technocracy

arXiv:2604.15468v1 Announce Type: new Abstract: AI-based systems, currently driven largely by LLMs and tool-using agentic harnesses, are increasingly discussed as a possible threat to software engineering. Foundation models get stronger, agents can plan and act across multiple steps, and tasks such as scaffolding, routine test generation, straightforward bug fixing, and small integration work look more exposed than they did only a few years ago. The result is visible unease not only among students and junior developers, but also […]

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arXiv:2602.23341v1 Announce Type: cross Abstract: Coarse data arise when learners observe only partial information about samples; namely, a set containing the sample rather than its exact value. This occurs naturally through measurement rounding, sensor limitations, and lag in economic systems. We study Gaussian mean estimation from coarse data, where each true sample $x$ is drawn from a $d$-dimensional Gaussian distribution with identity covariance, but is revealed only through the set of a partition containing $x$. When the coarse […]

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Table of Links Abstract and 1. Introduction Some recent trends in theoretical ML 2.1 Deep Learning via continuous-time controlled dynamical system 2.2 Probabilistic modeling and inference in DL 2.3 Deep Learning in non-Euclidean spaces 2.4 Physics Informed ML Kuramoto model 3.1 Kuramoto models from the geometric point of view 3.2 Hyperbolic geometry of Kuramoto ensembles 3.3 Kuramoto models with several globally coupled sub-ensembles Kuramoto models on higher-dimensional manifolds 4.1 Non-Abelian Kuramoto models on Lie groups 4.2 Kuramoto models […]

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Hi, I applied to two professional master’s programs this year, one at MILA and one at Polytechnique Montréal. I got accepted at Poly, but rejected from MILA, and they suggested I complete a minor in computer science instead. I’m trying to figure out whether it’s actually worth doing the minor and reapplying to MILA, or if I should just go straight to Poly. I already have a background in software development, a bachelor’s degree in mechanical engineering, and […]

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When I started writing about AI in 2019, my first article was dedicated to what machine learning is and how it works. It explained the difference between weak and strong (or general) AI and mentioned that we have no idea how to create the latter. Well, in 2023, maybe we actually (finally!) do. I’m talking about multimodal learning. Don’t get me wrong – multimodal learning wasn’t a new concept already in 2019. Back then, TechRepublic called it the […]

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:::info Authors: James Truslow Angela Spillane Huiming Lin Katherine Cyr Adeeti Ullal Edith Arnold Ron Huang Laura Rhodes Jennifer Block Jamie Stark James Kretlow Alexis L. Beatty Andreas Werdich Deepali Bankar Matt Bianchi Ian Shapiro Jaime Villalpando Sharon Ravindran Irida Mance Adam Phillips John Earl Rahul C. Deo Sumbul A. Desai Calum A. MacRae ::: Abstract Physical activity or structured exercise is beneficial in a wide range of circumstances. Nevertheless, individual-level data on differential responses to various types […]

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