technocracy

arXiv:2601.03360v1 Announce Type: new Abstract: Continuous-time state estimation has been shown to be an effective means of (i) handling asynchronous and high-rate measurements, (ii) introducing smoothness to the estimate, (iii) post hoc querying the estimate at times other than those of the measurements, and (iv) addressing certain observability issues related to scanning-while-moving sensors. A popular means of representing the trajectory in continuous time is via a Gaussian process (GP) prior, with the prior’s mean and covariance functions generated […]

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Most analysts don’t spend their time analysing data. They spend it copying, cleaning, and rebuilding the same reports every week. Across roles in e-commerce at Amazon, financial services at American Express, and the non-profit sector, I kept seeing the same pattern: manual reporting quietly consuming time, introducing errors, and slowing down decisions. At some point, improving reports stopped making sense. The process itself needed to go. The Problem No One Talks About On the surface, everything looked fine: […]

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arXiv:2604.15333v1 Announce Type: new Abstract: Human-AI romantic relationships are increasingly common, yet little is understood about how public discourse around them emerges and shifts over time. Prior research has examined user experiences and ethical concerns, but lacks longitudinal analyses of user-initiated public discussions. We address this gap by analyzing a high-precision dataset of 3,383 self-disclosed romantic companion AI posts from Reddit (2017-2025), using topic modeling and temporal statistical analysis to identify dominant themes and their evolution over time. […]

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arXiv:2601.17990v1 Announce Type: new Abstract: Shaping multi-megawatt loads, such as data centers, impacts generator dispatch on the electric grid, which in turn affects system CO2 emissions and energy cost. Substantiating the effectiveness of prevalent load shaping strategies, such as those based on grid-level average carbon intensity, locational marginal price, or marginal emissions, is challenging due to the lack of detailed counterfactual data required for accurate attribution. This study uses a series of calibrated granular ERCOT day-ahead direct current […]

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arXiv:2506.00452v4 Announce Type: replace-cross Abstract: In orthogonal frequency division multiplexing (OFDM), accurate channel estimation is crucial. Classical signal processing-based approaches, such as linear minimum mean-squared error (LMMSE) estimation, often require second-order statistics that are difficult to obtain in practice. Recent deep neural network (DNN)-based methods have been introduced to address this; yet they often suffer from high inference complexity. This paper proposes an Attention-aided MMSE (A-MMSE), a model-based DNN framework that learns the linear MMSE filter via the […]

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USA AI Summit LLC officially announces the launch of the USA AI Summit 2026, a landmark gathering designed to unite thought leaders, developers, researchers, founders, and innovators at the forefront of artificial intelligence. Positioned as a leading USA artificial intelligence summit, the event will take place on November 7, 2026, at 515 Madison Avenue, New York, NY 10022 (Jay Suites – The Beatles Room). As a premier AI summit and dynamic artificial intelligence summit, the USA AI Summit […]

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Urban traffic management demands systems that simultaneously predict future conditions, detect anomalies, and take safe corrective actions — all while providing reliability guarantees. We present STREAM-RL, a unified framework that introduces three novel algorithmic contributions: (1) PU-GAT+, an Uncertainty-Guided Adaptive Conformal Forecaster that uses prediction uncertainty to dynamically reweight graph attention via confidence-monotonic attention, achieving distribution-free coverage guarantees; (2) CRFN-BY, a Conformal Residual Flow Network that models uncertainty-normalized residuals via normalizing flows with Benjamini-Yekutieli FDR control under arbitrary […]

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arXiv:2604.13192v1 Announce Type: new Abstract: Robust control barrier functions (CBFs) provide a principled mechanism for smooth safety enforcement under worst-case disturbances. However, existing approaches typically rely on explicit, closed-form structure in the dynamics (e.g., control-affine) and uncertainty models. This has led to limited scalability and generality, with most robust CBFs certifying only conservative subsets of the maximal robust safe set. In this paper, we introduce a new robust CBF framework for general nonlinear systems under bounded uncertainty. We […]

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The crypto industry is now worth trillions, but Rome wasn’t built in a day. Over the years, many developers, enthusiasts, and users of all kinds and places have put their own blocks to raise this bright skyscraper. We’ve crossed some huge milestones, sometimes through careful planning, sometimes through happy accidents, and often through bold experiments. Of course, the first one is Bitcoin itself: the first-ever decentralized cryptocurrency, born on January 3, 2009. This modest snowball would create an […]

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