OpenAI is facing a criminal investigation in the US over whether its ChatGPT technology played a part in the murder of two people during a mass shooting at Florida State University last year. Florida's Attorney General James Uthmeier said on Tuesday his office had been looking into the use of the artificial intelligence (AI) chatbot by a man who allegedly shot several people at the campus in Tallahassee. Our review has revealed that a criminal investigation is necessary, Uthmeier said. ChatGPT offered significant advice to this shooter before he committed such heinous crimes. An OpenAI spokesperson said: ChatGPT is not responsible for this terrible crime.

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.

Hackers made death threats against this security researcher. In April 2024, a mysterious someone using the online handles "Waifu" and "Judische" began posting death threats on Telegram and Discord channels aimed at a cybersecurity researcher named Allison Nixon. These anonymous personas targeted Nixon because she had become a formidable threat: As chief research officer at the cyber investigations firm Unit 221B, named after Sherlock Holmes's apartment, she had built a career tracking cybercriminals and helping get them arrested. Though she'd done this work for more than a decade, Nixon couldn't understand why the person behind the accounts was suddenly threatening her. And although she had taken an interest in the Waifu persona in years past for crimes he boasted about committing, he hadn't been on her radar for a while when the threats began, because she was tracking other targets. Now Nixon resolved to unmask Waifu/Judische and others responsible for the death threats--and take them down for crimes they admitted to committing.

People have a right to know who their neighbors are, especially when it's ICE. On Tuesday, WIRED published details of ICE's planned expansion into more than 150 office spaces across the United States, including 54 specific addresses. ICE has designs on every major US city. It plans to not only occupy existing government spaces but share hallways and elevator bays with medical offices and small businesses. It will be down the street from daycares and within walking distance of churches and treatment centers.

Weshowtheperformance ofGETF onhigh order tensor data inFigure 6. Noted, when theorder increases, the tensor size would increase exponentially.

Who is in the Epstein files? The list of some of the world's most rich and powerful people with ties to late sex offender Jeffrey Epstein has lengthened with the latest US government release of millions of new files from its investigation into the disgraced financier. The 30 January drop of new material - dubbed the Epstein files - included three million pages, 180,000 images, 2,000 videos, and a number of household names like Richard Branson, Bill Gates and Elon Musk. There is no suggestion that appearing in the documents implies any wrongdoing, and many people who have featured in previous releases have denied any wrongdoing in relation to Epstein. The release came weeks after the deadline set by the Epstein Files Transparency Act which was signed into law by US President Donald Trump in November and required a full release of all Epstein-related documents.