Great Britain's Olympic and Paralympic teams are going to need to harness artificial intelligence and work together more closely in order to continue their success at recent Games, says UK Sport chairman Nick Webborn. In his first interview since taking up the role, the head of the elite sport funding agency told BBC Sport: We've been a really successful nation, and to maintain that position or to even go higher, we're going to have to do things differently. It's about how we think smarter now, how we utilise things like AI appropriately in sport, how we work together as different sports bodies, rather than in silos. I think we're now in a frame of mind where we're united and moving together, that sharing of information between sports is happening much more than ever before. And we're going to need to do that to maintain ourselves in our position on the medal table.

President Trump's state visit to the UK secured $350 billion in US tech investments to strengthen Britain's AI capabilities and counter Chinese influence.

The suspect in Charlie Kirk's assassination has been captured, FBI director Kash Patel announced MSNBC sparks outrage for'disgusting' Charlie Kirk comments following Utah shooting Tragedy as Charlie Kirk's wife left behind with two young children after conservative activist is fatally shot A DEI mayor, an inconvenient crime and video they never wanted you to see: MAUREEN CALLAHAN knows why the Left has sympathy for that killer... but none for his victim Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season We only had one symptom we dismissed... but then we were diagnosed with the rarest form of melanoma Soft-touch prosecutor let felon walk free... before crook'slit Auburn professor's throat in random attack' I tried the 30 cent'miracle chill pill' before a big event.. now I'm taking it for everything Donald Trump and House Republicans lead prayers for Charlie Kirk's family after conservative star is fatally shot Prince Harry says his father King Charles is'great' following their first meeting in 19 months... which was over a cup of tea and just 55 minutes long Liberal media defends thug who killed Ukrainian woman in cold blood: 'This man was hurting' Knifeman accused of stabbing Ukrainian refugee to death gives chilling reason for the attack... as he speaks for the first time from jail on the murder that shocked America Fox News reveals new lineup and elevates star White House reporter who's sparred with Trump Horrific new details of passenger injuries after they were'thrown' around Delta flight during'severe turbulence' Antarctica's'Doomsday Glacier' is on the verge of COLLAPSING: Huge ice sheet the size of Great Britain could cause global sea levels to rise by 2 FEET, study warns READ MORE: 'Doomsday Glacier' melting'much faster' than previously thought With the potential to cause sea levels across the planet to rise, it's no wonder the Thwaites Glacier has earned the nickname the'Doomsday Glacier.' Now, scientists have revealed concerning findings about how and when the glacier could collapse. Researchers from the British Antarctic Survey (BAS) used underwater robots to take new measurements of the glacier, which is the same size as Great Britain. The data indicates that the Thwaites Glacier and much of the West Antarctic Ice Sheet could be lost entirely by the 23rd century. Worryingly, if it collapses entirely, the experts say global sea levels would rise by two feet (65cm) - plunging huge areas underwater. With the potential to cause seas across the planet to rise, it's no wonder the Thwaites Glacier has earned the nickname the'Doomsday Glacier' The Thwaites Glacier is roughly 74.5 miles (120km) across - the same size as Great Britain or Florida - making it the widest glacier on the planet Ice shelf connected to Antarctic's doomsday glacier is CRACKING The Thwaites Glacier is roughly 74.5 miles (120km) across - the same size as Great Britain or Florida.

The recent introduction of multimodal large language models (MLLMs) combine the inherent power of large language models (LLMs) with the renewed capabilities to reason about the multimodal context. The potential usage scenarios for MLLMs significantly outpace their text-only counterparts. Many recent works in visualization have demonstrated MLLMs' capability to understand and interpret visualization results and explain the content of the visualization to users in natural language. In the machine learning community, the general vision capabilities of MLLMs have been evaluated and tested through various visual understanding benchmarks. However, the ability of MLLMs to accomplish specific visualization tasks based on visual perception has not been properly explored and evaluated, particularly, from a visualization-centric perspective. In this work, we aim to fill the gap by utilizing the concept of visualization literacy to evaluate MLLMs. We assess MLLMs' performance over two popular visualization literacy evaluation datasets (VLAT and mini-VLAT). Under the framework of visualization literacy, we develop a general setup to compare different multimodal large language models (e.g., GPT4-o, Claude 3 Opus, Gemini 1.5 Pro) as well as against existing human baselines. Our study demonstrates MLLMs' competitive performance in visualization literacy, where they outperform humans in certain tasks such as identifying correlations, clusters, and hierarchical structures.

