technocracy

First kākāpō chick in four years hatches on Valentine’s Day First chick of the 2026 breeding season! Kākāpō Yasmine hatched an egg fostered from kākāpō Tīwhiri on Valentine’s Day, bringing the total number of kākāpō to 237 – though it won’t be officially added to the population until it fledges. Here’s why the egg was fostered: “Kākāpō mums typically have the best outcomes when raising a maximum of two chicks. Biological mum Tīwhiri has four fertile eggs this […]

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arXiv:2602.22240v1 Announce Type: new Abstract: Large Language Models (LLM) show strong abilities in code generation, but their skill in creating efficient parallel programs is less studied. This paper explores how LLMs generate task-based parallel code from three kinds of input prompts: natural language problem descriptions, sequential reference implementations, and parallel pseudo code. We focus on three programming frameworks: OpenMP Tasking, C++ standard parallelism, and the asynchronous many-task runtime HPX. Each framework offers different levels of abstraction and control […]

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Mumbai, India, Jan 5, 2026: India’s digital transformation journey has moved decisively from vision to execution. As enterprises and government bodies race to modernize operations, adopt AI at scale, and secure increasingly complex digital ecosystems, the need for real-world strategies, peer learning, and trusted platforms has never been greater. Answering this moment, Exito Media Concepts presents the 43rd Edition of the Digital Transformation Summit India 2026, a flagship, in-person gathering bringing together India’s most influential CIOs, CISOs, and […]

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Reinforcement learning (RL) post-training is a critical stage in modern language model development, playing a key role in improving alignment and reasoning ability. However, several phenomena remain poorly understood, including the reduction in output diversity. To gain a broader understanding of RL post-training, we analyze the learning dynamics of RL post-training from a perspective that has been studied in supervised learning but remains underexplored in RL. We adopt an empirical neural tangent kernel (NTK) framework and decompose the […]

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We all knew that this year’s CES would be dominated by AI, and the reality is nothing short of that. Major companies and startups have unveiled some of the most unique AI products at the largest consumer tech conference in Las Vegas. When we talk of AI, Meta is among the names that pops up in everyone’s head, and rightly so. Meta teleprompter brings notes right to your eyes Well, Meta showed up at the CES 2026 event, […]

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arXiv:2512.21411v2 Announce Type: replace-cross Abstract: Singular learning theory characterizes Bayesian models with non-identifiable parameterizations through two central quantities: the real log canonical threshold (RLCT), which governs marginal likelihood asymptotics, and the singular fluctuation, which determines second-order generalization behavior and the complexity term in WAIC. While the geometric meaning of the RLCT is well understood, the interpretation of singular fluctuation has remained comparatively opaque. We show that singular fluctuation admits a precise thermodynamic interpretation. Under a tempered (Gibbs) posterior, […]

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Fix npm trusted publishing from GitHub Actions after token revocations: add OIDC permission, upgrade npm, and publish with –provenance.

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arXiv:2602.20646v1 Announce Type: cross Abstract: We study stochastic gradient descent (SGD) for composite optimization problems with $N$ sequential operators subject to perturbations in both the forward and backward passes. Unlike classical analyses that treat gradient noise as additive and localized, perturbations to intermediate outputs and gradients cascade through the computational graph, compounding geometrically with the number of operators. We present the first comprehensive theoretical analysis of this setting. Specifically, we characterize how forward and backward perturbations propagate and […]

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