May 2026

Digital phenotyping enables continuous passive monitoring of behavior and physiology, offering a promising paradigm for early detection of psychotic relapse. In this work, we develop and systematically study two smartwatch-based frameworks for daily relapse detection. The first forecasts cardiac dynamics and flags deviations between predicted and observed features as indicators of abnormality. The second adopts a multi-task formulation that fuses sleep with motion and cardiac-derived signals, learning time-aware embeddings and predicting measurement timing. Both pipelines use Transformer encoders […]

Ver mais

Active learning for machine-learning interatomic potentials (MLIPs) must address several challenges to be practical: scaling to large candidate pools, leveraging energy-force supervision, and maintaining robustness when candidate pools are biased relative to the target distribution. In this work, we jointly address these challenges. We first introduce a linearly scaling acquisition framework based on chunked feature-space posterior-variance shortlisting. By avoiding materialisation of the candidate and train set kernels, this approach enables screening of ~200k structures within hours and applies […]

Ver mais

Think of your database like your home. Your living room, bedroom, kitchen, garage: each room serves a different purpose, but they’re all under one roof. You don’t build a restaurant across town because you need to cook dinner. You don’t rent a commercial garage to park your car. Postgres works the same way. Search, vectors, time-series, queues, documents, all rooms in one house. Same roof, foundation, and key. But specialized database vendors have spent years telling you otherwise. […]

Ver mais

:::info Authors: Alhussein Fawzi Matej Balog Aja Huang Thomas Hubert Bernardino Romera-Paredes Mohammadamin Barekatain Alexander Novikov Francisco J. R. Ruiz Julian Schrittwieser Grzegorz Swirszcz David Silver Demis Hassabis Pushmeet Kohli ::: Abstract Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one such primitive task, occurring in many systems—from neural networks to scientific computing routines. The automatic discovery […]

Ver mais

:::info Astounding Stories of Super-Science April 2004, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. THE COUNTRY OF THE BLIND – XXXII. — THE COUNTRY OF THE BLIND. Astounding Stories of Super-Science April 2004: THE COUNTRY OF THE BLIND – XXXII. — THE COUNTRY OF THE BLIND. By H. G. Wells ::: Three hundred miles and more from Chimborazo, one hundred from the snows of Cotopaxi, […]

Ver mais

why isn’t there a neutral red-team-as-a-service that runs a standardized battery of reward-hack probes, verifier-fidelity tests, and contamination scans against RL environments before frontier labs buy them, saving labs engineer weeks of manual procurement review and giving env vendors a credible third-party artifact to sell against? submitted by /u/Sharp_Variation7003 [link] [comments]

Ver mais

Smart contracts are immutable once deployed. A single bug can drain millions in minutes. This article builds a practical taxonomy of the most dangerous vulnerability classes: reentrancy, integer overflow, access control, MEV, and invariant violations. Each section explains the vulnerability with Solidity code, formal notation, and systematic defenses.

Ver mais