A military drone may have autonomously attacked humans for the first time without being instructed to do so, according to a recent report by the UN Security Council. The report, published in March, claimed that the AI drone – Kargu-2 quadcopter – produced by Turkish military tech company STM, attacked retreating soldiers loyal to Libyan General Khalifa Haftar. The 548-page report by the UN Security Council's Panel of Experts on Libya has not delved into details on if there were any deaths due to the incident, but it raises questions on whether global efforts to ban killer autonomous robots before they are built may be futile. Over the course of the year, the UN-recognized Government of National Accord pushed the Haftar Affiliated Forces (HAF) back from the Libyan capital Tripoli, and the drone may have been operational since January 2020, the experts noted. "Logistics convoys and retreating HAF were subsequently hunted down and remotely engaged by the unmanned combat aerial vehicles or the lethal autonomous weapons systems such as the STM Kargu-2," the UN report noted.

NASA's Curiosity rover has been able to register something which, while unremarkable on Earth, is an interesting phenomenon for Mars -- cloudy skies. The agency has shared images of "shining" clouds, able to form on a planet that has a relatively thin atmosphere. Nothing has been confirmed just yet, but they could be naturally formed dry-ice clouds, made of carbon dioxide. It might not match the appeal of ancient megafloods or possible signs of life, but Curiosity continues to offer up new Mars insights, both above and below the surface of the red planet. A little closer to home, Japan's Aerospace Exploration Agency (JAXA) has teamed up with Sony, Doshisha University and toy-maker Tomy on a ball-shaped transforming robot destined for the Moon.

Paris, May 27, 2021 – Atos and Thales announce the creation of Athea, a joint venture that will develop a sovereign big data and artificial intelligence platform for public and private sector players in the defence, intelligence and internal state security communities. Athea will draw on the experience gained by both companies from the demonstration phase of the ARTEMIS programme, the big data platform of the French Ministry of Armed Forces. The contract to optimise and prepare the full-scale roll-out of the ARTEMIS platform was also awarded jointly to the two leaders by the French Defense Procurement Agency on April 30, 2021. The new joint venture will initially serve the French market before addressing European requirements at a later date. With the exponential rise in the number of sources of information, and increased pressure to respond more quickly to potential issues, State agencies need to manage ever-greater volumes of heterogeneous data and accelerate the development of new AI applications where security and sovereignty are key.

Long-time blockchain has been looked at as an isolated technology. Recently however we see a growing trend of blockchain being integrated with other technologies such as Big Data, Artificial Intelligence amongst others. An interesting development that can be observed is the growing attention of corporates to use blockchain for IoT or Internet of Things applications. And that is not strange. The IoT market is increasing drastically and this is expected to continue in an accelerated way triggered by the recent uptake of the 5G network. But with this there arise a number of big challenges that may limit its future growth.

A "lethal" weaponized drone "hunted down" and "remotely engaged" human targets without its handlers' say-so during a conflict in Libya last year, according to a United Nations report first covered by New Scientist this week. Whether there were any casualties remains unclear, but if confirmed, it would likely be the first recorded death carried out by an autonomous killer robot. In March 2020, a Kargu-2 attack quadcopter, which the agency called a "lethal autonomous weapon system," targeted retreating soldiers and convoys led by Libyan National Army's Khalifa Haftar during a civil conflict with Libyan government forces. "The lethal autonomous weapons systems were programmed to attack targets without requiring data connectivity between the operator and the munition: in effect, a true'fire, forget and find' capability," the UN Security Council's Panel of Experts on Libya wrote in the report. It remains unconfirmed whether any soldiers were killed in the attack, although the UN experts imply as much.

This article is part of "The age of surveillance," a special report on artificial intelligence. Lawmakers are still figuring out how best to use artificial intelligence. Lawbreakers are doing the same. The malicious use of artificial intelligence is growing. Officials are warning against attacks that use deepfake technology, AI-enhanced "phishing" campaigns and software that guesses passwords based on big data analysis.

U.S. Northern Command hosted a global information dominance exercise and the results point to the tremendous advantages the Defense Department would receive by applying machine learning and artificial intelligence to all-domain information, Air Force Gen. Glen D. VanHerck said yesterday. All 11 combatant commands participated in the exercise, which was based on a global scenario involving two peer competitors. "What we were looking to do is show the incredible value of information and how information can be used today," he said. This is especially true if commanders can take information from all domains -- undersea, space, cyberspace, air, land, sea and share it through machine-learning artificial intelligence, he said. This would serve to make data and information available in a timely manner to produce space for decision makers.

The Royal Navy is using artificial intelligence for the first time at sea in a bid to defeat missile attacks. Leading-edge software is being tested at sea against live missiles during the largest exercise of its type off the coasts of Scotland and Norway. Involving more than 3,000 military personnel, Formidable Shield tests the ability of NATO warships to detect, track and defeat incoming missiles, from sea-skimming weapons travelling at twice the speed of sound just above the waterline, to ballistic missiles. Three Royal Navy warships are taking part in the exercise, which runs until early June: destroyer HMS Dragon and two frigates, Lancaster and Argyll. HMS Lancaster and Dragon are trialing artificial intelligence and machine learning applications which offer a glimpse of the future of air defence at sea.

The federal government should establish an AI Safety Commissioner and halt the use of facial recognition and algorithms in important decision-making until adequate protections are in place, the Australian Human Rights Commission has concluded after a three-year investigation. The Australian Human Rights Commission's (AHRC) report on Human Rights and Technology was tabled in Parliament on Thursday afternoon, with 38 recommendations to the government on ensuring human rights are upheld in the laws, policies, funding and education on artificial intelligence. Human Rights Commissioner Ed Santow has urged local, state, territory and federal governments to put on hold the use of facial recognition and AI in decision-making that has a significant impact on individuals. This moratorium should be until adequate legislation is in place that regulates the use of these technologies and ensures human rights are protected. The use of automation and algorithms in government decision-making should also be paused until a range of protections and transparency measures are in place, Mr Santow said in the report.

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or QUBO (quadratic unconstrained binary optimization) form. Although such solutions are typically of very high quality, problem instances are usually not solved to optimality due to imperfections of the current generations quantum annealers. In this contribution, we aim to understand some of the factors contributing to the hardness of a problem instance, and to use machine learning models to predict the accuracy of the D-Wave 2000Q annealer for solving specific problems. We focus on the Maximum Clique problem, a classic NP-hard problem with important applications in network analysis, bioinformatics, and computational chemistry. By training a machine learning classification model on basic problem characteristics such as the number of edges in the graph, or annealing parameters such as D-Wave's chain strength, we are able to rank certain features in the order of their contribution to the solution hardness, and present a simple decision tree which allows to predict whether a problem will be solvable to optimality with the D-Wave 2000Q. We extend these results by training a machine learning regression model that predicts the clique size found by D-Wave.