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 …
Like most nebulous technologies marketed as the cure-all for the enterprise in the 21st century, artificial intelligence--and more specifically anyone tasked with selling it--promises a lot. But there are some major obstacles to adoption for both the public and private sector, and understanding them is key to understanding the limits and potential of AI technologies as well as the risks inherent in the Wild West of enterprise solutions. Consulting firm Booz Allen Hamilton has helped the US Army use AI for predictive maintenance and the FDA to better understand and combat the opioid crisis, so it knows a thing or two about getting large, risk-averse organizations behind meaningful AI deployments. For insights on where AI still stumbles, as well the hurdles it will have to clear, I reached out to Booz Allen's Kathleen Featheringham, Director of AI Strategy & Training. She identified the five greatest barriers to AI adoption, which apply equally to public and private sector organizations.
It is not surprising that Automation will change the industry landscape while impacting the employment percentage of the common man. Robots have been replacing humans over the past decades in several countries. While some experts believe that it will lead to a future without work, others are unconvinced of this forecast. A study co-authored by Daron Acemoglu, an MIT economist and Pascual Restrepo, an assistant professor of economics at Boston University, states the statistics on this trend and how the impact of robots differs by industry and region and may play a notable role in exacerbating income inequality in the USA. According to the study, from the period of 1990 to 2007, the addition of one robot per 1000 workers reduced the national employment-to-population ratio by an average of 0.2 percent.
Artificial intelligence is the major buzzword in federal IT these days, the way that cloud once was. It's easy to see why. There is booming investment in AI in the private sector, and various agencies across the government are experimenting with AI to achieve their missions. The National Oceanic and Atmospheric Administration is working with Microsoft to use AI and cloud technology to more easily and accurately identify animals and population counts of endangered species. NASA is ramping up the use of AI throughout its operations, from conducting basic financial operations to finding extra radio frequencies aboard the International Space Station.
The term'covidiot' is a coronavirus-era slang term for someone who ignores recommendations to limit the spread of the deadly disease – and a new study reveals what makes these people dismiss the warnings. Researchers found that whether or not an individual decides to follow social distancing depends on how much information their working memory can store, which determines mental abilities such as intelligence. Following a survey of 850 Americans, the team discovered that those with more working memory capacity were more likely to comply with recommendations during the early stage of the outbreak. The findings suggest that policy makers need promote compliance behaviors, such as wearing a mask, based on individuals' general cognitive abilities to avoid effortful decisions. The coronavirus began spread across the US earlier this year and when it gained more traction, the Centers for Disease Control and Prevention (CDC) released a list of recommendations aimed at limiting the spread of the virus.
How do planetary systems--like our solar system or multi-planet systems around other stars--organize themselves? Of all of the possible ways planets could orbit, how many configurations will remain stable over the billions of years of a star's life cycle? Rejecting the large range of unstable possibilities--all the configurations that would lead to collisions--would leave behind a sharper view of planetary systems around other stars, but it's not as easy as it sounds. "Separating the stable from the unstable configurations turns out to be a fascinating and brutally hard problem," said Daniel Tamayo, a NASA Hubble Fellowship Program Sagan Fellow in astrophysical sciences at Princeton. To make sure a planetary system is stable, astronomers need to calculate the motions of multiple interacting planets over billions of years and check each possible configuration for stability--a computationally prohibitive undertaking.