The US Department of Defense has a lot of congressionally mandated homework to do every year involving hundreds of required reports on various national security topics. But Pentagon officials have been proudly describing a new shortcut—using generative AI tools to write such reports for Congress.

Pentagon Chief Technology Officer Emil Michael highlighted AI-generated reports to Congress as a key example of how the Department of Defense—stylized as the Department of War under the Trump administration—has adopted generative AI during an event hosted by the Hudson Institute think tank in Washington, DC, on June 12. The Pentagon has made AI tools, starting with Google Cloud’s Gemini for Government, widely available to members of all six military branches through the department’s bespoke GenAI.mil platform since December 2025.

“I have to report to Congress every year on this thing,” Michael said. “Let me load all the papers onto it and have it draft me a congressional report that would otherwise take 200 hours of staffing time and do it in five hours.”

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Fully autonomous drones killed Russian soldiers during a battlefield test two years ago, according to a Ukrainian drone manufacturer. If true, the incident would represent another milestone in a war that has spurred unprecedented developments in military drones, robots, and AI-guided weaponry.

The one-time test was revealed by Alexander Kokhanovskyy, CEO of the Ukrainian drone maker Aero Center, during an interview with New Scientist at a press event hosted by the Ukrainian embassy in London. Kokhanovskyy described the test—which did not involve his current company Aero Center—using quadcopter drones that were preprogrammed to fly to a front-line area before activating an AI-powered “Terminator mode” that would seek out and attack any target in the given area.

There was apparently no video feed or anything else to show what the “Terminator” drones targeted and attacked. But Kokhanovskyy told New Scientist that human-piloted drones sent to check out the aftermath found “a couple” of dead Russian soldiers, which led to the conclusion that the fully autonomous drones had killed them.

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A decade after the global craze for Pokémon Go peaked, an AI company has been using billions of real-world images captured by millions of players to develop navigation technologies for delivery robots and possibly military drones. That represents an intriguing but potentially discomfiting legacy for an augmented reality mobile game that has incentivized gamers to capture short smartphone videos of physical neighborhoods and landmarks.

The AI company, Niantic Spatial, was spun out of Pokémon Go game developer Niantic in May 2025, after Niantic separately sold its licensed games such as Pokémon Go to the Saudi-backed video game publisher Scopely. But before that deal, Niantic publicly announced plans to use scans from millions of Pokémon Go players along with data captured by users of the company’s Scaniverse app to train and develop a “large geospatial model”—a 3D model of the physical world trained on the geolocated images provided by app users scanning real-world locations.

“Ground scans were one component to help train Niantic Spatial's real-world foundation models —AI systems that learn to recognize and interpret physical spaces,” a Niantic Spatial spokesperson told Ars. “The models are the product of that training, not a copy of or a means of accessing the underlying scans, which were of public points of interest such as statues and fountains.”

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A US Army helicopter gunship was apparently struck by an Iranian Shahed drone before going down near the Strait of Hormuz—but it's unclear whether the one-way attack drone was deliberately aimed or achieved more of a lucky accidental strike.

Axios correspondent Barak Ravid first reported an unnamed US government official’s comments that an Iranian drone had hit the US Army AH-64 Apache helicopter before the latter went down on June 8. The New York Times later confirmed that reporting through more anonymous US officials, including one official who said US military investigators were still evaluating whether the Iranian drone strike on the helicopter was intentional or accidental.

Iran has fired thousands of such Shahed drones against a wide range of military and civilian targets in the Gulf region since February 28, 2026, when the United States and Israel began the war by jointly attacking Iran with a barrage of bombs and missiles. But Shahed drones have mainly struck stationary targets such as Amazon data centers and energy facilities, sometimes hitting slow-moving commercial ships in the Strait of Hormuz.

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A drone boat picked up two US Army pilots from waters near the Strait of Hormuz after their helicopter gunship went down, US military officials said. The incident apparently represents the first time the US military has used a drone for such a rescue mission at sea.

The two crew members from the US Army AH-64 Apache were “rescued by American forces” at 7:33 pm US Eastern Time after their helicopter went down off the coast of Oman on June 8, according to a US Central Command press release. That press release mentioned support from US Navy units including the US 5th Fleet’s Task Force 59, which is charged with integrating uncrewed aerial, surface, and underwater vehicles, alongside AI, into 5th Fleet maritime operations.

Anonymous US military officials initially told CBS News that the Apache air crew was rescued by an uncrewed surface drone operated by Task Force 59 from the US Fifth Fleet in Bahrain. The officials also described the incident as the first time the military had used a drone to rescue people from the water.

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Russian satellites have been identified as the cause of mysterious, seconds-long bursts of GPS interference across Europe—a rare example of human-made GPS interference coming from space. But uncertainty still hangs over whether such interference is intentional and if it could be more powerfully weaponized as GPS jamming with continental reach in the future.

The discovery came from an investigation detailed in a June 2 preprint paper by Todd Humphreys and his student Zach Clements at The University of Texas at Austin, along with Argyris Kriezis at Stanford University in California. By sifting through public data from ground-based stations with global navigation satellite system (GNSS) receivers, they identified a pattern of high-powered interference lasting less than 10 seconds each time but simultaneously detectable by ground stations across Europe from Norway to Spain to Poland, and even reaching as far west as Greenland and Canada.

By analyzing the ground station data from January 2019 to April 2026, the researchers found 75 days with at least one widespread GNSS interference event overlapping with the GPS L1 frequency band centered on 1575.42 megahertz. That represents the main band used for signal transmission by the US-made GPS satellite constellation and GNSS constellations from other countries.

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SpaceX has requested unusually swift entry into several leading stock market indexes as a condition of its historic stock market debut. But the S&P 500 stock market index representing many of the largest profitable US companies has surprised market analysts by refusing to bend the rules for Elon Musk’s space and AI company.

The June 4 decision by S&P Dow Jones Indices—the company that creates and manages stock market indexes such as the S&P 500—means that SpaceX will not gain accelerated access to potentially billions more dollars through passive investment funds that automatically purchase shares of S&P 500 companies. Modifying the rules in response to SpaceX's request could have also allowed leading AI companies such as OpenAI and Anthropic to gain entry not long after their own expected initial public offerings (IPOs). That possibility has now been shuttered.

The news will likely come as a relief to people concerned about passive investor money and people’s retirement savings plans having greater exposure to the market risks associated with SpaceX’s big bet on AI and speculative orbital data center plans. AI companies are generally facing more challenges in funding and building expensive AI data centers, even as they shift more of the subsidized costs of running AI services onto shocked customers through usage-based pricing.

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It may appear that humanoid robots capable of handling any task have almost arrived—especially when tech companies showcase them performing acrobatic feats or handling household chores. But there is still a significant gap between these robot demonstrations and proving that the same robots can reliably and repeatedly manage such tasks in the real world.

The latest wave of robot videos can be particularly tricky, given the human tendency to anthropomorphize objects with a humanoid figure. A robot arm doing a dance move may simply seem “cool,” but a humanoid robot doing the same dance move can trigger more misleading assumptions, said Jonathan Hurst, cofounder of Agility Robotics and a robotics researcher at Oregon State University.

“People automatically extrapolate and assume that the robot that looks like a person can do all the things that a person who can dance could do—which is not true,” Hurst told Ars. “But a lot of the startup companies do kind of prey on that for being able to raise a lot of money.”

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