technocracy

arXiv:2603.08765v1 Announce Type: new Abstract: This paper studies a coupled two-dimensional Navier–Stokes–Cahn–Hilliard phase-field model augmented by a transported auxiliary field, and develops a continuous data assimilation (CDA) framework for recovering its trajectories from coarse-in-space observations. We formulate a nudging-based CDA system for the coupled NSCH–auxiliary-field model, in which coarse measurements are incorporated through a general linear observation operator. The observation mechanism is described abstractly by an interpolant satisfying an $H^{2}$-type approximation property, which is compatible with coarse spatial […]

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Introduction Disclaimer: This article is a cross post from Pytorch Medium Blog Post. One of the most exciting advancements, that has pushed the frontier of the Artificial Intelligence (AI) in recent years, is Deep Reinforcement Learning (DRL). DRL belongs to the family of machine learning algorithms. It assumes that intelligent machines can learn from their actions similar to the way humans learn from experience. Over the recent years we could witness some impressive real-world applications of DRL. The […]

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arXiv:2602.24165v1 Announce Type: cross Abstract: Hypothesis testing in singular statistical models is often regarded as inherently problematic due to non-identifiability and degeneracy of the Fisher information. We show that the fundamental obstruction to testing in such models is not singularity itself, but the formulation of hypotheses on non-identifiable parameter quantities. Testing is inherently a problem in distribution space: if two hypotheses induce overlapping subsets of the model class, then no uniformly consistent test exists. We formalize this overlap […]

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Scientific paper generation requires document-level planning and factual grounding, but current large language models, despite their strong local fluency, often fail in global structure, input coverage, and citation consistency. We present a reinforcement learning framework that casts scientific outline construction as a long-horizon planning problem over hierarchical document structures. Our approach models edit evolving outlines through structured actions, enabling the system to incrementally build a complete scientific manuscript. To support effective and stabilize learning,we introduce a two-stage optimization […]

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arXiv:2602.22237v1 Announce Type: new Abstract: Distributed storage architectures are foundational to modern cloud-native infrastructure, yet a critical operational bottleneck persists within disaster recovery (DR) workflows: the dependence on content-based cryptographic hashing for data identification and synchronization. While hash-based deduplication is effective for storage efficiency in steady-state operation, it becomes a systemic liability during failover and failback events when hash indexes are stale, incomplete, or must be rebuilt following a crash. This paper precisely characterizes the operational conditions under […]

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arXiv:2601.20994v1 Announce Type: new Abstract: Neural scaling laws describe how language model loss decreases with parameters and data, but treat architecture as interchangeable–a billion parameters could arise from a shallow-wide model (10 layers & 8,192 hidden dimension) or a deep-narrow one (80 layers & 2,048 hidden dimension). We propose architecture-conditioned scaling laws decomposing this dependence, finding that optimal depth scales as D* ~ C^0.12 while optimal width scales as W* ~ C^0.34, meaning width should grow 2.8x faster […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The Long Now of the Web: Inside the Internet Archive’s Fight Against Forgetting By @zbruceli [ 18 Min read ] A deep dive into the Internet Archive’s custom tech stack. Read More. Why Kubernetes Outages Are Usually Human Failures, Not Platform Bugs By @davidiyanu […]

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Independent journalists, human rights documentarians, and at-risk publishers overwhelmingly operate on shared-host WordPress installations nfrastructure they do not control and cannot audit. Existing tamper-evident publishing solutions require dedicated servers, compiled native libraries, or HSM-backed key storage, placing them beyond reach of the population most exposed to infrastructure-level content suppression. We present ArchivioMD, a cryptographic content integrity system deployable on shared-host PHP 7.4+ without native extensions, root access, or Composer dependencies. ArchivioMD combines four composable integrity layers: Deterministic content […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## 6 Ways to Use a Crypto Exchange Aggregator and Save on Swaps By @swapzone [ 7 Min read ] Maximize your crypto swaps! Learn 6 ways an exchange aggregator saves you money. Find the best rates on Bitcoin, Ethereum, & other cryptocurrencies on DEXs. […]

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arXiv:2603.08760v1 Announce Type: new Abstract: This paper contributes to the nascent debate around safety cases for frontier AI systems. Safety cases are structured, defensible arguments that a system is acceptably safe to deploy in a given context. Historically, they have been used in safety-critical industries, such as aerospace, nuclear or automotive. As a result, safety cases for frontier AI have risen in prominence, both in the safety policies of leading frontier developers and in international research agendas proposed […]

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