Build a Reasoning Model From Scratch Is Out
Short note announcing the release of Build a Reasoning Model From Scratch and linking the publisher and Amazon pages.
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June 2026
Satya Nadella está haciendo la pregunta correcta
La idea más importante sobre inteligencia artificial en estos momentos puede que no provenga de un artículo científico, del lanzamiento de un nuevo modelo o de un benchmark. Puede que provenga de un breve ensayo publicado en X por el CEO de Microsoft, Satya Nadella. En él, Nadella sostiene que el futuro de la empresa dependerá de la interacción entre lo que denomina capital humano y capital de tokens: por un lado, el conocimiento, el criterio, las relaciones […]
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8 Best Code Quality and Security Alternatives to SonarQube in 2026
Teams researching code quality and security alternatives to SonarQube are rarely looking for another dashboard. They want more relevant findings, faster remediation, less tool sprawl, and a workflow developers will continue using after the initial rollout. SonarQube remains a capable benchmark. Its current platform analyzes bugs, code smells, vulnerabilities, security hotspots, and architecture issues across the IDE, pull requests, and CI/CD pipelines. It also provides quality profiles, quality gates, secrets detection, SAST, and—through Advanced Security—software composition analysis. The […]
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Celebrating 100 Years: Avi 70 + CSDM 30 (June 14-18, 2027)
[Guest post by Amir Shpilka and Irit Dinur] https://www.ias.edu/math/events/celebrating-100-years-avi-70-csdm-30 The Institute for Advanced Study’s School of Mathematics is pleased to announce a conference celebrating Avi Wigderson’s 70th birthday and retirement, together with 30 years of the Computer Science and Discrete Mathematics program (CSDM) at IAS. The conference will honor both Avi’s extraordinary scientific legacy and his transformative role in shaping the intellectual community around theoretical computer science and discrete mathematics at IAS. Avi Wigderson has made foundational contributions […]
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How I Turned a OnePlus 3T into a postmarketOS Home Server
Why an old phone I’d wanted to self-host a small project of mine — a bot I run for myself. The blocker was always the hosting. I didn’t want to rent a VPS and run it remotely, set it up, patch it, keep it alive; and I didn’t want to pay more for a managed platform to skip that. So it stayed an idea. What I had was an old OnePlus 3T in a drawer: a 2016 flagship, […]
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Who Got Breasts First and How We Got Them
It really is Sydney Sweeney’s world, and we’re all just living in it. Human female breasts are an evolutionary mystery along several dimensions. First, breast permanence is unique to humans. All other mammals develop breast prominence during pregnancy or nursing, and the mammary tissue recedes after weaning. This process is called “involution”. In contrast, humans develop breast tissue at puberty before first pregnancies and maintain it permanently after last pregnancies. Second, breasts are costly, both metabolically and potentially […]
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A Bayesian latent Gaussian process framework for aerodynamic uncertainty quantification
arXiv:2606.28871v1 Announce Type: new Abstract: Predicting the aerodynamic performance (e.g. lift, drag, and moment coefficients) of an aircraft is challenging — computational models are biased and direct simulations are prohibitive. A pragmatic way to overcome this limitation is by calibrating low-fidelity computational predictions with experimental measurements. This, however, requires calibrating against emph{sparse} measurements contaminated with emph{uncertainty} in both the control inputs and the measured aerodynamic response. We develop a methodology to address this problem based on Gaussian process […]
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Perspectives on Latent Factor Indeterminacy and its Implications for Data Representation
arXiv:2606.28854v1 Announce Type: new Abstract: The common factor analytic model is related to Helmholtz and Boltzmann machines, can be conceived as a linear autoencoder, or can be thought of as a single-hidden-layer generative neural network. We thus consider it a basal generative representation learner that can be used as a minimal model for studying the foundational characteristics of (deep) generative model architectures. We focus on the fundamental problem of indeterminacy in latent factor projections. This indeterminacy implies that, […]
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Variance Reduction for Stochastic Gradient Generalized Non-reversible Langevin Monte Carlo Algorithms
arXiv:2606.28808v1 Announce Type: new Abstract: We study the leading-order fluctuation of stochastic gradient Euler-Maruyama estimators for generalized non-reversible Langevin dynamics. Under structural assumptions tailored to the small-stepsize central limit theorem and under an unbiased stochastic gradient oracle, we prove that the empirical average over a horizon of order the inverse squared stepsize satisfies a central limit theorem in the vanishing-stepsize regime. The limiting variance is characterized through the Poisson equation of the limiting full-gradient diffusion. We then rewrite […]
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