Modern-day LLMs are "fiction machines," designed not to be truthful but to make sense. What can we expect from these machines, and what are their limitations?

For decades, enterprises relied on historical sales figures and quarterly reports to guide their future strategies. While looking backward provides a baseline, ...

In the iconic Star Wars series, captain Han Solo and humanoid droid C-3PO boast drastically contrasting personalities. Driven by emotions and swashbuckling confidence, Han Solo often ignores C-3PO's ...

Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...

Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

This study develops a machine-learning-based approach to retrieve significant wave height (SWH) from soil moisture active passive (SMAP) radiometer data under tropical cyclone (TC) conditions, ...

Abstract: We implement transfer learning (TL) to attain efficiency in training and feature extraction by freezing the connection weights of shallow layers of deep learning (DL) models, already trained ...

Data analytics studies existing business data to identify patterns, trends, and insights that support better decisions.Data ...

Though new regulatory frameworks address fairness, accountability, and safety in AI systems, they often fail to directly mitigate the subtle communication bias in LLMs that can distort public ...