The most dangerous aspect of a water rescue for first responders isn't the treacherous environmental conditions, it's the terrified and panicked victim capable of pulling their rescuer under the waves along with them. Rather than risk national treasures like David Hasselhoff, the U-Safe self-propelled buoy from Portugal's Noras Performance will brave the waves in their stead. The U-Safe is an aquatic robot designed to drive out to a swimmer in distress using a pair of turbines mounted in its "legs." The turbines are omnidirectional and operate regardless of the U-Safe's orientation in the water. It can reach a top speed of 15km/h and range out to 3.2 nautical miles so long as the first responders can maintain a line of sight.

In recent years, deep learning techniques have proved to be highly valuable for tackling countless research and real-world problems. Researchers at Feedzai, a financial data science company based in Portugal, have demonstrated the potential of deep learning for the prevention and detection of illicit money laundering activities. In a paper presented at the 3rd ACM International Conference on AI in Finance, the team at Feedzai introduced LaundroGraph, a self-supervised model that could simplify the cumbersome process of reviewing large amounts of financial interactions looking for suspicious transactions or monetary exchanges. Their model is based on a graph neural network, an artificial neural network (ANN) designed to autonomously process large amounts of data that can be represented as a graph. "Wanting to strengthen our AML solution, and after identifying major pains with the current AML reviewing process, we thought about solutions to overcome these challenges using AI," Mario Cardoso, a Research Data Scientist at Feedzai, told TechXplore.