The world is closer than ever to destruction, scientists have said, as the Doomsday Clock was set at 85 seconds to midnight for 2026, the gloomiest assessment of humanity's prospects since the beginning of the tradition in 1947. The Bulletin of the Atomic Scientists, a not-for-profit organisation founded by Albert Einstein and other scientists, warned in its annual assessment on Tuesday that international cooperation is going backwards on nuclear weapons, climate change and biotechnology, while artificial intelligence poses new threats. "The Doomsday Clock's message cannot be clearer. Catastrophic risks are on the rise, cooperation is on the decline, and we are running out of time," said Alexandra Bell, the president and CEO of the Bulletin of the Atomic Scientists. In a more detailed statement explaining the reasoning for moving the clock closer to midnight, the bulletin expressed concerns that countries including Russia, China, and the United States were becoming "increasingly aggressive, adversarial, and nationalistic".

Doomsday Clock moves to 85 seconds to midnight as Bulletin of the Atomic Scientists warns of increased risks from nuclear war, climate change and AI.

A simple trick cured my tinnitus after a long-haul flight left me in misery for months. Here's the miracle method I wish everyone knew I was diagnosed with cancer after strange things began happening to my hands - here are the symptoms you can't ignore Explosive twist in'diva' inmate Bryan Kohberger's life in prison revealed in the FREE The Crime Desk newsletter Marco Rubio'cocoons like a mummy' in bizarre strategy to hide naps from Trump Food Network star Valerie Bertinelli's heartbreaking struggles laid bare after confession about shock firing Devastating truth about Blind Side actor Quinton Aaron: More to this'than everyone is letting on', friends reveal... as co-star Sandra Bullock'monitors' situation Mother hit by unimaginable triple tragedy after'son, 6, fell through icy pond and brothers aged 8 and 9 jumped in to save him' Sydney Sweeney shows off her bombshell curves in racy lingerie to promote her new SYRN line - as it's revealed Hollywood Sign bra stunt could leave her facing trespassing and vandalism charges Lawyer, 44, who died on flight to London after falling asleep on her mother's shoulder had undiagnosed cardiac condition, inquest hears Top Citi banker displayed'sexually charged' behavior towards female underling and let co-workers think they were having affair, harassment lawsuit alleges Revealed: Tupac Shakur's'crack fiend mama' lived in'SCARY' houseboat community full of drug addicts like'Psycho Steve' before shock death My perfect life at $2m Manchester-by-the-Sea mansion took nasty turn when neighbors tried to ban me from getting a gun because of my HUSBAND - now I've had the last laugh Boy, 15, has been missing for two weeks after sneaking away to New York to meet stranger he'd chatted to on Roblox Nicola Peltz could barely speak Victoria Beckham's name, says interviewer who quizzed her about THAT wedding dress row in explosive new chapter of family feud Doctor who was branded'tone deaf' for flaunting her Louboutin heels at work furiously hits back at critics Doomsday Clock ticks forward... moving humanity closer to annihilation than ever before The Doomsday Clock, which has been ticking down to the end of the world for decades, is now officially closer to annihilation than ever before. On Tuesday, scientists with the Bulletin of Atomic Scientists moved the symbolic clock four seconds forward to 85 seconds to midnight . It's also the closest the clock has ever been to midnight in its 79-year history, meaning experts believe humanity has never faced a more dire threat of a world-ending catastrophe than it does in 2026. The group, which decides where the hands are set annually, cited multiple threats to global stability, including nuclear weapons, climate change, disruptive technologies like AI, and the creation of synthetic biological substances called'mirror life.' Alexandra Bell, president and CEO of the Bulletin of Atomic Scientists, said: 'Every second counts and we are running out of time.

Trump Warned of a Tren de Aragua'Invasion.' Hundreds of records obtained by WIRED show thin intelligence on the Venezuelan gang in the United States, describing fragmented, low-level crime rather than a coordinated terrorist threat. Alleged members of Tren de Aragua sit handcuffed during a preliminary hearing on July 9, 2025, in Santiago, Chile, where they faced homicide charges. As the Trump administration publicly cast Venezuela's Tren de Aragua (TdA) as a unified terrorist force tied to President Nicolás Maduro and operating inside the United States, hundreds of internal US government records obtained by WIRED tell a far less certain story. Intelligence taskings, law-enforcement bulletins, and drug-task-force assessments show that agencies spent much of 2025 struggling to determine whether TdA even functioned as an organized entity in the US at all--let alone as a coordinated national security threat.

Despite the promising capability of multimodal foundation models, their application to the generation of meteorological products and services remains nascent. To accelerate aspiration and adoption, we explore the novel use of a vision language model for writing the iconic Shipping Forecast text directly from video-encoded gridded weather data. These early results demonstrate promising scalable technological opportunities for enhancing production efficiency and service innovation within the weather enterprise and beyond.

