Measuring Train Driver Performance as Key to Approval of Driverless Trains

The European Commission has been accused of a significant rollback of digital protections following proposals to delay key aspects of the Artificial Intelligence Act and dilute data protection regulations. If implemented, these changes would allow tech companies to utilize personal data for AI model training without user consent and reduce the frequency of consent requests for online tracking.

The European Commission has initiated a Digital Markets Act (DMA) investigation into US hyperscalers, focusing on their market power in the cloud infrastructure sector. This move is part of the EU's strategy to secure a competitive digital landscape in Europe and ensure fair practices among major tech players.

The Netherlands has temporarily halted its efforts to seize control of the Chinese-owned chipmaker Nexperia, a move seen as a gesture of goodwill aimed at easing tensions in the ongoing EU-China dispute. This decision comes amid concerns over the impact on global car supply chains, which have been affected by semiconductor shortages.

The European Union has proposed updates to the General Data Protection Regulation (GDPR), which include simplifying cookie permission pop-ups. Additionally, there are plans to dilute the AI Act in response to pressure from the United States and major technology companies. This shift marks a significant change in the EU's regulatory stance towards tech giants, raising concerns about the protection of user data and the integrity of AI governance.

MajinBook is an open catalogue aimed at enhancing the use of shadow libraries like Library Genesis and Z-Library for computational social science and cultural analytics. It combines metadata from these extensive archives with structured bibliographic data from Goodreads, resulting in a high-precision corpus of over 539,000 references to English-language books from the past three centuries. The project emphasizes machine-readable quality through native EPUB files and addresses biases found in traditional datasets, while also including secondary datasets for French, German, and Spanish literatur…

MMaDA-Parallel is a new multimodal diffusion framework aimed at enhancing thinking-aware generation in AI models. It addresses performance degradation caused by error propagation in existing autoregressive approaches. The framework introduces ParaBench, a benchmark for evaluating text and image outputs, revealing that misalignment between reasoning and generated images contributes to performance issues. MMaDA-Parallel employs supervised finetuning and Parallel Reinforcement Learning to improve interaction between text and images throughout the denoising process.

Recent research highlights a new class of attacks in federated learning that compromise model interpretability without impacting accuracy. The study reveals that adversarial clients can apply small color perturbations, shifting a model's saliency maps from meaningful regions while maintaining predictions. This method, termed the Chromatic Perturbation Module, systematically creates adversarial examples by altering color contrasts, leading to persistent poisoning of the model's internal feature attributions, challenging assumptions about model reliability.

The paper discusses Zero-shot coordination (ZSC), a significant challenge in multi-agent game theory, particularly in evolving games. It emphasizes the need for agents to coordinate with previously unseen partners without fine-tuning. The study introduces Scalable Population Training (ScaPT), an efficient reinforcement learning framework that enhances zero-shot coordination by utilizing a meta-agent to manage a diverse pool of agents, addressing limitations of existing methods that focus on small populations and computational constraints.