True ROI for R&D won't come from the tool that generates 10,000 new ideas. It will come from the tool that confidently tells ...

When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

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Abstract: This work proposes an approach that integrates reinforcement learning (RL) and model predictive control (MPC) to solve finite-horizon optimal control problems in mixed-logical dynamical ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

Artificial intelligence startup OpenEvidence says its AI model has scored a perfect 100% on the United States Medical Licensing Examination (USMLE), raising the bar on the proficiency of AI models to ...

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.