The roll-out of the European Union's Artificial Intelligence Act has hit a critical turning point. The act establishes rules for how AI systems can be used within the European Union. It officially entered into force on August 1 2024, although different rules come into effect at different times. The European Commission has now proposed delaying parts of the act until 2027. This follows intense pressure from tech companies and from the Trump administration.

WIRED brought 10 of the most popular artificial Christmas trees into a studio and got three interior designers to pick the best through blind judging. For extra trimming, we checked in on how those trees fared once they were taken home and decorated. Shopping for an artificial Christmas tree can be overwhelming, especially when you're doing it online. You'll find yourself staring at product photos, wondering: How realistic does it look? Will it shed all over my living room? Can you see daylight through the branches? Are the branches strong enough to hold that lopsided homemade macaroni ornament you've hung on your tree since 2004? We got tired of guessing, so we did a little experiment. We brought 10 of the most popular artificial trees from three top brands (Balsam Hill, King of Christmas, and National Tree Company) and hauled them to a photo studio in Kansas.

Spotify Wrapped is the streaming service's yearly review of users' listening habits. When it does arrive, the recap will likely fix the usual mix of users' top songs and most-streamed artists, as well as some interesting facts about how much you've listened over the year. In previous years, Spotify has always made sure to drop in a few unusual or surprising features, so expect to see a new way of reviewing your music this year. Despite users clamouring to learn when Spotify Wrapped will arrive, the company has never set a firm date for its release. Currently, you can access a landing page for the 2025 Spotify Wrapped, but it only links back to the 2024 recap.

Karoline Leavitt's family member was swarmed by ICE agents while picking up son from school as child's father tell her to'self deport' Deaths from highly infectious virus are growing... as states brace for widespread outbreaks My book on the Kennedys was used as a'mistress manual' by Olivia Nuzzi... then this wannabe Carolyn Bessette had the nerve to hound me with these outrageous texts: MAUREEN CALLAHAN Katy Perry's legal victory as judge orders disabled veteran to pay singer nearly $2m over Montecito mansion Trump reveals next DC renovation project to remove'Biden filth' after White House ballroom Cracker Barrel CEO whines that she got'fired by America' for woke redesign Kroger employee reveals shocking amount laundry products have increased by... 'biggest price jump I've seen in a single week' Hollywood heir, 23, whose mom Anne Heche died in horror car fireball has secret LOVE CHILD with 43-year-old... now she's telling all Missing Melodee Buzzard's mom'left her daughter with strangers she met at the zoo' Rachel Zoe reveals why she dumped husband of 26 years... and if she has started dating again Horrific moment cops found body of Cowboys star Marshawn Kneeland after he shot himself at end of 145 mph chase'This is pretty lurid' Jenny McCarthy, 53, reveals health emergency that involved NINE surgeries, her'teeth falling out' and'growth' on her eyeballs Maryland grandma, 58, dragged across floor after being deported to country she'has never even visited' The United Nations (UN) has confirmed that Earth's planetary defenses will be observing the interstellar comet 3I/ATLAS as it races through our solar system . Starting on November 27, a global team of scientists with the International Asteroid Warning Network (IAWN) will kick off a two-month campaign to track the comet as it nears our planet . 'While it poses no threat, comet 3I/ATLAS presents a great opportunity for the IAWN community to perform an observing exercise due to its prolonged observability from Earth and high interest to the scientific community,' the UN explains on its website. 'This 3I/ATLAS campaign is the 8th IAWN observing exercise since 2017 - IAWN holds these exercises roughly once a year.' While 3I/ATLAS was only discovered in July 2025, the UN explained that this'comet campaign' has long been planned.

They might be the smallest falcon, but American kestrels still intimidate other birds. Breakthroughs, discoveries, and DIY tips sent every weekday. No one wants poop on their cherries . Farmers in northern Michigan could get some help on this fecal matter from some feathered allies. Small falcons called the American kestrel help deter smaller birds that like to snack on the fruit when it is growing.

