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Every time I see ‘exactly-once semantics’ in a product README, I add a small mental asterisk. Not because the claim is false (it’s often technically accurate), but because it means something much more specific than most people assume when they first encounter it. I spent the better part of a sprint in our banking platform trying to diagnose why we had duplicate payment records in our Delta Lake tables despite using Spark Structured Streaming with checkpointing enabled. We […]

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As part of our continued collaboration with Anthropic, we had the opportunity to apply an early version of Claude Mythos Preview to Firefox. This week’s release of Firefox 150 includes fixes for 271 vulnerabilities identified during this initial evaluation. […] Our experience is a hopeful one for teams who shake off the vertigo and get to work. You may need to reprioritize everything else to bring relentless and single-minded focus to the task, but there is light at […]

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Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by high heterogeneity of clinical progression and limited accuracy of traditional prognostic approaches. Predicting the transition to an active disease phase is critical for timely adjustment of disease-modifying therapy and reduction of disability risk. Three deep learning architectures were developed (ResNet3D, PretrainedResNet2D, and ResNeXt) for predicting MS activity within a one-year horizon using longitudinal multimodal data comprising T1-weighted MRI volumes (50 axial slices, 128×128 […]

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Cross-sectional stock ranking is a fundamental task in quantitative investment, relying on both temporal modeling of individual stocks and the capture of inter-stock dependencies. While existing deep learning models leverage graph-based approaches to enhance ranking accuracy by propagating information over relational graphs, they suffer from a key challenge: crosstalk, namely unintended information interference across predictive factors. We identify two forms of crosstalk: temporal-scale crosstalk, where trends, fluctuations, and shocks are entangled in a shared representation and non-transferable local […]

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The integrity of scientific literature depends critically on accurate citations, yet miscitation—where references fail to support cited claims—remains a pervasive problem. Existing detection approaches based on semantic similarity or graph anomaly detection struggle with nuanced logical relationships and multi-hop reasoning, while LLM-based methods face hallucination risks and prohibitive computational costs. Moreover, current LLM agent architectures rely on unconstrained generation, lacking verifiable and safe execution guarantees. We propose CiteGuard, a multi-agent framework that unifies chain-of-evidence reasoning, graph-enhanced detection, and […]

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We prove strict log-concavity of the Riemann-Jacobi kernel, establish hyperbolicity of the Jensen polynomials J_{d,n}(x) for d <= 22, n <= 14, and prove that the global Riemann Hypothesis is algebraically equivalent to a subluminal condition on the Wronskian components. Part I (Sections 2-5) proves the kernel is strictly log-concave (TP_2) with curvature kappa >= 19.24, via the convex potential decomposition and a perturbation bound using only 4.3% of the log-concavity budget. Part II (Sections 6-8) establishes K_{d,n}(x) […]

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In this Part 2 of the paper, analytical, parametric multi-step solution is given of all of the six area and moments integrals of arbitrary segment of ellipse defined in parametrical form by trigonometric functions, based on its corresponding integrals of its central sector from Part 1 of the paper. Those integrals are here built from the general moment form of Green’s theorem curve integral for the calculation of the area and moments of a planar shape enclosed by […]

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What happens when you stop throwing money at AI infrastructure and start thinking about architecture instead A third-party cost analysis priced the platform at $32,000. The prototype went from concept to production deployment in six hours. Total compute cost for the first full cognitive evaluation session: less than one cent. Those numbers are not a rounding error. They are the result of a fundamental architectural decision that most AI developers never consider: what if the intelligence isn’t in […]

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The software engineering industry relies heavily on Large Language Models (LLMs) accessed via flat-rate web subscriptions, operating under the assumption of infinite, highly available compute. However, the paradigm of “unlimited compute” is fundamentally incompatible with the physical constraints of data centers. Surging enterprise demand and massive context windows have forced AI providers to introduce peak-hour usage rationing. In metropolitan hubs, the concentration of demand leads to significant rate-limiting during standard business hours (08:00–14:00 EST). In empirical observations of […]

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LoRA successfully specialized an LLM for high-variance speech, achieving significant WER improvements – but it wasn’t just the model. The results validated that building AI for widespread use requires a thoughtfully engineered data pipeline and careful dataset refinement, not simply massive amounts of data.

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