MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" that solves the latency bottleneck of long-document analysis.

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

Across the University of Pennsylvania Health System, scientists are now using AI to enhance their understanding of biological systems and modern medicine.

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

Understand why testing must evolve beyond deterministic checks to assess fairness, accountability, resilience and ...

For decades, television advertising has been a game of creativity and repetition. Jingles and mascots became part of our ...

Why next-generation avionics validation is becoming a value driver for aircraft leases. Avionics are the nervous system of ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

For a project in Bangladesh, Prof. Mushfiq Mobarak and his team used machine-learning models applied to mobile phone records ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...