World's biggest company Nvidia stuns Wall Street as it gives biggest clue yet to state of US economy'Triple whammy' will decide if Wall Street crashes within the next day A senior White House official has told me the REAL threat to Trump. Epstein is a humiliating distraction. But he's losing grip fast... this could be fatal: ANDREW NEIL Secret reasons Ronaldo was desperate to meet Trump... and what he REALLY wants from the president Melania Trump delivers'dystopian' speech to troops sparking meltdown Kevin Spacey reveals he is currently homeless and'living in hotels' as he admits his financial situation is'not great' - two years after he was cleared of sexual assault allegations Female health inspector sparks internet firestorm over video of her pouring BLEACH all over unlicensed taco vendor's food Haunting final words of boy, 12, 'tortured by lesbian wives' until he shrunk and died Nancy Mace leaks wild sexts about Republican colleague: 'You will be a good girl' Full-faced Britney Spears looks unrecognizable as she carries Champagne flute from wine bar, then drives away... AGAIN: Family speak out on'nightmare' spiral'The Mamdani effect' goes berserk: Desperate New Yorkers fight over multimillion-dollar homes outside city... prices jump 24% in five DAYS All the scandals of the 1939 Wizard of Oz: How Judy Garland was drugged and starved in an'iron corset', actors DIED and one had an eyelid burned off... not to mention the drunken orgies SARAH VINE: Meghan the Domestic Goddess is back - and she's in full festive flow. Meghan Markle goes barefaced as she poses on cover of Harper's Bazaar magazine Doctors warn'overprescribed' medical test use has DOUBLED despite raising the risk of cancer by three times Deep red state of Utah will see its population swell by TWO MILLION by 2065 thanks to'net-in migration' READ MORE: Can you spot the AI-generated faces? Britain boasts some of the best authors in the world - but they could soon be replaced by AI, a disturbing report reveals.

Evaluating large language models (LLMs) on question answering often relies on static benchmarks that reward memorization and understate the role of retrieval, failing to capture the dynamic nature of world knowledge. We present LiveSearchBench, an automated pipeline for constructing retrieval-dependent benchmarks from recent knowledge updates. Our method computes deltas between successive Wikidata snapshots, filters candidate triples for quality, and synthesizes natural-language questions at three levels of reasoning difficulty, each guaranteed to admit a unique, verifiable answer through SPARQL validation. The pipeline is fully automated, scalable across time, and minimizes human intervention, enabling continual regeneration of temporally grounded benchmarks. Experiments show a pronounced performance drop when models confront facts that post-date pretraining, with the gap most salient on multi-hop queries. Retrieval augmented methods and larger, instruction-tuned models provide partial gains but fail to close this recency gap. By design, LiveSearchBench shifts evaluation from static memorization toward tasks that require up-to-date retrieval and reasoning, offering a foundation for systematic, long-term assessment of LLMs under evolving knowledge.

AI bot ChatGPT has named its ultimate Euros line-up – but football fans will be shocked by some very controversial omissions. MailOnline asked for the'best Euros squad of all time' made of 11 players who have starred in at least one UEFA European Championship since the first in 1960. But shockingly, the AI tool did not name a single British player – not even on the subs bench. This is despite famous Euro performances in the past from the likes of Wayne Rooney, Alan Shearer, Paul Gascoigne and Gareth Bale. Among the stars included are German legend Franz Beckenbauer, France's Thierry Henry and Zinedine Zidane, as well as Cristiano Ronaldo, considered one of the greatest players of all time. MailOnline asked ChatGPT to name its ultimate Euros line-up - and it didn't name a single British player, not even on the subs bench OpenAI's free tool ChatGPT has been trained on troves of data to interact with human users conversationally.

This paper introduces an innovative application of Large Event Models (LEMs), akin to Large Language Models, to the domain of soccer analytics. By learning the "language" of soccer - predicting variables for subsequent events rather than words LEMs facilitate the simulation of matches and offer various applications, including player performance prediction across different team contexts. We focus on fine-tuning LEMs with the WyScout dataset for the 2017-2018 Premier League season to derive specific insights into player contributions and team strategies. Our methodology involves adapting these models to reflect the nuanced dynamics of soccer, enabling the evaluation of hypothetical transfers. Our findings confirm the effectiveness and limitations of LEMs in soccer analytics, highlighting the model's capability to forecast teams' expected standings and explore high-profile scenarios, such as the potential effects of transferring Cristiano Ronaldo or Lionel Messi to different teams in the Premier League. This analysis underscores the importance of context in evaluating player quality. While general metrics may suggest significant differences between players, contextual analyses reveal narrower gaps in performance within specific team frameworks.

