It happened once that it was tantamount to spying into a system of an unsuspecting neighborhood. You would visit a few of the servers, check CPU or memory, and decide that nothing was wrong at the end of the day. Those days are long gone. The new environment of a cloud-native system is far more dynamic and unpredictable. Several seconds are spent before containers move in and out. Inter-cloud transversal microservices clusters. The virtual networks have a journey […]

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arXiv:2603.28815v1 Announce Type: new Abstract: This technical report presents SkillTester, a tool for evaluating the utility and security of agent skills. Its evaluation framework combines paired baseline and with-skill execution conditions with a separate security probe suite. Grounded in a comparative utility principle and a user-facing simplicity principle, the framework normalizes raw execution artifacts into a utility score, a security score, and a three-level security status label. More broadly, it can be understood as a comparative quality-assurance harness […]

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I’ve been designing products for over a decade now, and I’ve noticed something: most design debt doesn’t start with bad design. It starts with decisions that made perfect sense at the time. A PM says, “Let’s ship this for now, we’ll clean it up in Q3.” The team’s underwater. The deadline’s real. And honestly? Shipping something imperfect is often the right call. Products have to move. I’ve made these calls myself. But somewhere between launching and scaling, something […]

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Objection, a Thiel-backed startup, aims to use AI to judge journalism, letting users pay to challenge stories. Critics warn it could chill whistleblowers and reshape how media accountability works.

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Hey Hackers! This article is the second in a two-part series on the engineering reality of Physical AI. In Part 1, titled The Next Great Engineering Frontier: The Hidden Complexity of Physical AI, I discussed how the chaotic physical world, the high stakes of failure, and the Sim-to-Real gap make using embodied AI in robotics a harder problem than generating text, images, or video via an AI chatbot. However, mastering the physics is only half the battle. The […]

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arXiv:2603.26731v1 Announce Type: new Abstract: How much scene context a single object carries is a well-studied question in human scene perception, yet how this capacity is organized in vision-language models (VLMs) remains poorly understood, with direct implications for the robustness of these models. We investigate this question through a systematic behavioral and mechanistic analysis of contextual inference from single objects. Presenting VLMs with single objects on masked backgrounds, we probe their ability to infer both fine-grained scene category […]

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arXiv:2506.20533v4 Announce Type: replace Abstract: Robust subspace estimation is fundamental to many machine learning and data analysis tasks. Iteratively Reweighted Least Squares (IRLS) is an elegant and empirically effective approach to this problem, yet its theoretical properties remain poorly understood. This paper establishes that, under deterministic conditions, a variant of IRLS with dynamic smoothing regularization converges linearly to the underlying subspace from any initialization. We extend these guarantees to affine subspace estimation, a setting that lacks prior recovery […]

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