Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...

AI is searching particle colliders for the unexpected ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Dinosaur footprints have always been mysterious, but a new AI app is cracking their secrets. DinoTracker analyzes photos of fossil tracks and predicts which dinosaur made them, with accuracy rivaling ...

Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...

Regulators evaluate RNG systems to ensure outcomes are not manipulated and that probabilities behave as advertised.

Abstract: This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization ...

Low-rank data analysis has emerged as a powerful paradigm across applied mathematics, statistics, and data science. With the rapid growth of modern datasets in size, dimensionality, and complexity, ...

Abstract: The goal of this project is to construct an intelligent tourist management system, and to make use of big data, AI, IOT and cloud computing to realize the digital transformation of tourism ...