technocracy

arXiv:2603.24974v1 Announce Type: cross Abstract: Firms that price perishable resources — airline seats, hotel rooms, seasonal inventory — now routinely use demand predictions, but these predictions vary widely in quality. Under hard capacity constraints, acting on an inaccurate prediction can irreversibly deplete inventory needed for future periods. We study how prediction uncertainty propagates into dynamic pricing decisions with linear demand, stochastic noise, and finite capacity. A certified demand forecast with known error bound~$epsilon^0$ specifies where the system should […]

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arXiv:2602.18528v1 Announce Type: new Abstract: Audio-visual continual test-time adaptation involves continually adapting a source audio-visual model at test-time, to unlabeled non-stationary domains, where either or both modalities can be distributionally shifted, which hampers online cross-modal learning and eventually leads to poor accuracy. While previous works have tackled this problem, we find that SOTA methods suffer from catastrophic forgetting, where the model’s performance drops well below the source model due to continual parameter updates at test-time. In this work, […]

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arXiv:2604.04937v1 Announce Type: new Abstract: Large language models produce fluent text but struggle with systematic reasoning, often hallucinating confident but unfounded claims. When Apple researchers added irrelevant context to mathematical problems, LLM performance degraded by 65% Apple Machine Learning Research, exposing brittle pattern-matching beneath apparent reasoning. This epistemic gap, the inability to ground claims in traceable evidence, limits AI reliability in domains requiring justification. We introduce Pramana, a novel approach that teaches LLMs explicit epistemological methodology by fine-tuning […]

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Post-quantum migration for ZK proof systems is an architecture problem, not a parameter-tuning problem. This research note proposes a four-layer framework for analyzing where quantum-vulnerable assumptions sit in a proving stack, a three-condition modularity test for whether deployed systems can actually migrate, and applies them to Zcash, ZKsync Era, and Starknet.

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April 24 2026 | Global — As structural changes reshape the crypto market, liquidity is increasingly moving across trading venues rather than concentrating in a few dominant platforms. Global crypto derivatives exchange Zoomex states that the shift is not driven by shrinking market activity, but by evolving trader behavior — with users prioritizing execution quality and trading efficiency over platform size. According to CoinGlass, total crypto trading volume reached approximately $20.6 trillion in Q1 2026, with derivatives accounting […]

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arXiv:2604.02429v1 Announce Type: new Abstract: Photonic computing is a computing paradigm which have great potential to overcome the energy bottlenecks of electronic von Neumann architecture. Throughput and power consumption are fundamental limitations of Complementary-metal-oxide-semiconductor (CMOS) chips, therefore convolutional neural network (CNN) is revolutionising machine learning, computer vision and other image based applications. In this work, we propose and validate a fully photonic convolutional neural network (PCNN) that performs MNIST image classification entirely in the optical domain, achieving 94 […]

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arXiv:2604.15360v1 Announce Type: new Abstract: This study presents a triadic analysis of energy storage operation under multi-stage model predictive control, investigating the interplay between data characteristics, forecast uncertainty, planning horizon, and battery c-rate. Synthetic datasets are generated to systematically explore variations in data profiles and uncertainty, enabling parametrization and the construction of relationships that map these characteristics to optimal horizon length. Results reveal the presence of an effective horizon, defined as the look-ahead length beyond which additional forecast […]

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