Re-imagining smartphone photography: Adobe’s new camera allows you to photoshop pictures in real-time

Researchers at the Queen Mary University of London have developed an algorithm that predicts whether an actor’s career has peaked and predicts their most successful days in the future, with an accuracy of 85 per cent. The jobs in an actor’s career follow the rich-get-richer phenomenon. It reveals that an actor’s success could be down to their circumstances rather than acting ability.

A team of researchers from Pennsylvania State and Columbia University, USA, has developed an Artificial Intelligence (AI) tool for detecting discrimination based on race or gender. Their method used various types of available data, such as income data from the US Census Bureau, New York City Police Department’s stop-and frisk program data etc, and used counterfactual inference algorithms to arrive at the results.

Researchers at the Yale University have developed an AI-enabled tool that uses machine -learning algorithms to predict heart attacks and other cardiac issues. They found the algorithm better at pulling out data patterns and refining risk assessment compared to Coronary Compute d Tomography Arteriography (CCTA).

Using AI, researchers at Penn State University have developed an algorithm to detect cloud formations that lead to storms, hurricanes and cyclones with 99 per cent accuracy. They created a framework based on machine learning (ML) that detects rotational movements in clouds from satellite images that might have otherwise gone unnoticed.

Scientists at the Northern Illinois University, USA, have developed an AI-based tool that can identify and distinguish between normal cry signals of babies and abnormal ones, such as those resulting from an underlying illness. They used a new cry language recognition algorithm based on automatic speech recognition to detect the features of infant cries. The algorithm is independent of the individual crier, meaning that it can be used in a broader sense in practical scenarios.

MIT scientists have developed a technique that enables robots to quickly identify objects hidden in a 3D cloud of data. Robots ‘see’ their environment through sensors that translate a visual scene into a matrix of dots. With the new technique, a robot can accurately pick out an object that is otherwise obscured within a dense cloud of dots.