Gyant, whose AI-enabled health platform is designed to drive patient-doctor engagement, today closed a $13.6 million round. The company says the funding will support its ongoing product development, operational, and interoperability efforts. The demand for triaging technologies, like conversational bots, has risen substantially as the coronavirus pandemic rages on, which isn't surprising. Millions of patients wait at least two hours to see a health care provider, according to a study published by the U.S. Centers for Disease Control and Prevention (CDC). In response, tech giants like IBM, Facebook, and Microsoft have partnered with governments and private industry to roll out chatbot-based solutions, as have a number of startups.
While it was a sci-fi concept, then, it is no longer a fiction anymore. Scientists around the world are using AI algorithms to predict the life of other planets in the solar system, detecting the presence of water, finding out the possibility of a Blackhole, or determining the orbital curve of a celestial object. According to NASA officials, AI could also aid in the search for life on alien planets and the detection of nearby asteroids in space. What took years for earlier astronomers to discover can now be done in a shorter time duration by using machine learning models of AI. Now researchers from Princeton University have claimed to have found a way to predict if a planet will clash with another in its path.
For today's warfighters, it's imperative to have access to the latest technology at the blink of an eye to ensure mission success and warfighter safety. To meet the challenge of equipping today's warfighters with mission-critical information, milCloud 2.0 is stepping up to provide the technology that is vital to that effort. On Wednesday July 22, General Dynamics Information Technology (GDIT), Intel, Oracle, and MeriTalk will be hosting a webinar, "milCloud 2.0: Leveraging the Latest Tech for the Mission" to educate mission partners about the latest milCloud 2.0 capabilities and technologies, as well as how the platform helps support rapid innovation in mission-critical areas including artificial intelligence (AI), machine learning (ML), cyber sensing, and other emerging technology solutions. The July 22 webinar – the second in a series of four – will help organizations maximize milCloud 2.0 capabilities, and will dive into: The digital conversation will be led by three preeminent subject matter experts: Senior Director for Oracle Public Sector Lauren Farese; Cloud Services Portfolio Lead for milCloud 2.0 at GDIT Jeffrey Phelan; and Chief Enterprise Solution Architect at Intel Darren Pulsipher. Managed by the Defense Information Systems Agency and operated by GDIT, milCloud 2.0 connects commercial cloud service offerings to Defense Department (DoD) networks.
In 2018, Silicon Valley, like Hamlet's engineer, was hoist with its own petard. Citizens were panicking about data privacy, researchers were sounding alarms about artificial intelligence, and even industry stakeholders rebelled against app addiction. Policymakers, meanwhile, seemed to take a renewed interest in breaking up big tech, as a string of congressional hearings put CEOs in the hot seat over the products they made. Everywhere, techies were grasping for answers to the unintended consequences of their own creations. So the Omidyar Network--a "philanthropic investment firm" created by eBay founder Pierre Omidyar--set out to provide them.
Set in 2013, California based AI-centric healthcare providers, Caption Health has raised a fund of up to 53 million dollars to modify equipment and quicken the medical scanning by their registered nurses without undergoing an elaborative training. It was a revisionist approach by Caption Health CEO, Charles Cadieu to bring alteration in the field of medical science with the help of artificial intelligence. Investors seized this opportunity with the pandemic's onset to envision quick popularization of Caption Health and contributed to equipping better AI-powered Softwares for performing ultrasounds and scans. After receiving the market authorization from the U.S. Food and Drug Administration for cardiac ultrasound software last year, it helped to engage even the non-specialist to conduct the ultrasound where the machine automated reading and interpretation of the search results. It further helped to demonstrate the accuracy of machine learning technologies recently. Robert Ochs, deputy director of the FDA's Office of In Vitro Diagnostics and Radiological Health, commented on it: Cardieu observed the significance of this software as it will be a boon to the COVID patients in this time of crisis by quickly detecting any change in the cardiovascular functions.
