Kim Jong Un praises troops who'self-blasted' to avoid capture by Ukraine Kim Jong Un has praised North Korean soldiers who killed themselves by detonating their grenades while fighting for Russia against Ukraine, confirming a long-suspected battlefield policy. In a speech this week, the North Korean leader said those who unhesitatingly opted for self-blasting, suicide attack, in order to defend the great honour were heroes. South Korea estimates at least 15,000 North Koreans have been sent to help Russia recapture parts of western Kursk, and more than 6,000 have been killed so far. Neither Pyongyang nor Moscow have confirmed the numbers. Intelligence agencies and defectors have said the soldiers were under Pyongyang's orders to kill themselves rather than be taken prisoner by Ukraine.

One group of hackers used AI for everything from vibe coding their malware to creating fake company websites--and stole as much as $12 million in three months. The advent of AI hacking tools has raised fears of a near future in which anyone can use automated tools to dig up exploitable vulnerabilities in any piece of software, like a kind of digital intrusion superpower. Here in the present, however, AI seems to be playing a more mundane, if still concerning, role in hackers' toolkit: It's helping mediocre hackers level up and carry out broad, effective malware campaigns. That includes one group of relatively unskilled North Korean cybercriminals who've been discovered using AI to carry out virtually every part of an operation that hacked thousands of victims to steal their cryptocurrency. On Wednesday, cybersecurity firm Expel revealed what it describes as a North Korean state-sponsored cybercrime operation that installed credential-stealing malware on more than 2,000 computers, specifically targeting the machines of developers working on small cryptocurrency launches, NFT creation, and Web3 projects.

The sequential nature of autoregressive next-token prediction imposes a fundamental speed limit on large language models. While continuous flow models offer a path to parallel generation, they traditionally demand expensive iterative integration. Flow Maps bypass this bottleneck by compressing generative trajectories into single-step mappings, theoretically enabling the generation of full text sequences from noise in a single forward pass. However, standard formulations rely on Euclidean regression losses that are geometrically ill-suited for discrete data. In this work, we resolve this conflict with Discrete Flow Maps, a framework that reconciles trajectory compression with the geometry of the probability simplex. We recast standard flow map training for the discrete domain, aligning the training dynamics with the discrete nature of language. Empirically, this strict geometric alignment allows our method to surpass previous state-of-the-art results in discrete flow modeling.

Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as $O(N^2)$ in the number of events. The canonical linear exponential Hawkes process admits a faster $O(N)$ recurrence, but prior work evaluates this recurrence sequentially, without exploiting parallelization on modern GPUs. We show that the Hawkes process intensity can be expressed as a product of sparse transition matrices admitting a linear-time associative multiply, enabling computation via a parallel prefix scan. This yields a simple yet massively parallelizable algorithm for maximum likelihood estimation of linear exponential Hawkes processes. Our method reduces the computational complexity to approximately $O(N/P)$ with $P$ parallel processors, and naturally yields a batching scheme to maintain constant memory usage, avoiding GPU memory constraints. Importantly, it computes the exact likelihood without any additional assumptions or approximations, preserving the simplicity and interpretability of the model. We demonstrate orders-of-magnitude speedups on simulated and real datasets, scaling to thousands of nodes and tens of millions of events, substantially beyond scales reported in prior work. We provide an open-source PyTorch library implementing our optimizations.

In its early days, the AI initiative known as Project Maven had its fair share of skeptics at the Pentagon. Today, many of them are true believers. The rise of AI warfare speaks to the biggest moral and practical question there is: Who--or what--gets to decide to take a human life? And who bears that cost? In 2018, more than 3,000 Google workers protested the company's involvement in "the business of war" after finding out the company was part of Project Maven, then a nascent Pentagon effort to use computer vision to rifle through copious video footage taken in America's overseas drone wars. They feared Project Maven's AI could one day be used for lethal targeting. In my yearslong effort to uncover the full story of Project Maven for my book,, I learned that is exactly what happened, and that the undertaking was just as controversial inside the Pentagon. Today, the tool known as Maven Smart System is being used in US operations against Iran . How the US military's top brass moved from skepticism about the use of AI in war to true believers has a lot to do with a Marine colonel named Drew Cukor. In early September 2024, during the cocktail hour at a private retreat for tech investors and defense leaders, Vice Admiral Frank "Trey" Whitworth found his way to Drew Cukor. Now Project Maven's founding leader and his skeptical successor were standing face-to-face. Three years earlier, Whitworth had been the Pentagon's top military official for intelligence, advising the chairman of the Joint Chiefs of Staff and running one of the most sensitive and potentially lethal parts of any military process: targeting.

Chinese President Xi Jinping, Russian President Vladimir Putin and North Korean leader Kim Jong Un arrive for a reception marking the 80th anniversary of the end of World War II, at the Great Hall of the People in Beijing on Sept. 3, 2025. Moscow and Beijing are driving closer collaboration between authoritarian states and such networks help advance repression globally, according to researchers who used artificial intelligence to drill into the activities. The U.S.-based nonprofit Action for Democracy said in a report Wednesday that its researchers built an index to track seven types of cooperation, including on funding, diplomatic activities, propaganda and tech sharing. It found that China and Russia sit at the center of global authoritarian collaboration" and were jointly involved in around half of all recorded activity. The report's authors said that such cooperation generated compound returns because, for example, surveillance infrastructure exported to one regime becomes a template for the next." In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Plus: Elizabeth Warren wants answers on xAI's access to military data. Human-made glass is thousands of years old. But it's now poised to find its way into the AI chips used in the world's newest and largest data centers. This year, a South Korean company called Absolics will start producing special glass panels that make next-generation computing hardware more powerful and efficient. Other companies, including Intel, are also pushing forward in this area. If all goes well, the technology could reduce the energy demands of chips in AI data centers--and even consumer laptops and mobile devices.

Iraq's Prime Minister Mohammed Shia al-Sudani faces pressure to act against Iran-backed terrorist groups following increased attacks on U.S., European, and Kurdish assets in the country.

President Donald Trump warns NATO allies they face a 'very bad' future if they don't help defend the Strait of Hormuz, telling The Financial Times beneficiaries should assist.

Has Trump failed to sell the Iran war to the world? Are US-Israeli attacks against Iran legal? As anticipated, it ended up being One Battle After Another's night at the 98th annual Academy Awards, with the political thriller carting away six Oscars out of a total of 13 nominations. But while Paul Thomas Anderson's magnum opus continued its march towards awards-season domination, there were moments of genuine surprise and subversion in Sunday's ceremony. Host Conan O'Brien and his fellow presenters deftly avoided mentioning President Donald Trump by name, but their barbs took direct aim at his policies since returning to office.