Abstract: Deep learning-based traffic prediction models require vast amounts of data to learn embedded spatial and temporal dependencies. The inherent privacy and commercial sensitivity of such data ...

In managing airport traffic, small errors can cause catastrophe. A group from the CMU Robotics Institute's AirLab used the ...

Wall St. Journal warns AI growth may be fueled by subsidies and partnerships, not real demand, raising risks for marketers ...

The Flighty app claims to warn travellers of disruptions and delays up to 25 hours in advance, even before airlines have made ...

A fundamental technique in the world of artificial intelligence (AI) is machine learning, which helps machines like computers ...

Local tech leaders from MYOB, Guzman y Gomez, and Aware Super reveal how AI is reshaping customer experience, streamlining ...

Traffic congestion costs the trucking industry $108B annually. From rising fuel and labor costs to driver retention ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...

Traffic jams are a problem in large urban areas. How can they be solved without expanding the road network? This is a ...

Advancements in Machine Learning for Materials Science Machine learning (ML) is really shaking things up in materials ...

Amazon can steer market-wide prices without ever colluding—exposing a gap in antitrust law that the FTC is now fighting to close.

Climate change is drying out rivers across the country. A new AI forecasting tool can help managers, governments and water ...