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Facial recognition software used by the UK’s biggest police force has returned false positives in more than 98 percent of alerts generated, The Independent revealed, with the country’s biometrics regulator calling it “not yet fit for use”.
The Metropolitan Police’s system has produced 104 alerts of which only two were later confirmed to be positive matches, a freedom of information request showed. In its response the force said it did not consider the inaccurate matches “false positives” because alerts were checked a second time after they occurred.
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One startup believes that AI holds the key to the future of flavor: As the New Food Economy reports, NYC-based Analytical Flavor Systems envisions a future in which food is hyper-customised for people’s individual tastes — “a day when we’ll each have a Doritos of our own.”
Mass-market snacks and drinks are designed to appeal to as wide an audience as possible, resulting in what CEO Jason Cohen believes are “endless shelves of products that most people like, but few people really love.” His company has created an AI platform called Gastrograph — a free version can be downloaded via the iTunes App Store — that collects highly specific data from individual users, with the goal of “giving food and beverage companies the information they need to develop products optimised for more and more specific sensibilities.”
Tesla CEO Elon Musk is turning to intensive collaboration between programmers to help clear out production bottlenecks. Musk revealed Sunday that a hackathon was underway to fix the two worst robot production choke points. He tweeted the information in a response to an Ars Technica tweet that promoted an article on how Tesla was repeating mistakes made by automakers in the 1980s.
Musk tweeted: “Fair criticism, but we’re fixing it fast. Hackathon going on right now to fix 2 worst robot production choke points. Looks promising.”
Close to a dozen employees at Google Inc. have apparently quit their jobs in protest over a project in which the company is providing the U.S. Department of Defense with artificial intelligence.
According to Gizmodo, which spoke with some of the departing employees, Google has not taken their objections seriously. Some of them said that it is humans, not AI, who should be doing the work in matters of war.
A team of researchers from Intel and the University of Illinois at Urbana-Champaign recently developed a neural network that performs incredible post-processing enhancements on extreme low-light photographs. The AI takes images which appear pitch black or full of noise and makes them look bright, clean, and colorful.
How it’s done: The researchers created the See-in-the-Dark (SID) data set, a group of 5,094 short-exposure images in RAW format, and fed it to a deep learning system. They then trained the AI to compare the information contained in the low-light images to corresponding photographs taken at longer exposure. The results are pretty amazing.
A recently inked agreement between Paige.AI and New York-based Memorial Sloan Kettering will give the startup exclusive access to the cancer center’s intellectual property in computational pathology, as well as its library of 25 million pathology slides for the next eight years. Founder and CSO, Thomas Fuchs, said access to both Memorial Sloan Kettering’s library of slides as well as its world-class pathologists gives Paige.AI a leg up on the competition.
Fuchs ultimately hopes that by digitising slides and perfecting his company’s algorithms, pathologists will be able to use the pattern recognition capabilities of Paige.AI to conduct something of an image search. Cross-referencing cancerous slides from a fresh biopsy with Paige.AI’s database of slides, the algorithms will make use of past cases where a patient presented with similar cell morphology.
Qventus, a health IT business that harnesses a form of artificial intelligence to improve hospital workflows in a way that’s compared with air traffic control, has closed a $30 million Series B round, according to an emailed news release. The funding will be used to boost its customer base and apply machine learning tools to different pain points in healthcare.
The company has developed machine learning tools to help hospitals tackle logistical pain points such as reducing emergency room wait times for patients. It can prompt staff to check on certain patients in the form of nudges. It can also prompt staff on unfinished lab tests and imaging that needs to be completed. In the operating room, Qventus software is designed to reduce case delays and improve utilisation. Another component helps make patient discharge more efficient to reduce capacity issues for inpatients, according to the company’s website.