Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Look Up Say More Mashable Selects Mashable Voices Safety Net Creator Hub Versus Gift Ideas For Everyone On Your List Switch Off Trending Now In My Bag All Series Deliberately destroying rare books might be the final straw in the eyes of the Federal Trade Commission. Earlier this month, we reported on the disturbing trend of AI companies using physical copies of books to train their agentic AI, in a practice so eerily reminiscent of book burning that it's spooking even devotees of artificial intelligence . Well, according to Axios, the FTC is now being urged to investigate the practice, not, as we might like, for crimes against humanity, but for violations of antitrust law, since every book destroyed is one less book available for competing AI agents to use. SEE ALSO: AI companies keep destroying old books. Axios reports that [m]ore than a dozen civil society groups, including Demand Progress Education Fund, the Consumer Federation of America, and the Institute for Local Self-Reliance, are urging the FTC to investigate these practices, particularly those involving rare books.

Are AI companies to blame? Last week, the internet raged as social-media posts and news articles accused AI companies of "destroying the world's books" --including "millions of rare" ones--by chopping off their spines to scan them more easily, and discarding them afterward. One article said the news was "sparking concerns that the last remaining copies of out-of-print texts are being destroyed." The investor and AI skeptic Michael Burry called the practice of sacrificing rare books "evil incarnate." Even Elon Musk weighed in, posting that he had asked the engineers training xAI's models to "preserve any rare books in a library and scan them the hard way."

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Three aid workers killed, 4 wounded in RSF drone attack in Sudan's Kordofan At least three aid workers have been killed and four others wounded in a drone attack by the paramilitary Rapid Support Forces (RSF) on an aid convoy in Sudan's South Kordofan state, according to the Sudan Doctors Network, in the latest carnage against civilians caught up in the nation's brutal civil war. The convoy of trucks carrying food and humanitarian supplies was targeted by the RSF, and its ally, the Sudan People's Liberation Movement-North, while travelling through the Kartala area on its way to the cities of Kadugli and Dilling on Thursday. The network said that this attack marked the "second such incident in less than a month, following the shelling of a United Nations aid convoy in the town of Al-Rahad," adding: "this dangerous escalation threatens the safety of humanitarian operations and further exacerbates civilian suffering". The Sudan Doctors Network reiterated its call to the "international community, the United Nations, and human rights organisations to exert urgent and effective pressure on the leadership of the Rapid Support Forces to ensure the protection of aid convoys and their workers, to open safe and sustainable humanitarian corridors, and to hold those responsible for targeting aid accountable". Al Jazeera could not independently verify the latest RSF attack, which came a month after the government-aligned Sudanese Armed Forces (SAF) announced that it had broken a nearly two-year-long RSF siege on Dilling.

We present AgentZero++, an agent-based model that integrates cognitive, emotional, and social mechanisms to simulate decentralized collective violence in spatially distributed systems. Building on Epstein's Agent\_Zero framework, we extend the original model with eight behavioral enhancements: age-based impulse control; memory-based risk estimation; affect-cognition coupling; endogenous destructive radius; fight-or-flight dynamics; affective homophily; retaliatory damage; and multi-agent coordination. These additions allow agents to adapt based on internal states, previous experiences, and social feedback, producing emergent dynamics such as protest asymmetries, escalation cycles, and localized retaliation. Implemented in Python using the Mesa ABM framework, AgentZero++ enables modular experimentation and visualization of how micro-level cognitive heterogeneity shapes macro-level conflict patterns. Our results highlight how small variations in memory, reactivity, and affective alignment can amplify or dampen unrest through feedback loops. By explicitly modeling emotional thresholds, identity-driven behavior, and adaptive networks, this work contributes a flexible and extensible platform for analyzing affective contagion and psychologically grounded collective action.

NVIDIA CEO and co-founder Jensen Huang commends President Donald Trump's A.I. agenda and outlines what the country's job future will look like on'Special Report.' Classical and character-based education may seem to some antiquated concepts in the new AI-driven world. However, two recent and prominent AI developments definitively prove the opposite to be true. Going back to our nation's founding, great minds were universal in the belief that the survival of the Republic depended on an educated and virtuous public. Now, if AI experts are to be believed, classical and character education is fundamental to the very survival of humanity.

When you think of Nintendo, it's almost impossible not to picture Donkey Kong. Yet despite Donkers' undeniable place in gaming history – and obligatory appearances in Smash Bros and Mario Kart – for the last few console generations, Donkey Kong platformers have been MIA. Enter DK's first standalone adventure in 11 years, Donkey Kong Bananza. While Mario's recent adventures saw him exploring the reaches of outer space or deftly possessing enemies with an anthropomorphic hat, DK's grand return is all about primal rage. As you smash and punch your way through walls, floors and ceilings, you can burrow all the way to the ground below, forging new paths and unearthing hidden treasures.

A fragile ceasefire remains in place between Israel and Iran, one day after US President Donald Trump announced a truce, ending 12 days of fighting that erupted following Israeli strikes on Tehran's nuclear and military sites. An analysis of data from the Armed Conflict Location and Event Data Project (ACLED) shows that between October 7, 2023, and just before Israel attacked Iran on June 13, 2025, Israel carried out nearly 35,000 recorded attacks across five countries: the occupied Palestinian territory, Lebanon, Syria, Yemen, and Iran. These attacks include air and drone strikes, shelling and missile attacks, remote explosives, and property destruction. The majority of attacks have been on Palestinian territory with at least 18,235 recorded incidents, followed by Lebanon (15,520), Syria (616), Iran (58) and Yemen (39). While the bulk of Israel's attacks have concentrated on nearby Gaza, the occupied West Bank, and Lebanon, its military operations have also reached far beyond its immediate borders.

The most accurate clock in space launches within days and will begin building a highly synchronised network out of the best clocks on Earth. But the project, decades in preparation, will only operate for a few years before it burns up as the International Space Station deorbits at the end of the decade. NASA's most accurate atomic clock will be tested on a mission to Venus The Atomic Clock Ensemble in Space (ACES) is a European Space Agency (ESA) mission that will generate a time signal with unprecedented accuracy and then transmit it via laser to nine ground stations as it passes overhead at 27,000 kilometres per hour. This network of clocks will be in extremely close synchronisation and provide highly accurate timekeeping around the world. The result is that ACES will be able to test Einstein's theory of general relativity, which says that the passing of time is affected by the strength of gravity, with great accuracy.

Recent advancements in Neural Combinatorial Optimization (NCO) have shown promise in solving routing problems like the Traveling Salesman Problem (TSP) and Capacitated Vehicle Routing Problem (CVRP) without handcrafted designs. Research in this domain has explored two primary categories of methods: iterative and non-iterative. While non-iterative methods struggle to generate near-optimal solutions directly, iterative methods simplify the task by learning local search steps. However, existing iterative methods are often limited by restricted neighborhood searches, leading to suboptimal results. To address this limitation, we propose a novel approach that extends the search to larger neighborhoods by learning a destroy-and-repair strategy. Specifically, we introduce a Destroy-and-Repair framework based on Hyper-Graphs (DRHG). This framework reduces consecutive intact edges to hyper-edges, allowing the model to pay more attention to the destroyed part and decrease the complexity of encoding all nodes. Experiments demonstrate that DRHG achieves stateof-the-art performance on TSP with up to 10,000 nodes and shows strong generalization to real-world TSPLib and CVRPLib problems.