We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

As AI Music Tools Proliferate, Detection Technologies and Industry Responses EvolveThe music industry faces an unprecedented ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

Insurance companies aren't experimenting with AI. They're deploying it at scale across three critical functions that directly ...

Ethical disclosures and Gaussian Splatting are on the wane, while the sheer volume of submitted papers represents a new ...

Experts repeatedly point to privacy and security as key advantages of on-device AI. In a cloud situation, data is flying every which way and faces more moments of vulnerability. If it remains on an ...

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

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 ...

In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology ...

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, ...

The study points up interpretability as a critical barrier to trust and adoption. Many AI-based cybersecurity tools function ...

Artificial intelligence is currently advancing at a velocity that few executives have witnessed in their careers. New capabilities are not emerging annually, but quarterly, and in some cases, monthly.