Six months ago I implemented a NumPy environment for generals.io and trained an agent that hit top 20 on human leaderboards. I reached 5k fps with that setup. In the last couple of days I rewrote everything in JAX with help from opus4.5 (here we go again) and got 1.4M FPS on single H200, which is a 300x speedup! I’m confident that with so much more fps going super-human is much more attainable! For those interested in coding […]

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arXiv:2603.21610v1 Announce Type: cross Abstract: Existing machine learning frameworks for compliance monitoring — Markov Logic Networks, Probabilistic Soft Logic, supervised models — share a fundamental paradigm: they treat observed data as ground truth and attempt to approximate rules from it. This assumption breaks down in rule-governed domains such as taxation or regulatory compliance, where authoritative rules are known a priori and the true challenge is to infer the latent state of rule activation, compliance, and parametric drift from […]

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Spatio-temporal forecasting is fundamental to intelligent systems in transportation, climate science, and urban planning. However, training deep learning models on the massive, often redundant, datasets from these domains presents a significant computational bottleneck. Existing solutions typically focus on optimizing model architectures or optimizers, while overlooking the inherent inefficiency of the training data itself. This conventional approach of iterating over the entire static dataset each epoch wastes considerable resources on easy-to-learn or repetitive samples. In this paper, we explore […]

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arXiv:2602.15249v1 Announce Type: new Abstract: This study examines the geographical distribution of Artificial Intelligence (AI) research production across European regions at the NUTS-3 level for the period 2015-2024. Using bibliometric data from Clarivate InCites and the Citation Topics classification system, we analyze two hierarchical levels of thematic aggregation: Electrical Engineering, Electronics & Computer Science (Macro Citation Topic 4) and Artificial Intelligence & Machine Learning (Meso Citation Topic 4.61). We calculate the Relative Specialization Index (RSI) and Relative Citation […]

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arXiv:2511.15315v2 Announce Type: replace Abstract: Bayesian Optimization is critically vulnerable to extreme outliers. Existing provably robust methods typically assume a bounded cumulative corruption budget, which makes them defenseless against even a single corruption of sufficient magnitude. To address this, we introduce a new adversary whose budget is only bounded in the frequency of corruptions, not in their magnitude. We then derive RCGP-UCB, an algorithm coupling the famous upper confidence bound (UCB) approach with a Robust Conjugate Gaussian Process […]

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arXiv:2601.16458v1 Announce Type: new Abstract: Open-source ecosystems such as NPM and PyPI are increasingly targeted by supply chain attacks, yet existing detection methods either depend on fragile handcrafted rules or data-driven features that fail to capture evolving attack semantics. We present IntelGuard, a retrieval-augmented generation (RAG) based framework that integrates expert analytical reasoning into automated malicious package detection. IntelGuard constructs a structured knowledge base from over 8,000 threat intelligence reports, linking malicious code snippets with behavioral descriptions and […]

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Five years ago, when I was thinking about the choice of my Master’s degree, I remember asking many people for advice. I was very grateful to my friends, as well as random people on LinkedIn and Reddit, who helped me make many important decisions. Fast forward to today. Having graduated from the university almost two years ago, I have pretty fresh and current experience of being a “young professional” in the tech industry. Now I am honoured to […]

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