Age: Ted started in 1984. And has Ted been talking ever since? I know, and they do the inspirational online talks. Correct, under the slogan "Ideas change everything". She was talking at the Hay festival, in Wales.

Police believe live facial recognition cameras may become "commonplace" in England and Wales, according to internal documents, with the number of faces scanned having doubled to nearly 5m in the last year. A joint investigation by the Guardian and Liberty Investigates highlights the speed at which the technology is becoming a staple of British policing. Major funding is being allocated and hardware bought, while the British state is also looking to enable police forces to more easily access the full spread of its image stores, including passport and immigration databases, for retrospective facial recognition searches. Live facial recognition involves the matching of faces caught on surveillance camera footage against a police watchlist in real time, in what campaigners liken to the continual finger printing of members of the public as they go about their daily lives. Retrospective facial recognition software is used by the police to match images on databases with those caught on CCTV and other systems.

Detecting and segmenting salient objects from given image scenes has received great attention in recent years. A fundamental challenge in training the existing deep saliency detection models is the requirement of large amounts of annotated data. While gathering large quantities of training data becomes cheap and easy, annotating the data is an expensive process in terms of time, labor and human expertise. To address this problem, this paper proposes to learn the effective salient object detection model based on the manual annotation on a few training images only, thus dramatically alleviating human labor in training models. To this end, we name this task as the few-cost salient object detection and propose an adversarial-paced learning (APL)-based framework to facilitate the few-cost learning scenario. Essentially, APL is derived from the self-paced learning (SPL) regime but it infers the robust learning pace through the data-driven adversarial learning mechanism rather than the heuristic design of the learning regularizer. Comprehensive experiments on four widely-used benchmark datasets demonstrate that the proposed method can effectively approach to the existing supervised deep salient object detection models with only 1k human-annotated training images. The project page is available at https://github.com/hb-stone/FC-SOD.

And, as AI gets more advanced, so do the resurrections. Most recently, Stacey Wales used AI to generate a video of her late brother, Christopher Pelkey, to address the courtroom at the sentencing hearing for the man who killed him in a road rage incident in Chandler, Arizona. According to NPR, its the first time AI has ever been used in this way. "He doesn't get a say. He doesn't get a chance to speak," Wales told NPR, referring to her brother.

Sahan Hewage Wewelwala School of Computing Informatics Institute of Technology Colombo 06, Sri Lanka sahanwewelwala@gmail.com T.G.D.K. Sumanathilaka Department of Computer Science Swansea University Swansea, Wales, United Kingdom deshankoshala@gmail.com Abstract -- This research presents a hybrid emotion recognition system integrating advanced Deep Learning, Natural Language Processing (NLP), and Large Language Models (LLMs) to analyze audio and textual data for enhancing customer interactions in contact centers. By combining acoustic features with textual sentiment analysis, the system achieves nuanced emotion detection, addressing the limitations of traditional approaches in understanding complex emotional states. Rigorous testing on diverse datasets demonstrates the system's robustness and accuracy, highlighting its potential to transform customer service by enabling personalized, empathetic interactions and improving operational efficiency. This research establishes a foundation for more intelligent and human - centric digital communication, redefining customer service standards. The capacity to identify and comprehend emotions effectively is an essential element of human - computer interaction, especially in spoken and written communication.

The prevalence of Vision-Language Models (VLMs) raises important questions about privacy in an era where visual information is increasingly available. While foundation VLMs demonstrate broad knowledge and learned capabilities, we specifically investigate their ability to infer geographic location from previously unseen image data. This paper introduces a benchmark dataset collected from Google Street View that represents its global distribution of coverage. Foundation models are evaluated on single-image geolocation inference, with many achieving median distance errors of <300 km. We further evaluate VLM "agents" with access to supplemental tools, observing up to a 30.6% decrease in distance error. Our findings establish that modern foundation VLMs can act as powerful image geolocation tools, without being specifically trained for this task. When coupled with increasing accessibility of these models, our findings have greater implications for online privacy. We discuss these risks, as well as future work in this area.

South Wales Police have revealed plans to deploy live facial recognition cameras in Cardiff during this year's Six Nations rugby internationals. The cameras will be placed at'key points' across the city centre, and will alert officers to anyone who is on a predetermined watchlist. The force claims that the cameras will help to'keep visitors safe'. 'The expansion of facial recognition cameras around the city centre really enhances our ability to keep visitors safe from harm,' said Trudi Meyrick, Assistant Chief Constable. 'Our priority is to keep the public safe and this technology helps us achieve that.'

Drones have become a "threat to national security", the prisons watchdog has said, after a surge in the amount of weapons and drugs flown into high-security jails. Charlie Taylor, the chief inspector of prisons, called for urgent action from Whitehall and the police after inquiries found that terrorism suspects and criminal gangs could escape or attack guards because safety had been "seriously compromised". His demands follow inspections at two category A prisons holding some of England and Wales's most dangerous inmates. HMP Manchester and HMP Long Lartin in Worcestershire had thriving illicit economies selling drugs, mobile phones and weapons, and basic anti-drone security measures such as protective netting and CCTV had been allowed to fall into disrepair, inspectors found. In a report released on Tuesday, Taylor said the police and prison service had "in effect ceded the airspace above two high-security prisons to organised crime gangs" despite knowing they were holding "extremely dangerous prisoners".

This paper presents TopoFormer, a novel hybrid deep learning architecture that integrates transformer-based encoders with convolutional long short-term memory (ConvLSTM) layers for the precise prediction of topographic beach profiles referenced to elevation datums, with a particular focus on Mean Low Water Springs (MLWS) and Mean Low Water Neaps (MLWN). Accurate topographic estimation down to MLWS is critical for coastal management, navigation safety, and environmental monitoring. Leveraging a comprehensive dataset from the Wales Coastal Monitoring Centre (WCMC), consisting of over 2000 surveys across 36 coastal survey units, TopoFormer addresses key challenges in topographic prediction, including temporal variability and data gaps in survey measurements. The architecture uniquely combines multi-head attention mechanisms and ConvLSTM layers to capture both long-range dependencies and localized temporal patterns inherent in beach profiles data. While all models demonstrated strong performance, TopoFormer achieved the lowest mean absolute error (MAE), as low as 2 cm, and provided superior accuracy in both in-distribution (ID) and out-of-distribution (OOD) evaluations. Accurate topographic measurements are essential for coastal applications such as flood risk assessment, erosion monitoring, habitat mapping, and navigation safety.

But Google Maps has been causing chaos for some shoppers after pranksters set up a'phantom' Aldi in the middle of the Welsh countryside. The small village of Cyffylliog has been inundated with an'endless stream' of confused shoppers looking for somewhere to buy their groceries. Following Google's directions actually brought them to an empty field on a remote farm tens of miles away from the nearest supermarket. While it might have been added as a joke, the fake Aldi has since led to chaos for this small community as deliveries have begun to arrive in search of the non-existent supermarket. The misguided prank has even led to real Aldi deliveries arriving on one farmer's doorstep and becoming stuck on the narrow lanes.