As tropical cyclones intensify and track forecasts become increasingly uncertain, U.S. ports face heightened supply-chain risk under extreme weather conditions. Port operators need to rapidly synthesize diverse multimodal forecast products, such as probabilistic wind maps, track cones, and official advisories, into clear, actionable guidance as cyclones approach. Multimodal large language models (MLLMs) offer a powerful means to integrate these heterogeneous data sources alongside broader contextual knowledge, yet their accuracy and reliability in the specific context of port cyclone preparedness have not been rigorously evaluated. To fill this gap, we introduce CyPortQA, the first multimodal benchmark tailored to port operations under cyclone threat. CyPortQA assembles 2,917 real-world disruption scenarios from 2015 through 2023, spanning 145 U.S. principal ports and 90 named storms. Each scenario fuses multi-source data (i.e., tropical cyclone products, port operational impact records, and port condition bulletins) and is expanded through an automated pipeline into 117,178 structured question-answer pairs. Using this benchmark, we conduct extensive experiments on diverse MLLMs, including both open-source and proprietary model. MLLMs demonstrate great potential in situation understanding but still face considerable challenges in reasoning tasks, including potential impact estimation and decision reasoning.

Humanity is officially one second closer to world annihilation, scientists say. The Doomsday Clock has been revealed – and it now sits at 89 seconds to midnight, one second closer than last year. It's also the closest the clock has ever been to midnight in its 78-year history, meaning we're nearer to world-ending catastrophe than ever before. The Bulletin of Atomic Scientists, which decides where the hands are set, cited the Russia-Ukraine war, ongoing conflicts in the Middle East, the threat of nuclear war, climate change, a looming bird flu pandemic and AI arms race for the update. The Chicago-based nonprofit created the Doomsday Clock in 1947 during the Cold War tensions that followed World War II to warn the public about how close humankind was to destroying the world.

This month, humanity will learn just how close we are to annihilation. Every January, the Bulletin of the Atomic Scientists (BAS) sets a new time for the Doomsday Clock - the symbolic scale for humanity's proximity to the apocalypse. Last year, scientists left the clock sitting at 90 seconds to midnight - the closest humanity had come to destruction since the creation of the atomic bomb. But with war still raging in Ukraine and chaos across the Middle East, experts say that the risk of nuclear war is now'far too high'. Dr Haydn Belfield, research associate at the Centre for the Study of Existential Risk, told MailOnline: 'We are probably closer to nuclear war than at any point in the last forty years.'

Double difference earthquake relocation is an essential component of many earthquake catalog development workflows. This technique produces high-resolution relative relocations between events by minimizing differential measurements of the arrival times of waves from nearby sources, which highlights the resolution of faults and improves interpretation of seismic activity. The inverse problem is typically solved iteratively using conjugate-gradient minimization, however the cost scales significantly with the total number of sources and stations considered. Here we propose a Graph Neural Network (GNN) based earthquake double-difference relocation framework, Graph Double Difference (GraphDD), that is trained to minimize the double-difference residuals of a catalog to locate earthquakes. Through batching and sampling the method can scale to arbitrarily large catalogs. Our architecture uses one graph to represent the stations, a second graph to represent the sources, and creates the Cartesian product graph between the two graphs to capture the relationships between the stations and sources (e.g., the residuals and travel time partial derivatives). This key feature allows a natural architecture that can be used to minimize the double-difference residuals. We implement our model on several distinct test cases including seismicity from northern California, Turkiye, and northern Chile, which have highly variable data quality, and station and source distributions. We obtain high resolution relocations in these tests, and our model shows adaptability to variable types of loss functions and location objectives, including learning station corrections and mapping into the reference frame of a different catalog. Our results suggest that a GNN approach to double-difference relocation is a promising direction for scaling to very large catalogs and gaining new insights into the relocation problem.

Classical point process models, such as the epidemic-type aftershock sequence (ETAS) model, have been widely used for forecasting the event times and locations of earthquakes for decades. Recent advances have led to Neural Point Processes (NPPs), which promise greater flexibility and improvements over classical models. However, the currently-used benchmark dataset for NPPs does not represent an up-to-date challenge in the seismological community since it lacks a key earthquake sequence from the region and improperly splits training and testing data. Furthermore, initial earthquake forecast benchmarking lacks a comparison to state-of-the-art earthquake forecasting models typically used by the seismological community. To address these gaps, we introduce EarthquakeNPP: a collection of benchmark datasets to facilitate testing of NPPs on earthquake data, accompanied by a credible implementation of the ETAS model. The datasets cover a range of small to large target regions within California, dating from 1971 to 2021, and include different methodologies for dataset generation. In a benchmarking experiment, we compare three spatio-temporal NPPs against ETAS and find that none outperform ETAS in either spatial or temporal log-likelihood. These results indicate that current NPP implementations are not yet suitable for practical earthquake forecasting. However, EarthquakeNPP will serve as a platform for collaboration between the seismology and machine learning communities with the goal of improving earthquake predictability.