Medtronic and Medicrea announced in a press release that they are in the process of finalizing the acquisition by the US company of the Lyon-based SME. The latter is one of the pioneers in transforming spinal surgery through artificial intelligence, predictive modeling and customized spinal implants. The agreement between the two players will be achieved through the acquisition by Medtronic of all outstanding Medicrea shares. With a focus on predictive medicine, Medicrea designs, manufactures and distributes more than 30 families of FDA-approved implantable devices, which have been used in more than 175,000 surgical procedures worldwide to date. Medicrea is a Lyon-based SME with 175 employees, 35 of whom work in its subsidiary Medicrea USA Corp. based in New York. The company has its own ultra-modern production unit in Lyon, dedicated to the machining and development of custom implants by 3D printing from titanium powder.
Phil Duffy, is the VP of Product, Program & UX Design at Brain Corp a San Diego-based technology company specializing in the development of intelligent, autonomous navigation systems for everyday machines.The company was co-founded in 2009 by world-renowned computational neuroscientist, Dr. Eugene Izhikevich, and serial tech entrepreneur, Dr. Allen Gruber. The company is now focused on developing advanced machine learning and computer vision systems for the next generation of self-driving robots.Brain Corp powers the largest fleet of autonomous mobile robots (AMRs) with over 10,000 robots deployed or enabled worldwide and works with several Fortune 500 customers like Walmart and Kroger.What attracted you initially to the field of robotics?My personal interest in developing robots over the last two decades stems from the fact that intelligent robots are one of the two major unfulfilled dreams of the last century--the other dream being flying cars.Scientists, science-fiction writers, and filmmakers all predicted we would have intelligent robots doing our bidding and helping us in our daily lives a long time ago.
Medical imaging artificial intelligence (AI) specialist Avicenna.AI has announced it has received 510(k) clearance from the US Food and Drug Administration (FDA) for its CINA Head triage AI solution for neurovascular emergencies. The FDA's decision covers CINA's automatic detection capabilities for both intracranial haemorrhage and large vessel occlusion (LVO) from CT-scan imaging. Stroke is a leading cause of death in the USA, with more than 795,000 strokes resulting in more than 100,000 deaths each year. It is estimated that up to a third of the most common type of stroke are caused by LVO, when a clot blocks the circulation of the blood in the brain. Around one in 10 strokes are thought to be caused by intracranial haemorrhage.
The DARPA Subterranean (SubT) Challenge aims to develop innovative technologies that would augment operations underground. The SubT Challenge allows teams to demonstrate new approaches for robotic systems to rapidly map, navigate, and search complex underground environments, including human-made tunnel systems, urban underground, and natural cave networks. The SubT Challenge is organized into two Competitions (Systems and Virtual), each with two tracks (DARPA-funded and self-funded). The Cave Circuit, the final of three Circuit events, is planned for later this year. Final Event, planned for summer of 2021, will put both Systems and Virtual teams to the test with courses that incorporate diverse elements from all three environments.
Researchers at the US Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) have developed a novel machine learning approach to quickly enhance the resolution of wind velocity data by 50 times and solar irradiance data by 25 times--an enhancement that has never been achieved before with climate data. The researchers took an alternative approach by using adversarial training, in which the model produces physically realistic details by observing entire fields at a time, providing high-resolution climate data at a much faster rate. This approach will enable scientists to complete renewable energy studies in future climate scenarios faster and with more accuracy. "To be able to enhance the spatial and temporal resolution of climate forecasts hugely impacts not only energy planning, but agriculture, transportation, and so much more," said Ryan King, a senior computational scientist at NREL who specializes in physics-informed deep learning. Recommended AI News: Interlink Electronics Welcomes Aboard Edward Suski As Chief Product Officer King and NREL colleagues Karen Stengel, Andrew Glaws, and Dylan Hettinger authored a new article detailing their approach, titled "Adversarial super-resolution of climatological wind and solar data," which appears in the journal Proceedings of the National Academy of Sciences of the United States …