagon is planning a new'weapon of mass destruction' that involves thousands of drones that strike by air, land and water to destroy enemy defenses - but experts fear humans could lose control of the'swarms.' The top-secret project, dubbed AMASS (Autonomous Multi-Domain Adaptive Swarms-of-Swarms), would represent automated warfare on an unprecedented scale. AMASS is still in the planning stages, but DARPA (Defense Advanced Research Project Agency) has been collecting bids from suppliers for the $78 million contract. Small drones would be equipped with weapons and tools for navigation and communication, along with abilities ranging from radar jamming to launching lethal attacks. While the technology would change how the US goes to war, experts in the industry raise concerns.

Every year, an army of hackers takes aim at the tax code. The tax code is not computer code, but it is a series of rules--supposedly deterministic algorithms--that take data about your income and determine the amount of money you owe. This code has vulnerabilities, more commonly known as loopholes. It has exploits; those are tax avoidance strategies. There is an entire industry of black-hat hackers who exploit vulnerabilities in the tax code: We call them accountants and tax attorneys.

The article appeared on the DoD's Defense Visual Information Distribution Service (DVIDS), an internet repository of news and images generated by the American military. It was about the launch of Task Force 39, which according to ChatGPT, is "an empowered, collaborative group of soldiers dedicated to fostering an innovative culture and pursuing regional and industry partnerships in order to generate future combat efficiency. The team is focused on countering the threat of small Unmanned Aerial Systems and developing innovative solutions to other security challenges."

Crew members aboard China's orbiting space station completed their first spacewalk as part of their six-month mission. The seven-hour extra-vehicular activity was completed at 12:16 a.m. Fei Junlong and Zhang Lu, who are members of the Shenzhou-15 mission, completed several tasks like installing extension pumps outside the Mengtian laboratory module during the spacewalk while fellow crew member Deng Qingming supported them from inside the Tiangong space station, according to AP News. Fei and Zhang safely returned to the Wentian lab module following the extravehicular activity, according to China.org.cn. The three crew members are expected to make several such spacewalks while aboard the Tiangong station, which is the second permanently inhabited space outpost after Nasa's International Space Station.

The artificial intelligence application ChatGPT has already been banned in some state schools over concerns it could help students cheat, but some Australian MPs had no such qualms when they delivered speeches partially written by the tool in parliament this week. ChatGPT has a reputation for saying a lot without saying much at all, so perhaps it's ideally suited to the job of parliamentary speechwriter – or maybe it's smarter than we give it credit for. To find out, we searched Hansard for parliamentary speeches made by Australian MPs in 2020 and asked ChatGPT to opine on the same subjects – ranging from the role the arts play in society to the government's obligation to provide good dental care. See if you can tell them apart.

From 2001: A Space Odyssey and Ex Machina to Wall-E and Her, artificial intelligence has reliably been a subject of fascination in modern culture. But AI is no longer a thing of imagination, books or film scripts – it is already playing a pivotal role in both our professional and personal lives. And when it comes to the capability of this next-generation technology, we are now on the precipice of an exponential leap. The potential impact of AI on our lives cannot be understated, so the growing AI skills gap must be addressed if we are to ensure that businesses are prepared to take this jump. AI has already transformed the way we interact with banks, how we shop and how we manufacture.

The ChatGPT AI chatbot has created plenty of excitement in the short time it has been available and now it seems it has been enlisted by some in attempts to help generate malicious code. AI writing tools can help lighten your workload by writing emails and essays and even doing math. They use artificial intelligence to generate text or answer queries based on user input. ChatGPT is one popular example, but there are other noteworthy AI writers. ChatGPT is an AI-driven natural language processing tool which interacts with users in a human-like, conversational way. Among other things, it can be used to help with tasks like composing emails, essays and code.

This article presents a novel telepresence system for advancing aerial manipulation in dynamic and unstructured environments. The proposed system not only features a haptic device, but also a virtual reality (VR) interface that provides real-time 3D displays of the robot's workspace as well as a haptic guidance to its remotely located operator. To realize this, multiple sensors namely a LiDAR, cameras and IMUs are utilized. For processing of the acquired sensory data, pose estimation pipelines are devised for industrial objects of both known and unknown geometries. We further propose an active learning pipeline in order to increase the sample efficiency of a pipeline component that relies on Deep Neural Networks (DNNs) based object detection. All these algorithms jointly address various challenges encountered during the execution of perception tasks in industrial scenarios. In the experiments, exhaustive ablation studies are provided to validate the proposed pipelines. Methodologically, these results commonly suggest how an awareness of the algorithms' own failures and uncertainty (`introspection') can be used tackle the encountered problems. Moreover, outdoor experiments are conducted to evaluate the effectiveness of the overall system in enhancing aerial manipulation capabilities. In particular, with flight campaigns over days and nights, from spring to winter, and with different users and locations, we demonstrate over 70 robust executions of pick-and-place, force application and peg-in-hole tasks with the DLR cable-Suspended Aerial Manipulator (SAM). As a result, we show the viability of the proposed system in future industrial applications.

Summarizing text-rich documents has been long studied in the literature, but most of the existing efforts have been made to summarize a static and predefined multi-document set. With the rapid development of online platforms for generating and distributing text-rich documents, there arises an urgent need for continuously summarizing dynamically evolving multi-document sets where the composition of documents and sets is changing over time. This is especially challenging as the summarization should be not only effective in incorporating relevant, novel, and distinctive information from each concurrent multi-document set, but also efficient in serving online applications. In this work, we propose a new summarization problem, Evolving Multi-Document sets stream Summarization (EMDS), and introduce a novel unsupervised algorithm PDSum with the idea of prototype-driven continuous summarization. PDSum builds a lightweight prototype of each multi-document set and exploits it to adapt to new documents while preserving accumulated knowledge from previous documents. To update new summaries, the most representative sentences for each multi-document set are extracted by measuring their similarities to the prototypes. A thorough evaluation with real multi-document sets streams demonstrates that PDSum outperforms state-of-the-art unsupervised multi-document summarization algorithms in EMDS in terms of relevance, novelty, and distinctiveness and is also robust to various evaluation settings.