University of Bristol researchrs developed a handheld robot that predicts a user's plans, then frustrates the user by rebelling against those plans. Researchers at the University of Bristol in the U.K. have developed a handheld robot that predicts a user's plans, and then frustrates the user by rebelling against those plans, demonstrating an understanding of human intention. The robots hold knowledge about the task at hand, and can help the user through guidance, fine-tuned motion, and decisions about task sequences. While the technology helps fulfill tasks quicker and with higher accuracy, users can get irritated when the robot's decisions are not in line with their own plans. The team used a prototype that can track the user's eye gaze, along with machine learning, to derive short-term predictions about intended actions.

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GE Healthcare and Intel have a new software hardware combination that can get the most critical X-rays to the top an ER doctor's review stack. The new solution puts GE's mobile, digital X-ray system, its artificial intelligence-powered Critical Care Suite, and Intel's computer vision platform OpenVINO in one product. The Critical Care algorithms are embedded in the imaging devices to speed up image processing time. OpenVINO improves computing power to allow hospitals to deploy this new service on existing hardware. "So, the thing that's actually capturing the images is also doing the processing," said Todd Minnigh, CMO X-Ray, GE Healthcare, in a press release.

GE Healthcare and Intel have a new software hardware combination that can get the most critical X-rays to the top an ER doctor's review stack. The new solution puts GE's mobile, digital X-ray system, its artificial intelligence-powered Critical Care Suite, and Intel's computer vision platform OpenVINO in one product. The Critical Care algorithms are embedded in the imaging devices to speed up image processing time. OpenVINO improves computing power to allow hospitals to deploy this new service on existing hardware. "So, the thing that's actually capturing the images is also doing the processing," said Todd Minnigh, CMO X-Ray, GE Healthcare, in a press release.

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I don't have a pilot's license. None of these obstacles, however, stopped me from landing a small private jet recently at Stewart International Airport in New Windsor, New York. OK, full confession: Actually, the plane landed itself. I merely pressed a single red button on the roof of the main cabin, transforming it into an autonomous aircraft. I was aboard a $2.75-million Cirrus Aircraft Vision Jet, newly outfitted with an aptly named safety system called Safe Return, which is in the final stages of getting approval from the Federal Aviation Administration.

The team then used SAUCIE to analyze the dengue patients' data, which were collected by a team in India that works with School of Medicine professor Ruth Montgomery. Her immunology research considers why different individuals have different outcomes when exposed to the same conditions -- such as dengue patients and healthy individuals who live in the same home. This goal of differentiating outcomes when considering a dataset of 11,228,838 cells inspired the development of SAUCIE, and the research yielded useful biological conclusions in addition to computational advancements.

HALCON, the standard machine vision software from MVTec Software GmbH (www.mvtec.com), is well prepared for new developments in the embedded vision environment. The leading provider of modern machine vision software offers proof that its software can acquire and process images from MIPI (Mobile Industry Processor Interface) camera modules. Existing HALCON interfaces, such as Video4Linux, GenTL, as well as shared memory access, can be used for this. The hardware interface experts at MVTec have successfully tested the VC MIPI OV 9281 camera module from Vision Components in conjunction with Raspberry Pi 3 and 4, using HALCON 19.05. They also utilized the same HALCON version to successfully test the MIPI IMX290 sensor module from The Imaging Source on an NVIDIA Jetson Nano via FPD-Link III (cable lengths of up to 15 meters).

UnitedHealth Group used technology that may have kept sick black patients from receiving high-quality care. New York's state departments of financial services and health sent a letter to UnitedHealth Group over its use of an algorithm that researchers found to be racially biased. Per the Wall Street Journal, the missive is an initial step into a larger investigation. The algorithm in question, Impact Pro, identifies which patients would benefit from complex health procedures favored treating white patients than sicker black ones between 2013 and 2015, according to a study published in the prestigious journal Science. New York lawmakers deemed the use of this discriminatory technology "unlawful," and asked to either demonstrate the algorithm is not biased or to stop using Impact Pro immediately.

Discrimination in the U.S. credit market is well documented. Historically, minorities have disproportionately been denied loans, mortgages, and credit cards, or charged higher rates than other customers. Now that artificial intelligence is taking over many credit decisions -- and taking human bias out of the equation -- it'll be easy to enforce laws against discrimination in lending, right? Not necessarily, argues Jann Spiess, an assistant professor of operations, information, and technology at Stanford Graduate School of Business. In a recent paper in The University of Chicago Law Review, he and Talia Gillis, a doctoral student at Harvard Business School and Harvard Law School, examined what happens when existing anti-discrimination rules are applied to choices made by machines.