The world is facing a maternal health crisis. According to the World Health Organization, approximately 810 women die each day due to preventable causes related to pregnancy and childbirth. Two-thirds of these deaths occur in sub-Saharan Africa. In Rwanda, one of the leading causes of maternal mortality is infected Cesarean section wounds. An interdisciplinary team of doctors and researchers from MIT, Harvard University, and Partners in Health (PIH) in Rwanda have proposed a solution to address this problem.

Global artificial intelligence (AI) software spending will grow 21.3 per cent to US$62 billion next year, according to analyst firm Gartner. Knowledge management, virtual assistants, autonomous vehicles, digital workplace and crowdsourced data will make up the top five use cases for AI software spending in 2022. The forecast report focused on applications with AI embedded in them, such as computer vision software, as well as software that is used to build AI systems. "Use cases that deliver significant business value, yet can be scaled to reduce risk, are critical to demonstrate the impact of AI investment to business stakeholders," Gartner senior research director Alys Woodward said. Demand for AI technologies and associated market growth is closely tied to organisational AI maturity levels, the report said.

Aegis AI, an artificial intelligence startup that builds software which employs computer vision to automatically detect weapons in security camera feeds, today announced that it's rebranding as Actuate and launched new AI threat-detection features. Actuate was founded in early 2018 by University of Chicago MBAs Sonny Tai and Ben Ziomek. Tai is a former Marine Corps captain who spent his formative years in Johannesburg, South Africa, where gun violence rates are some of the highest in the world, while Ziomek brings deep data science and AI expertise gained from his time as a program manager at Microsoft. The New York City-based Aegis Systems is a venture capital-backed AI startup that provides computer vision software to turn any security camera into a threat-detecting smart camera. Aegis AI system automatically detects firearms in existing security camera feeds, providing early warning and dramatically improving law enforcement response.

International Data Corporation (IDC) recently published an IDC Innovators report profiling five companies that offer compelling and differentiated computer vision software. The five companies are Algolux, Deep Vision AI, Sighthound, ViSenze, and Umbo CV. Computer vision is an AI technology that allows computers to understand and label images. Use cases include video surveillance, driverless car testing, daily medical diagnostics, and monitoring the health of crops and livestock. AI is used for pattern recognition and learning techniques driven largely by machine learning (ML) and deep learning (DL) algorithms that bring visual understanding capabilities in a growing variety of hardware and software applications.

If you're in the market to buy fresh papayas, it can be a challenge to figure out ripeness based on peel color without also squeezing the fruit to test for softness. A Brazilian research group could make life easier for both shoppers and producers in the near future with a computer vision algorithm that estimates ripeness based on images alone. Last year, the United States alone imported more than US $107 million worth of fresh papayas as the world's largest papaya import market. The computer vision software could enable papaya growers to maximize the value of their fruit by sending the ripest papayas to local markets and saving less ripe papayas for export, says Douglas Fernandes Barbin, a researcher in the department of food engineering at the University of Campinas in São Paulo, Brazil. But he and his colleagues also want to help individual shoppers get their money's worth in grocery aisles.

Computer vision software has a long way to go. We know it can have trouble recognizing even the simplest of images, so it's little surprise the human face, in all its complexity, is an inevitable stumbling block. But what happens when you intentionally distort a face? In a new project, two artists exploit the technology's shortcomings to produce wonky-looking portraits that test the limits of facial recognition software. Unseen Portraits is the work of Philipp Schmitt and Stephan Bogner, both designers from Germany.