AI’s predictive power is transformative, but its lack of explainability, contextual understanding, and causal reasoning ...

Users can note which content they would like to view more frequently. Instagram is handing users some control in deciding what content they see. The social media giant is allowing users to have a say ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

Google expects an explosion in demand for AI inference computing capacity. The company's new Ironwood TPUs are designed to be fast and efficient for AI inference workloads. With a decade of AI chip ...

Abstract: Traditional machine-learning approaches face limitations when confronted with insufficient data. Transfer learning addresses this by leveraging knowledge from closely related domains. The ...

School of Economics, The University of Nottingham-Ningbo, Ningbo, China. The study focuses on identifying and distinguishing whether there are differences between those students receiving special ...

Company will showcase scientific leadership with three key presentations and highlights scalable, data-agnostic research solutions at ISPE Annual Conference 2025. With a strong emphasis on causal ...

The 3rd Workshop on Causal Inference and Machine Learning in Practice at KDD 2025 aims to bring together researchers, industry professionals, and practitioners to explore the application of causal ...