technocracy

“A follow-up to “What I Learned from Lee Kuan Yew – The Alpha Engineer Who Built a Nation” Walking the Talk In my previous piece, I explored how Lee Kuan Yew exemplified the Alpha Engineer archetype, a leader who understood systems at the deepest technical level and used that understanding to transform an entire nation. But there’s a critical principle I didn’t fully emphasize: Alpha Engineers never truly leave the engine room, regardless of the executive positions they hold. […]

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arXiv:2507.06969v4 Announce Type: replace-cross Abstract: Differentially private (DP) mechanisms are difficult to interpret and calibrate because existing methods for mapping standard privacy parameters to concrete privacy risks — re-identification, attribute inference, and data reconstruction — are both overly pessimistic and inconsistent. In this work, we use the hypothesis-testing interpretation of DP ($f$-DP), and determine that bounds on attack success can take the same unified form across re-identification, attribute inference, and data reconstruction risks. Our unified bounds are (1) […]

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Retrieval-Augmented Generation (RAG) has become a standard technique for grounding large language models in external knowledge — but the moment you move beyond plain text and start mixing in images and videos, the whole approach starts to buckle. Visual data is token-heavy, semantically sparse relative to a specific query, and grows unwieldy fast during multi-step reasoning. Researchers at Tongyi Lab, Alibaba Group introduced ‘VimRAG’, a framework built specifically to address that breakdown. The problem: linear history and compressed […]

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arXiv:2603.24629v1 Announce Type: new Abstract: Converting process sketches into executable simulation models remains a major bottleneck in process systems engineering, requiring substantial manual effort and simulator-specific expertise. Recent advances in generative AI have improved both engineering-diagram interpretation and LLM-assisted flowsheet generation, but these remain largely disconnected: diagram-understanding methods often stop at extracted graphs, while text-to-simulation workflows assume structured inputs rather than raw visual artifacts. To bridge this gap, we present an end-to-end multi-agent large language model system that […]

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Despite the success of machine learning (ML) in surrogate modeling, its use in radiation dose assessment is limited by safety-critical constraints, scarce training-ready data, and challenges in selecting suitable architectures for physics-dominated systems. Within this context, rapid and accurate plume shine dose estimation serves as a practical test case, as it is critical for nuclear facility safety assessment and radiological emergency response, while conventional photon-transport-based calculations remain computationally expensive. In this work, an interpolation-assisted ML framework was developed […]

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Hi everyone, I’ve written a short research note on GitHub where I explore an idea related to making LLMs improve their own training process by self-distribution aware analysis. The focus is not on a specific implementation, but on a general training paradigm and how models could guide what data or signals they learn from next. I’m looking for feedback or criticism. My goal is discussion and learning, not making any strong claims. If someone finds the direction interesting […]

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I’ve finished a couple of courses on RL (theoretical and hands on). I’m looking for a problem suitable for RL that is not “lunar landing” or the usual games. Is there any useful application? I’m not questioning usefulness of RL. I just can’t think of one that I can tackle submitted by /u/NoAcanthocephala4741 [link] [comments]

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arXiv:2601.15514v1 Announce Type: cross Abstract: Macroeconomic conditions influence the environments in which health systems operate, yet their value as leading signals of health system capacity has not been systematically evaluated. In this study, we examine whether selected macroeconomic indicators contain predictive information for several capacity-related public health targets, including employment in the health and social assistance workforce, new business applications in the sector, and health care construction spending. Using monthly U.S. time series data, we evaluate multiple forecasting […]

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