A bear warning sign is displayed in Shirakawa-go, a popular tourist spot in Gifu Prefecture. A town in Miyagi Prefecture has retracted its social media post warning of a bear sighting after discovering an image submitted to it had been generated using artificial intelligence. A Japanese town has deleted a social media post warning of a bear sighting after discovering that a picture it had received showing the fearsome creature was generated using artificial intelligence. Similar fake images have been circulating online as fear of bears runs high in the country, where the animals have killed a record 13 people this year. "The town prioritized informing residents to avoid danger, but we apologize for causing any anxiety or confusion," the town of Onagawa, Miyagi Prefecture, said on its official X social media account on Wednesday.

Australia clamps downs on'nudify' sites used for AI-generated child abuse Internet users in Australia have been blocked from accessing several websites that used artificial intelligence to create child sexual exploitation material, the country's internet regulator has announced. The three "nudify" sites withdrew from Australia following an official warning, eSafety Commissioner Julie Inman Grant said on Thursday. Grant said such "nudify" services, which allow users to make images of real people appear naked using AI, have had a "devastating" effect in Australian schools. "We took enforcement action in September because this provider failed to put in safeguards to prevent its services being used to create child sexual exploitation material and were even marketing features like undressing'any girl,' and with options for'schoolgirl' image generation and features such as'sex mode,'" Grand said in a statement. The development comes after Grant's office issued a formal warning to the United Kingdom-based company behind the sites in September, threatening civil penalties of up to 49.5 million Australian dollars ($32.2m) if it did not introduce safeguards to prevent image-based abuse.

Causal effect estimation in networked systems is central to data-driven decision making. In such settings, interventions on one unit can spill over to others, and in complex physical or social systems, the interaction pathways driving these interference structures remain largely unobserved. We argue that for identifying population-level causal effects, it is not necessary to recover the exact network structure; instead, it suffices to characterize how those interactions contribute to the evolution of outcomes. Building on this principle, we study an evolution-based approach that investigates how outcomes change across observation rounds in response to interventions, hence compensating for missing network information. Using an exposure-mapping perspective, we give an axiomatic characterization of when the empirical distribution of outcomes follows a low-dimensional recursive equation, and identify minimal structural conditions under which such evolution mappings exist. We frame this as a distributional counterpart to difference-in-differences. Rather than assuming parallel paths for individual units, it exploits parallel evolution patterns across treatment scenarios to estimate counterfactual trajectories. A key insight is that treatment randomization plays a role beyond eliminating latent confounding; it induces an implicit sampling from hidden interference channels, enabling consistent learning about heterogeneous spillover effects. We highlight causal message passing as an instantiation of this method in dense networks while extending to more general interference structures, including influencer networks where a small set of units drives most spillovers. Finally, we discuss the limits of this approach, showing that strong temporal trends or endogenous interference can undermine identification.

AI/ML models have rapidly gained prominence as innovations for solving previously unsolved problems and their unintended consequences from amplifying human biases. Advocates for responsible AI/ML have sought ways to draw on the richer causal models of system dynamics to better inform the development of responsible AI/ML. However, a major barrier to advancing this work is the difficulty of bringing together methods rooted in different underlying assumptions (i.e., Dana Meadow's "the unavoidable a priori"). This paper brings system dynamics and structural equation modeling together into a common mathematical framework that can be used to generate systems from distributions, develop methods, and compare results to inform the underlying epistemology of system dynamics for data science and AI/ML applications.

Markov Chain Monte Carlo (MCMC) is a flexible approach to approximate sampling from intractable probability distributions, with a rich theoretical foundation and comprising a wealth of exemplar algorithms. While the qualitative correctness of MCMC algorithms is often easy to ensure, their practical efficiency is contingent on the `target' distribution being reasonably well-behaved. In this work, we concern ourself with the scenario in which this good behaviour is called into question, reviewing an emerging line of work on `robust' MCMC algorithms which can perform acceptably even in the face of certain pathologies. We focus on two particular pathologies which, while simple, can already have dramatic effects on standard `local' algorithms. The first is roughness, whereby the target distribution varies so rapidly that the numerical stability of the algorithm is tenuous. The second is flatness, whereby the landscape of the target distribution is instead so barren and uninformative that one becomes lost in uninteresting parts of the state space. In each case, we formulate the pathology in concrete terms, review a range of proposed algorithmic remedies to the pathology, and outline promising directions for future research.