Has Britain become an economic colony? The UK could've been a true tech leader - but it has cheerfully submitted to US dominance in a way that may cost it dear T wo and a half centuries ago, the American colonies launched a violent protest against British rule, triggered by parliament's imposition of a monopoly on the sale of tea and the antics of a vainglorious king. Today, the tables have turned: it is Great Britain that finds itself at the mercy of major US tech firms - so huge and dominant that they constitute monopolies in their fields - as well as the whims of an erratic president. Yet, to the outside observer, Britain seems curiously at ease with this arrangement - at times even eager to subsidise its own economic dependence. Britain is hardly alone in submitting to the power of American firms, but it offers a clear case study in why nations need to develop a coordinated response to the rise of these hegemonic companies.

We present an extended Greek Dialectal Dataset (GRDD+) 1that complements the existing GRDD dataset with more data from Cretan, Cypriot, Pontic and Northern Greek, while we add six new varieties: Greco-Corsican, Griko (Southern Italian Greek), Maniot, Heptanesian, Tsakonian, and Katharevusa Greek. The result is a dataset with total size 6,374,939 words and 10 varieties. This is the first dataset with such variation and size to date. We conduct a number of fine-tuning experiments to see the effect of good quality dialectal data on a number of LLMs. We fine-tune three model architectures (Llama-3-8B, Llama-3.1-8B, Krikri-8B) and compare the results to frontier models (Claude-3.7-Sonnet, Gemini-2.5, ChatGPT-5).

ABSTRACT In this paper, we propose an Optimal Transport objective for learning one-dimensional translation-equivariant systems and demonstrate its applicability to single pitch estimation. Our method provides a theoretically grounded, more numerically stable, and simpler alternative for training state-of-the-art self-supervised pitch estimators. 1. INTRODUCTION Pitch estimation is a core task in audio analysis, long studied in the speech and Music Information Retrieval (MIR) communities [1]. It involves estimating the fundamental frequency of harmonic or quasi-harmonic signals, with traditional methods relying on signal processing techniques to extract harmonicity cues [2-4], or by matching the input spectrum to that of a synthetic waveform [5]. Recently, supervised deep learning approaches leveraging large annotated datasets (such as CREPE [6]) have achieved impressive accuracy, but come with notable challenges. In particular, labeling audio with the temporal precision needed for training (typically within a few milliseconds) is labor-intensive and prone to errors.

Citiverses hold the potential to support regulatory learning by offering immersive, virtual environments for experimenting with policy scenarios and technologies. This paper proposes a science-for-policy agenda to explore the potential of citiverses as experimentation spaces for regulatory learning, grounded in a consultation with a high-level panel of experts, including policymakers from the European Commission, national government science advisers and leading researchers in digital regulation and virtual worlds. It identifies key research areas, including scalability, real-time feedback, complexity modelling, cross-border collaboration, risk reduction, citizen participation, ethical considerations and the integration of emerging technologies. In addition, the paper analyses a set of experimental topics, spanning transportation, urban planning and the environment/climate crisis, that could be tested in citiverse platforms to advance regulatory learning in these areas. The proposed work is designed to inform future research for policy and emphasizes a responsible approach to developing and using citiverses. It prioritizes careful consideration of the ethical, economic, ecological and social dimensions of different regulations. The paper also explores essential preliminary steps necessary for integrating citiverses into the broader ecosystems of experimentation spaces, including test beds, living labs and regulatory sandboxes

British soldiers will be granted new powers to shoot down drones threatening military bases. The plans, to be unveiled by Defence Secretary John Healey in a speech on Monday, are intended to allow troops to take faster, more decisive action. Four British airbases used by US forces reported mystery drone sightings last year, while drones have disrupted airspace across Europe a number of times in recent months. The new powers will only apply to military sites, but could be extended to civilian locations such as airports. Healey is set to announce the introduction of a kinetic option, first reported by the Daily Telegraph, that would enable British troops or Ministry of Defence (MoD) police to shoot drones posing a threat to a military site in the UK.

