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You're viewing the US edition You can switch to the UK or AU homepage at any time using this menu. Devastating wildfire burning through Nevada threatens Reno...injury count rises as homes and a hospital forced to EVACUATE The images that shocked the world: How Taliban's medieval barbarity was exposed by video showing a woman stoned to death for adultery Tupac's brother speaks: The rapper's hidden life, a secret career he never got to have... and the haunting pain as a gang leader finally stands trial for his 1996 killing Lindsay Clancy's supporters are all suddenly acting strange. I'm afraid of what they might do next... something very sick is going on: KENNEDY WNBA star ejected for elbowing rival in the face in league's latest brutal foul The retro diet food making a comeback... experts reveal if the beloved 80s'it' ingredient is key to weight loss Picturesque Jewish summer camp quickly turns into nightmare after drunken gunman open fired on basketball court...where campers as young as SEVEN were playing SARAH VINE: Sorry, Meghan, there's a new Fab Four now... and I wouldn't want to be in your shoes facing these remarkable, glamorous women across the damask in the drawing room at Balmoral CLAUDIA CONNELL: I lost 16lb... after I'd already QUIT the fat jabs. Kobe Bryant's widow Vanessa shares touching tribute on what would've been his 48th birthday Trump's son-in-law meets with top House Democrat as Republicans stare down a potential midterm disaster Owner of Swiss bar that went up in flames and killed 41 is arrested'for domestic abuse against his wife' Harry and Meghan will look to become'private royals-plus' while back in the UK and may only stay one year before moving to Canada or Australia, says source Mysterious'lost continent' linked to alien beings may have finally been located Hayden Panettiere's mom: 'My daughter didn't want to be saved!' Read bombshell hour-long interview on what she thinks REALLY happened at death-scene Airbnb... her jaw-dropping Brian Hickerson allegations... and fury at'shameful' Gayle King It used to only be gay men... but now my female friends are trying this dangerous sex drug: JANA HOCKING READ MORE: How AI cops will be used to patrol Britain's streets It's designed for non-emergency police incidents - but it seems many Brits are taking the mickey when it comes to calling 101. The most ridiculous calls to the service have been revealed, and they range from the silly to the absurd.

This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG . 'The Odyssey' streaming scam could steal your bank info Trump puts brakes on OpenAI's newest AI model NASA's Chandra telescope reveals Milky Way's outer reaches may stretch farther than previously known'Milestone': Scientists claim to build synthetic cell, raising concerns in step toward artificial life Boy's jaw-dropping Jersey Shore find turns out to be millions of years old Archaeological discovery offers stunning support for Scripture, says Dinesh D'Souza Bible skeptics face decisive archaeological evidence, author Dinesh D'Souza says Pentagon releases UAP files showing'cold orbs,' 'triangular objects' Jesse Watters: Whatever these are, they keep showing up where they shouldn't Family of boy rescued from California monster surf says teen hero became'extended family' Ancient manuscript unlocks lost sermons from one of Christianity's founding thinkers Kurt CyberGuy Knutsson explains how a mystery voicemail scam can shows up on your phone multiple times without notice. Your phone buzzes with a voicemail notification.

Data analysis has become an indispensable part of scientific research. To discover the latent knowledge and insights hidden within massive datasets, we need to perform deep exploratory analysis to realize their full value. With the advent of large language models (LLMs) and multi-agent systems, more and more researchers are making use of these technologies for insight discovery. However, there are few benchmarks for evaluating insight discovery capabilities. As one of the most comprehensive existing frameworks, InsightBench also suffers from many critical flaws: format inconsistencies, poorly conceived objectives, and redundant insights. These issues may significantly affect the quality of data and the evaluation of agents. To address these issues, we thoroughly investigate shortcomings in InsightBench and propose essential criteria for a high-quality insight benchmark. Regarding this, we develop a data-curation pipeline to construct a new dataset named InsightEval. We further introduce a novel metric to measure the exploratory performance of agents. Through extensive experiments on InsightEval, we highlight prevailing challenges in automated insight discovery and raise some key findings to guide future research in this promising direction.