This study harnesses the predictive capabilities of Long Short-Term Memory (LSTM) networks to analyse and predict road traffic accidents in Great Britain. It addresses the challenge of traffic accident forecasting, which is paramount for devising effective preventive measures. We utilised an extensive dataset encompassing reported collisions, casualties, and vehicles involvements from 1926 to 2022, provided by the Department for Transport (DfT). The data underwent stringent processing to rectify missing values and normalise features, ensuring robust LSTM network input.

Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the fundamental drivers of electricity load and increasing the complexity of load modelling and forecasting. We address this challenge in two ways. First, our setting is adaptive; our models take into account the most recent observations available, yielding a forecasting strategy able to automatically respond to changes in the underlying process. Second, we consider probabilistic rather than point forecasting; indeed, uncertainty quantification is required to operate electricity systems efficiently and reliably. Our methodology relies on the Kalman filter, previously used successfully for adaptive point load forecasting. The probabilistic forecasts are obtained by quantile regressions on the residuals of the point forecasting model. We achieve adaptive quantile regressions using the online gradient descent; we avoid the choice of the gradient step size considering multiple learning rates and aggregation of experts. We apply the method to two data sets: the regional net-load in Great Britain and the demand of seven large cities in the United States. Adaptive procedures improve forecast performance substantially in both use cases for both point and probabilistic forecasting.

Social science studies dealing with control in networks typically resort to heuristics or describing the static control distribution. Optimal policies, however, require interventions that optimize control over a socioeconomic network subject to real-world constraints. We integrate optimisation tools from deep-learning with network science into a framework that is able to optimize such interventions in real-world networks. We demonstrate the framework in the context of corporate control, where it allows to characterize the vulnerability of strategically important corporate networks to sensitive takeovers, an important contemporaneous policy challenge. The framework produces insights that are relevant for governing real-world socioeconomic networks, and opens up new research avenues for improving our understanding and control of such complex systems.

Video games provided a diversion during the coronavirus pandemic. With life opening up, do games retain the same commitment of time and money or could their importance wane? Some answers could come over the next few days during the Electronic Entertainment Expo (E3). The annual video game industry event, which was cancelled last year, will be a four-day online event beginning Saturday. Fans can sign up and see the schedule at E3Expo.com.

Predicting the weather can be a frustratingly imprecise science. The weather app on your phone is pretty good at forecasting if it's likely to rain at some point during a given day, but much less helpful if you want to know if there's going to be a downpour in central London at 3 pm this Sunday. If you absolutely have to stay dry, you're best off keeping an umbrella with you or staying inside. This story originally appeared on WIRED UK. For most people, not knowing what the weather is going to do in the next hour is a minor inconvenience.

Poland still bears the scars from thousands of bombs that hit the nation in WWII – and a new map has uncovered 6,000 of the impact sites. Researchers at the University of Silesia used LIDAR technology to map the Koźle Basin, allowing them to peer through vegetation and see impact sites across and deep within the ground. The craters ranged in size from 16 to 49 feet in diameter, with some parts found with up to 30 craters in just one acre of land. The craters are a reminder of the historical event, but the impact sites have also intertwined with nature over the past 75 years, turning into bodies of water and homes for wildlife. The bombs were dropped by Allied planes above Koźle Basin, which at the time of WWII was occupied by Nazi soldiers and home to a number of their fuel production plants.