Modern cybersecurity operations depend on fast, reliable data movement across cloud, on-premises and hybrid environments. Security teams collect data from security information and event management ...

Public experiment log using Get Physics Done (GPD) with Codex to explore predictive control of tokamak plasma turbulence and confinement. A physics-based flight simulator for optimizing airbrake ...

Google has quietly reworked Gemini‘s usage limits, splitting the shared pool and boosting the individual caps for the Thinking and Pro models. At launch, both models had the same daily quota, meaning ...

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control and ...

Functional connectivity (FC) analysis holds strong potential for predicting behavioral traits. However, whole-brain predictive models face challenges with interpretability and generalizability, while ...

Abstract: Model-free predictive control (MFPC) has become a popular choice for addressing the robustness limitations of model-based predictive control (MBPC), by replacing physical models with ...

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.