This study develops a hierarchical Bayesian framework that integrates expert domain knowledge to quantify player-specific effects in expected goals (xG) estimation, addressing a limitation of standard models that treat all players as identical finishers. Using 9,970 shots from StatsBomb's 2015-16 data and Football Manager 2017 ratings, we combine Bayesian logistic regression with informed priors to stabilise player-level estimates, especially for players with few shots. The hierarchical model reduces posterior uncertainty relative to weak priors and achieves strong external validity: hierarchical and baseline predictions correlate at R2 = 0.75, while an XGBoost benchmark validated against StatsBomb xG reaches R2 = 0.833. The model uncovers interpretable specialisation profiles, including one-on-one finishing (Aguero, Suarez, Belotti, Immobile, Martial), long-range shooting (Pogba), and first-touch execution (Insigne, Salah, Gameiro). It also identifies latent ability in underperforming players such as Immobile and Belotti. The framework supports counterfactual "what-if" analysis by reallocating shots between players under identical contexts. Case studies show that Sansone would generate +2.2 xG from Berardi's chances, driven largely by high-pressure situations, while Vardy-Giroud substitutions reveal strong asymmetry: replacing Vardy with Giroud results in a large decline (about -7 xG), whereas the reverse substitution has only a small effect (about -1 xG). This work provides an uncertainty-aware tool for player evaluation, recruitment, and tactical planning, and offers a general approach for domains where individual skill and contextual factors jointly shape performance.

The generalization of language models (LMs) is undergoing active debates, contrasting their potential for general intelligence with their struggles with basic knowledge composition (e.g., reverse/transition curse). This paper uncovers the phenomenon of linear correlations in LMs during knowledge composition. For explanation, there exists a linear transformation between certain related knowledge that maps the next token prediction logits from one prompt to another, e.g., "X lives in the city of" $\rightarrow$ "X lives in the country of" for every given X. This mirrors the linearity in human knowledge composition, such as Paris $\rightarrow$ France. Our findings indicate that the linear transformation is resilient to large-scale fine-tuning, generalizing updated knowledge when aligned with real-world relationships, but causing hallucinations when it deviates. Empirical results suggest that linear correlation can serve as a potential identifier of LM's generalization. Finally, we show such linear correlations can be learned with a single feedforward network and pre-trained vocabulary representations, indicating LM generalization heavily relies on the latter.

An award-winning festival that combines artificial intelligence, art and cutting-edge computer scientists is putting Leicester on the map. The Art AI Festival, which is run by Professor Tracy Harwood of the Institute of Creative Technologies at De Montfort University Leicester (DMU) has been invited to be part of a network of the UK's top science festivals. The UK Science Festivals Network Association is run by the British Science Association, supported by the UK Research and Innovation and Wellcome Trust. It exists to promote science and help festivals gain new audiences by showcasing some of the best work happening today. Membership means the Art AI Festival will have the chance to work with the network to grow, be a voice for science, have access to funded projects and work with other festivals to promote best practice.

Fabrizio Poltronieri is an artist who explores the relationship technology and deep-rooted philosophical concepts, such as chance. His current artwork involves Artificial Intelligence, applying machine and deep learning techniques to create and design narratives, moving images and objects. He is a self-taught programmer who started to code during his childhood. His first degree was in Maths, he has a Master Degree in Education and Culture and holds a PhD in Semiotics from the Pontifical Catholic University of São Paulo (PUC/SP). Poltronieri is an Associate Professor and permanent member of the IOCT (Institute of Creative Technologies) at De Montfort University, Leicester, UK, supervising PhD students and teaching creative code in the Digital Arts MA.

UK workers are sabotaging and assaulting workplace robots in an attempt to stop them taking their jobs, finds study. But for some manual workers they have found their own ways of stopping the robots' rise to world domination - by confusing them. The study by De Montfort University in Leicester which looked into the use of robotics in healthcare concluded that UK workers are particularly apposed to the introduction of the intelligent machines into the work place. Compared to Norway where the study found co-working robots are often given affectionate names and welcomed. Jonathan Payne, Professor of Work, Employment and Skills, said: 'We heard stories of workers standing in the way of robots, and minor acts of sabotage - and not playing along with them.' Adding: 'The UK seems to have a problem with diffusion and take-up of technology.'

Just before the launch of Football Manager 2017 [official site], with the beta already released to the many people who preordered the game, I spoke to Sports Interactive director Miles Jacobson about the changes his team have made in this latest game in the series. We talked about AI improvements, Brexit, and whether Leicester winning the Premier League was a happy day or a sad day at Sports Interactive. With updates to the beta arriving regularly as the people playing provided feedback, commentary and complaints, Sports Interactive is a busy place around this time of year. The fortnight before launch day is an enormous playtest, in which more eyes are on the new version of the game than have been at any point during development. Jacobson seems happy to take time away from assessment of new release candidate builds to talk though.