Ukrainian authorities are growing frustrated with a surge in foreign components being found in Russian drones, with a senior diplomat calling on allies to tighten sanctions controls as Moscow scales up military production. Vladyslav Vlasiuk, Ukrainian President Volodymyr Zelenskyy's special envoy on sanctions, said the European Union's sanctions regime is showing cracks as enforcement is carried out by member states rather than the bloc as a whole -- even as the Kremlin expands large-scale aerial attacks. We would like the European Union to step up exports control for European companies," Vlasiuk said in an interview in Kyiv. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

California's landmark frontier AI law to bring transparency Late last month, California became the first state in the United States to pass a law to regulate cutting-edge AI technologies. Now experts are divided over its impact. They agree that the law, the Transparency in Frontier Artificial Intelligence Act, is a modest step forward, but it is still far from actual regulation. It mandates reporting of incidents such as large-scale cyber-attacks, deaths of 50 or more people, large monetary losses and other safety-related events caused by AI models. It also puts in place whistleblower protections.

The EU's Global Gateway plan is challenging China's Belt and Road Initiative to influence Africa, by providing funding that will expand access to electricity. Nearly 600 million Africans--half the continent's population--are without electricity, largely because of the continent's limited distribution network, and Africans make up the vast majority of those worldwide without electricity access. But the European Union wants to change this. At the end of September, the president of the European Commission, Ursula von der Leyen, announced a €545 million ($636 million) investment package to support renewable energy and electrification in Africa. New EU-funded projects will include a high-voltage transmission line in Côte d'Ivoire, the electrification of hundreds of rural communities in Cameroon, the exploitation of wind and hydro energy in Lesotho, and the installation of mini-grids in remote areas of Madagascar.

The growth and permeation of artificial intelligence (AI) technologies across society has drawn focus to the ways in which the responsible use of these technologies can be facilitated through AI governance. Increasingly, large companies and governments alike have begun to articulate and, in some cases, enforce governance preferences through AI policy. Yet existing literature documents an unwieldy heterogeneity in ethical principles for AI governance, while our own prior research finds that discussions of the implications of AI policy are not yet present in the computer science (CS) curriculum. In this context, overlapping jurisdictions and even contradictory policy preferences across private companies, local, national, and multinational governments create a complex landscape for AI policy which, we argue, will require AI developers able adapt to an evolving regulatory environment. Preparing computing students for the new challenges of an AI-dominated technology industry is therefore a key priority for the CS curriculum. In this discussion paper, we seek to articulate a framework for integrating discussions on the nascent AI policy landscape into computer science courses. We begin by summarizing recent AI policy efforts in the United States and European Union. Subsequently, we propose guiding questions to frame class discussions around AI policy in technical and non-technical (e.g., ethics) CS courses. Throughout, we emphasize the connection between normative policy demands and still-open technical challenges relating to their implementation and enforcement through code and governance structures. This paper therefore represents a valuable contribution towards bridging research and discussions across the areas of AI policy and CS education, underlining the need to prepare AI engineers to interact with and adapt to societal policy preferences.

The upsurge of policies and guidelines that aim to ensure Artificial Intelligence (AI) systems are safe and trustworthy has led to a fragmented landscape of AI governance. The European Union (EU) is a key actor in the development of such policies and guidelines. Its High-Level Expert Group (HLEG) issued an influential set of guidelines for trustworthy AI, followed in 2024 by the adoption of the EU AI Act. While the EU policies and guidelines are expected to be aligned, they may differ in their scope, areas of emphasis, degrees of normativity, and priorities in relation to AI. To gain a broad understanding of AI governance from the EU perspective, we leverage qualitative thematic analysis approaches to uncover prevalent themes in key EU documents, including the AI Act and the HLEG Ethics Guidelines. We further employ quantitative topic modelling approaches, specifically through the use of the BERTopic model, to enhance the results and increase the document sample to include EU AI policy documents published post-2018. We present a novel perspective on EU policies, tracking the evolution of its approach to addressing AI governance.