Animal vocalizations contain sequential structures that carry important communicative information, yet most computational bioacoustics studies average the extracted frame-level features across the temporal axis, discarding the order of the sub-units within a vocalization. This paper investigates whether discrete acoustic token sequences, derived through vector quantization and gumbel-softmax vector quantization of extracted self-supervised speech model representations can effectively capture and leverage temporal information. To that end, pairwise distance analysis of token sequences generated from HuBERT embeddings shows that they can discriminate call-types and callers across four bioacoustics datasets. Sequence classification experiments using $k$-Nearest Neighbour with Levenshtein distance show that the vector-quantized token sequences yield reasonable call-type and caller classification performances, and hold promise as alternative feature representations towards leveraging sequential information in animal vocalizations.

Apple's Best New iOS 26 Feature Has Been on Pixel Phones for Years The iPhone's new software screens your calls using machine intelligence. Neat, but Google had the feature first--just like so many other features that rely on AI to work. Call Screening on an iPhone. Ever since I was a child, I've despised answering the phone when an unknown number calls. Who could be on the other end?

A BBC Verify investigation has revealed that the identities of British public sector workers have been cloned using AI by a Russian-linked disinformation campaign. The BBC's Olga Robinson has tracked down and spoken to an emergency medical advisor from Preston in England, who was shocked to learn his voice had been faked in a video campaign spreading fear ahead of Poland's presidential election earlier this year.

Emergency response services are critical to public safety, with 9-1-1 call-takers playing a key role in ensuring timely and effective emergency operations. To ensure call-taking performance consistency, quality assurance is implemented to evaluate and refine call-takers' skillsets. However, traditional human-led evaluations struggle with high call volumes, leading to low coverage and delayed assessments. We introduce LogiDebrief, an AI-driven framework that automates traditional 9-1-1 call debriefing by integrating Signal-Temporal Logic (STL) with Large Language Models (LLMs) for fully-covered rigorous performance evaluation. LogiDebrief formalizes call-taking requirements as logical specifications, enabling systematic assessment of 9-1-1 calls against procedural guidelines. It employs a three-step verification process: (1) contextual understanding to identify responder types, incident classifications, and critical conditions; (2) STL-based runtime checking with LLM integration to ensure compliance; and (3) automated aggregation of results into quality assurance reports. Beyond its technical contributions, LogiDebrief has demonstrated real-world impact. Successfully deployed at Metro Nashville Department of Emergency Communications, it has assisted in debriefing 1,701 real-world calls, saving 311.85 hours of active engagement. Empirical evaluation with real-world data confirms its accuracy, while a case study and extensive user study highlight its effectiveness in enhancing call-taking performance.

The rise of Agentic applications and automation in the Voice AI industry has led to an increased reliance on Large Language Models (LLMs) to navigate graph-based logic workflows composed of nodes and edges. However, existing methods face challenges such as alignment errors in complex workflows and hallucinations caused by excessive context size. To address these limitations, we introduce the Performant Agentic Framework (PAF), a novel system that assists LLMs in selecting appropriate nodes and executing actions in order when traversing complex graphs. PAF combines LLM-based reasoning with a mathematically grounded vector scoring mechanism, achieving both higher accuracy and reduced latency. Our approach dynamically balances strict adherence to predefined paths with flexible node jumps to handle various user inputs efficiently. Experiments demonstrate that PAF significantly outperforms baseline methods, paving the way for scalable, real-time Conversational AI systems in complex business environments.

Large Action Models (LAMs) have revolutionized intelligent automation, but their application in healthcare faces challenges due to privacy concerns, latency, and dependency on internet access. This report introduces an ondevice, multi-agent healthcare assistant that overcomes these limitations. The system utilizes smaller, task-specific agents to optimize resources, ensure scalability and high performance. Our proposed system acts as a one-stop solution for health care needs with features like appointment booking, health monitoring, medication reminders, and daily health reporting. Powered by the Qwen Code Instruct 2.5 7B model, the Planner and Caller Agents achieve an average RougeL score of 85.5 for planning and 96.5 for calling for our tasks while being lightweight for on-device deployment. This innovative approach combines the benefits of ondevice systems with multi-agent architectures, paving the way for user-centric healthcare solutions.