Using precise technology, this new driver-powered approach to safety is a simple, but powerful way for drivers to be more proactive and accountable for their own improvement, while giving management the necessary visibility and data to effectively monitor and intervene if needed. With these new MV AI-powered updates, when an event is detected, the DriveCam Event Recorder will issue a real-time in-cab alert to help drivers recognize and address their own risky behaviors and self-correct in the moment. Depending on the behavior, the alert will include a light and/or spoken phrase. With Lytx's ability to detect more than 60 driving behaviors with greater than 95% accuracy, its in-cab alerts are some of the most precise in the industry. Drivers will also have access to new check-in tools allowing them to review their own video and performance after-the-fact, including behavior duration.

Financial crime as a wider category of cybercrime continues to be one of the most potent of online threats, covering nefarious actives as diverse as fraud, money laundering and funding terrorism. Today, one of the startups that has been building data intelligence solutions to help combat that is announcing a fundraise to continue fueling its growth. Ripjar, a UK company founded by five data scientists who previously worked together in British intelligence at the Government Communications Headquarters (GCHQ, the UK's equivalent of the NSA), has raised $36.8 million (£28 million) in a Series B, money that it plans to use to continue expanding the scope of its AI platform -- which it calls Labyrinth -- and scaling the business. Labyrinth, as Ripjar describes it, works with both structured and unstructured data, using natural language processing and an API-based platform that lets organizations incorporate any data source they would like to analyse and monitor for activity. It automatically and in real time checks these against other data sources like sanctions lists, politically exposed persons (PEPs) lists and transaction alerts.

One little-known home and retail automation startup might seem like an unlikely candidate to help combat the ongoing pandemic. But its founder says its technology can do just that, even if it wasn't the company's original plan. Butlr, a spin-out of the MIT Media Lab, uses a mix of wireless, battery-powered hardware and artificial intelligence to track people's movements indoors without violating their privacy. The startup uses ceiling-mounted sensors to detect individuals' body heat to track where a person walks and where they might go next. The sensors can turn on mood-lighting or air conditioning when it detects movement, help businesses understand how shoppers navigate their stores, determine the wait-time in the queues at the checkout, and even sound the alarm if it detects a person after-hours.

Robots could be trained to disinfect surfaces, take temperatures, collecting swabs and provide social support for quarantined patients to help combat coronavirus. The'dull, dirty and dangerous jobs' could be automated, but we would need to add many new functionalities to machines first, roboticists argued in a journal editorial. Many of these necessary capabilities, however, are neither being funded or developed at present, the experts cautioned. Robots could be trained to disinfect surfaces, take temperatures, collecting swabs and provide social support for quarantined patients to help combat coronavirus. Among the signatories of the editorial are roboticist Howie Choset of the Carnegie Mellon University in Pittsburgh and the president of the National Academy of Science, Marcia McNutt.