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Quantum key distribution (QKD) networks require relaying when distant key management entities share no direct quantum link. Most relay strategies, however, rely on centralized control or globally maintained routing state. This paper asks whether useful security and efficiency can still be obtained with topology-oblivious stochastic forwarding. It studies the security-overhead trade-off in a model in which fragmented key material is relayed via random-walk variants and reconstructed under privacy amplification. Under a restricted model with at most one compromised […]

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:::info Design, implementation, and benchmarks of a native BM25 index for Postgres. Now generally available to all Tiger Cloud customers and freely available via open source. ::: If you have used Postgres’s built-in ts_rank for full-text search at any meaningful scale, you already know the limitations. Ranking quality degrades as your corpus grows. There is no inverse document frequency, so common words carry the same weight as rare ones. There is no term frequency saturation, so a document that mentions […]

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TLS 1.3 zero-round-trip-time (0-RTT) resumption reduces reconnection latency by allowing clients to transmit early application data using pre-shared keys (PSK) derived from previously established session tickets. This mechanism is pivotal for latency-sensitive web services, API gateways, and IoT applications. However, the cryptographic foundations of current session tickets—symmetric keys derived from classical X25519 key exchange—are fundamentally vulnerable to Harvest-Now-Decrypt-Later (HNDL) quantum attacks: an adversary capturing session ticket exchanges today can retroactively decrypt PSKs and all 0-RTT early data once […]

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The Two-Envelope Problem (TEP) is revisited to argue that the standard evaluation of expected returns relies on spurious probabilities arising from a misuse of formal probability theory. The source of the problem is the ex post framing of two identical envelopes, X and Y, one containing twice as much money as the other, after one envelope, say X, has been selected and its content X=x observed. The value x is then used to define Y in terms of […]

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In this project, we study the optimization methods impacts on deep learning tasks, where we particularly focus on adaptive learning rate optimizers (e.g., AdaGrad, RMSProp, and Adam) and describe them, stating their strengths, weaknesses, and scenarios where they excel or underperform. We employ an experimental approach to analyze their performance, generalization, computational efficiency, and hyperparameter sensitivity. The study compares the performance of adaptive optimizers against a traditional method (SGD) and a non-tuning machine learning model (LDA). Our empirical […]

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Effective management of infectious healthcare waste at the Military Medical Academy (VMA) depends on reliable forecasting in order to ensure adequate treatment capacity (e.g., sterilization facilities), optimize logistics, maintain regulatory compliance, and minimize environmental impact. However, conventional statistical approaches often struggle to capture the complex and heterogeneous patterns of waste generation ob-served across clinical departments with different medical specializations. The aim of this study is to develop and comparatively evaluate six models for predict-ing annual infectious waste generation […]

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I examine the technology of machine learning from the perspective of rhetoric, which is simply the art of persuasion. Rather than being a neutral and "objective" way to build "world models" from data, machine learning is (I argue) inherently rhetorical. I explore some of its rhetorical features, and examine one pervasive business model where machine learning is widely used, "manipulation as a service."

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Mont Fleuri, Seychelles, April 7th, 2026/Chainwire/–Whale.io is announcing the launch of its AI Agent MCP (Model Context Protocol) – the first of its kind in the online crypto casino space – alongside a two-week campaign built entirely around it. The campaign kicks off soon and is aimed squarely at developers, builders, and the vibe coding community who’ve been quietly wondering what their agents are capable of. Now their AI agents get a seat at the table. Overview of […]

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We study offline learning in KL-regularized two-player zero-sum games, where policies are optimized under a KL constraint to a fixed reference policy. Prior work relies on pessimistic value estimation to handle distribution shift, yielding only $widetilde{mathcal{O}}(1/sqrt n)$ statistical rates. We develop a new pessimism-free algorithm and analytical framework for KL-regularized games, built on the smoothness of KL-regularized best responses and a stability property of the Nash equilibrium induced by skew symmetry. This yields the first $widetilde{mathcal{O}}(1/n)$ sample complexity […]

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I. The Push America did not misplace Anthropic. It pushed it. For years the relationship looked like a success story. Anthropic was the first major AI lab cleared to handle classified material. Pentagon contracts, intelligence community access, armed services integration. Claude was, and remains, the only AI model approved for use on Pentagon classified networks. That is not a small thing. Then it refused two things. No autonomous weapons. No mass domestic surveillance. Prior administrations had disagreed and […]

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