With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

A new, real threat has been discovered by Anthropic researchers, one that would have widespread implications going ahead, on ...

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

Artificial Intelligence enabled threat detection for Blockchain attacks mainly involved in the application of deep learning and machine learning techniques to identify and mitigate vulnerable and ...

From PSIM’s rise and fall to the emergence of integration alliances, connected intelligence, and agentic AI, the physical ...

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

In a striking leap toward safer self-driving cars, researchers at Texas A&M University College of Engineering and the Korea ...

Professor Kijung Shin's research team at the Kim Jaechul Graduate School of AI has developed an AI technology that predicts complex social group behavior by analyzing how individual attributes such as ...

This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...