Science

Artificial intelligence is rapidly transforming anti-money laundering practices, offering the potential for more accurate, efficient, and transparent financial systems.

A new study demonstrates how convolutional neural networks can identify and explain potentially fraudulent activity in publicly traded companies.

New research reveals that background distractions in images don’t always hinder deep learning models for autonomous vehicle perception, challenging conventional assumptions about feature importance.

A new approach tackles the challenges of zero-shot super-resolution forecasting by enabling models to generalize effectively across different resolutions.

Researchers are developing new techniques to train language models to not just generate text, but to actively reason and verify their conclusions.

A new principle, Neural Coherence, offers a way to boost model performance on unseen tasks by strategically selecting pre-trained models and data.

A new review explores how quantifying uncertainty can unlock data-efficient artificial intelligence, enabling robust performance even with limited training data.

A new approach to detecting AI-generated images focuses on the subtle fingerprints left by camera hardware, rather than the telltale signs of the generative model itself.

As demand for robust facial recognition systems grows, researchers are increasingly turning to artificially generated datasets to overcome limitations in real-world training data.

Researchers are leveraging the power of artificial intelligence to reverse-engineer the complex processes that lead to the formation of exoplanets.