What do Taylor Swift, Andrew Tate and Robert Oppenheimer all have in common? They were the most searched articles on Wikipedia this year. The platform shared a fascinating report revealing the topics most interested people in English-speaking countries. Collectively, we racked up more than 84 billion views on Wikipedia this year. The site's page for ChatGPT was the top article, with more than 49 million views, following its breakout year that sparked curiosity and concern worldwide. Curiosity and concern also played a part in the second most viewed Wikipedia article of the year: 'Deaths in 2023' ' which HAD over 42 million views.

From a chilled glass of Rooh Afza to the scrumptious pakoras and dates, the Holy month of Ramadan is synonymous to a delicious Iftaar spread. Abstaining from taking even a drop of water throughout the day and then breaking your fast with some delicious food in the evening is a wholesome experience and holds great significance. During Iftar, most of us enjoy whatever we love and eat enough to fill up our energy bars. Heading to the streets lined with vendors is common during Ramadan. But have you ever seen celebrities serving Iftar meals on streets?

Drawing on the expertise of rights holders, broadcasters and technology providers from across the sports ecosystem, SportsPro's latest Insider Series event returned to the theme of over-the-top (OTT) and broadcast, providing a wealth of insight into the technology that the industry is tapping into to put live sports on our screens. With much to unpack, SportsPro writers select five key takeaways from across the two days, covering piracy, machine learning and remote production. Cameron Andrews, BeIN Media Group's legal director for anti-piracy, said sports rights holders "were slow" to react to the incursion of BeoutQ, but described the Saudi bootlegging operation as "a very good case study" for piracy "and the impact it can have". "I think some rights owners are certainly aware of that and are very engaged," he said. "But unfortunately I think a lot of other rights owners are still quite some way behind." The emergence of BeoutQ has shone a light on the threat piracy poses to the sports industry, and Andrews called on rights owners, such as leagues and governing bodies, to come together to tackle the issue.

Pointer generator networks have been used successfully for abstractive summarization. Along with the capability to generate novel words, it also allows the model to copy from the input text to handle out-of-vocabulary words. In this paper, we point out two key shortcomings of the summaries generated with this framework via manual inspection, statistical analysis and human evaluation. The first shortcoming is the extractive nature of the generated summaries, since the network eventually learns to copy from the input article most of the times, affecting the abstractive nature of the generated summaries. The second shortcoming is the factual inaccuracies in the generated text despite grammatical correctness. Our analysis indicates that this arises due to incorrect attention transition between different parts of the article. We propose an initial attempt towards addressing both these shortcomings by externally appending traditional linguistic information parsed from the input text, thereby teaching networks on the structure of the underlying text. Results indicate feasibility and potential of such additional cues for improved generation.

The trio is considered the best players in the world right now with Messi and Neymar playing alongside each other for Barcelona from 2013 to 2017 in a spell that saw the club win two La Liga titles, three Copa del Reys, one Champions League crown and the FIFA Club World Cup. However, Neymar shockingly made the move from Barcelona to Paris Saint-Germain last summer after the oil-rich Ligue 1 side activated his €222 million ($273.7 million) release clause in what is still the world record transfer deal. It is highly believed that the Brazilian did not move for money but rather, the chance to play for a side built around him rather than Messi as with his current injury aside, he has flourished this season with 29 goals and 19 assists in 30 games in all competitions with PSG requiring just four points from their last six games to seal a fifth Ligue 1 title in six years. But, there are rumors that the 25-year-old is unhappy in Paris with speculation rising that he could return to La Liga for Barcelona or even rivals Real Madrid where he would be teammates with Ronaldo. There were also reports that Zahavi, who acted as an intermediary for Neymar's move last summer, accompanied a PSG delegation to Brazil last month to check on his injury and determine his value for another potential transfer.

Whether you call it soccer or football, this sport is the world's favorite to watch and play. Thanks to Hugo Mathien who compiled, cleaned, and shared a dataset of stats on European professional football on Kaggle, it can become a data scientist's favorite playground, too. Among other data points, the database includes 25,000 matches from 2008 to 2011, 10,000 players from 11 countries, and betting odds from up to 10 providers. This impressive collection of data allows Kagglers test their machine learning techniques by building models predicting match outcomes (can you beat the bookies?) and find insights through data visualization and storytelling. In this interview, Hugo explains how he pulled data from a number of sources using Python's Scrapy and overcame data integrity issues with manual effort to build this incredible dataset for Kagglers to enjoy.