Computer hacker Rui Pinto, the man behind the Football Leaks website that helped trigger the Premier League probe into Manchester City's finances, will remain under police protection, Portuguese authorities confirmed. Pinto obtained private documents that showed City broke league rules from 2009 to 2018. An independent commission found City guilty of all but one of 115 charges brought against them over breaches of Premier League financial rules. A previous resolution was nullified because Pinto had not been "duly informed of the reasons for the decision" and had not had the opportunity to challenge it, the statement added on Friday. Pinto's lawyers last week denounced irregularities in the proceedings, highlighting the real threats facing their client, who was assaulted in Lisbon last April.

Look Up Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable Selects Say More Top creators, ranked Gift Ideas For Everyone On Your List Creator Playbook In My Bag AI at School Safety Net Versus Trending Now All Series How to watch Portugal vs. Norway online for free Live stream select fixtures from the UEFA Nations League without spending anything. Joseph Green is the Global Shopping Editor for Mashable. He covers VPNs, headphones, fitness gear, dating sites, streaming, and shopping events like Black Friday and Prime Day. All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission.

Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Mashable Selects In My Bag Look Up Say More AI at School Safety Net Versus Trending Now Back to School Good Connection: Uplifting stories for a digital age All Series How to watch Denmark vs. Portugal online for free Live stream select fixtures from the UEFA Nations League without spending anything. Joseph Green is the Global Shopping Editor for Mashable. He covers VPNs, headphones, fitness gear, dating sites, streaming, and shopping events like Black Friday and Prime Day. All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission.

AI at School Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable Selects Look Up Say More Safety Net Versus Creator Playbook In My Bag Trending Now Back to School Good Connection: Uplifting stories for a digital age All Series How to watch Portugal vs. Wales online for free Live stream select fixtures from the UEFA Nations League without spending anything. Joseph Green is the Global Shopping Editor for Mashable. He covers VPNs, headphones, fitness gear, dating sites, streaming, and shopping events like Black Friday and Prime Day. All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission.

Why Do Some Soccer Players Cut the Heels Off Their Cleats? An image of Portugal forward Pedro Neto's cleats at the World Cup has reignited a practice among some soccer players: modifying their cleats to relieve heel discomfort. During this year's World Cup, one very peculiar image caught the attention of fans and commentators: Portuguese forward Pedro Neto played a match with the back of his cleats cut off, right above the heel. The modification was intended to relieve pressure on a particularly sensitive area of his foot. Although the image went viral, it's not new.

Predicting a complete spatially correlated field from sparse observations is a fundamental challenge in spatial statistics and environmental modelling. Classical interpolation methods such as Kriging rely on Gaussian process assumptions and variography, which can limit their effectiveness in non-stationary settings and require substantial domain expertise. In this work, we leverage an architecture based on convolutional neural networks (CNNs) for spatial interpolation that is trained and applied on a single partially observed field, without access to external data or prior fields. The model is supervised directly on the observed locations and learns to predict values at unobserved points on the user defined grid. Unlike Kriging, our method does not require explicit covariance modelling or variogram estimation, and it can flexibly capture local spatial patterns in a data-driven manner. This work demonstrates the potential of CNNs for single-instance spatial interpolation under sparse supervision, offering a practical alternative to classical geostatistical methods, and extending the use of CNNs to a new problem domain.

A French woman and her partner will remain in custody after allegedly abandoning her two young boys on a roadside in the south of Portugal, a court has ruled. The boys were found on Tuesday evening crying beside a road near Alcacer do Sal, about 100km (60 miles) south of Lisbon. The woman and her partner, identified by authorities as Marine R and Marc B, were arrested in Fatima on Thursday. As they were being led into court on Saturday morning, the man shouted I love you in French and the boys' mother sang. A judge subsequently ordered the pair be placed in pre-trial detention, French and Portuguese media report.

RoboCup is an international competition that promotes and advances robotics and AI through the challenges presented by its various leagues. We got the chance to sit down with Professor Manuela Veloso, one of RoboCup's founders, to find out more about how it all started, how the community has grown over the years, and the vision for the future. I think it would be very interesting to go right back to the beginning and hear how RoboCup got started. What was the initial idea, and how did it get set up? So we are talking about the mid-90s. In terms of the research in those days, it was the beginning of the internet and many AI and computer science researchers were focused on the internet, first on sophisticated search algorithms, on natural language understanding, on information retrieval, and then on software agents and machine learning applied to digital information. From what I recall, there was a smaller group of researchers who were interested in actual, physical robots, and in particular in AI and robotics.

As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that are interpretable but also trustworthy with formal guarantees. Existing XAI methods fall short: heuristic attribution techniques (e.g., LIME, Integrated Gradients) highlight influential features but offer no mathematical guarantees about decision boundaries, while formal methods verify robustness yet remain untargeted, analyzing the nearest boundary regardless of whether it represents a critical risk. In safety-critical systems, not all misclassifications carry equal consequences; confusing a "Stop" sign for a "60 kph" sign is far more dangerous than confusing it with a "No Passing" sign. We introduce ViTaX (Verified and Targeted Explanations), a formal XAI framework that generates targeted semifactual explanations with mathematical guarantees. For a given input (class y) and a user-specified critical alternative (class t), ViTaX: (1) identifies the minimal feature subset most sensitive to the y->t transition, and (2) applies formal reachability analysis to guarantee that perturbing these features by epsilon cannot flip the classification to t. We formalize this through Targeted epsilon-Robustness, certifying whether a feature subset remains robust under perturbation toward a specific target class. ViTaX is the first method to provide formally guaranteed explanations of a model's resilience against user-identified alternatives. Evaluations on MNIST, GTSRB, EMNIST, and TaxiNet demonstrate over 30% fidelity improvement with minimal explanation cardinality.