An emerging artificial intelligence (AI) software that reportedly reduces false negative rates for fractures by 29 percent has received FDA clearance. BoneView AI (Gleamer) detects fractures on X-rays, highlights regions of interest and submits them to radiologists for confirmation, according to the French company Gleamer. The company said the algorithm was designed to aid a variety of physicians who read X-rays in clinical practice. Noting that traumatic injuries account for one-third of visits to emergency rooms (ERs), Gleamer noted that errors with fracture interpretation, which are common during evening hours, can represent up to 24 percent of harmful diagnostic errors in the ER. The company said these errors may result from fatigue and non-expert reading of X-rays.

The breast imaging service at Leeds Teaching Hospitals NHS Trust has started using artificial intelligence (AI) to evaluate the quality of mammograms. The technology, provided by Densitas IntelliMammo, ensure that any quality issues are flagged during a patient's appointment to help reduce recall rate and improve accuracy of the image interpretation. The technology will be implemented in both screening and symptomatic breast services and will deliver instantaneous feedback and AI-generated positioning information at the point the image is taken. Dr Nisha Sharma, director of breast screening at Leeds Teaching Hospitals, said: "Using AI will make a real difference to the quality of our breast screening program and ultimately to the health outcomes of women in Leeds. Here at the Leeds Breast Screening unit we are delighted to collaborate with Densitas and build on this foundation for future developments that will improve breast care." Canadian software company Densitas, worked with the team at Leeds to customise the software to ensure it would both meet the needs of the busy department and the required high standards of the NHS Breast Screening Programme.

As Russia's invasion of Ukraine continues unabated, it's becoming a test case for the role of technology in modern warfare. Destructive software -- presumed to be the work of Russian intelligence -- has compromised hundreds of computers at Ukrainian government agencies. On the other side, a loose group of hackers has targeted key Russian websites, appearing to bring down webpages for Russia's largest stock exchange as well as the Russian Foreign Ministry. AI, too, has been proposed -- and is being used -- as a way to help decisively turn the tide. As Fortune writes, Ukraine has been using autonomous Turkish-made TB2 drones to drop laser-guided bombs and artillery strikes.

With the continuous rise in Machine Learning (ML), our society becomes heavily reliant on its applications in the real world. However the more dependent we become on Machine Learning models, the more vulnerabilities on how to defeat these models. The dictionary definition of an "adversary" is: "one that contends with, opposes, or resists" In the Cybersecurity sector, adversarial machine learning attempts to deceive and trick models by creating unique deceptive inputs, to confuse the model resulting in a malfunction in the model. Adversaries may input data that have an intention to compromise or alter the output and exploit its vulnerabilities. We are unable to identify these inputs through the human eye, however, it causes the model to fail.

Original article by Azfar Adib, who is currently pursuing his PhD in Electrical and Computer Engineering in Concordia University in Montreal. He is a Senior Member in the Institute of Electrical and Electronic Engineers (IEEE). A recent announcement by Meta about terminating the face recognition system in Facebook sparked worldwide attention. It comes as a sort of new reality for many Facebook users, who have been habituated for years to the automatic people recognition feature in Facebook photos and videos. Since the arrival of mankind on earth, facial outlook has remained as the most common identifier for humans.

AI regulations form a major part of tech industries right now. In the last five years, the adoption of AI has skyrocketed as more than 25% of businesses have already or are planning to adopt AI in the future. Clearly, as technology improves and businesses realize the value of AI adoption, the trend of AI adoption will continue to grow. AI already has a myriad of applications for both consumers and businesses, and those benefits and exponentially wide-ranging. Hence, the impotence of AI regulations remains uncompromisable.

As 2022 is now here, tech personnel and firms must take note of the new trends in the software productivity space and adjust accordingly to meet the growing expectations of the market. The future is uncertain, and if we have learned anything from the past several months is the value of being prepared for the unexpected. There are key trends especially in the areas of remote working, cloud computing, artificial intelligence, cybersecurity and outsourcing that must be considered. The freedom and ability to operate from anywhere will be permanent in the future of software development. An article by Computer Weekly suggests that the Covid-19 pandemic accelerated the growth of remote work among developers, with a reduction of office working by 74% since the pandemic hit.

Darktrace, a cybersecurity firm from Britain, has made an official statement that one of its customers successfully blocked the invasion of Babuk ransomware onto their network by using the company's Automated Response technology, titled Antigena. Antigena is a self learning tech-form that knows how to detect, respond and investigate cyber attacks. And as it is fairly backed by Artificial Intelligence (AI), it can also block emerging cyber threats in real-time. Ransomware threat has become a headache to most CIOs and CTOs of corporate companies. DarkTrace AI can detect any abnormalities in a network by scanning out performance issues and unusual connection requests and alert the admin about any possibilities of malware intrusion.

Prepare your drone flight, analyze the resulting data, and prepare professional reports using QGIS. GIS and Drone Technologies are both powerful tools for assisting people in analyzing the world we inhabit. Whether you are someone with GIS skills looking to add drones to your toolbelt, or a drone pilot who wants to level up their deliverable products, you are in the right place. Both these skills require very similar mindsets, such as an attention to detail, focus and accuracy. If you can do one, you can do the other, so why not do both!

General Atomics Aeronautical Systems (GA-ASI) has unveiled its newest unmanned aerial system called Gambit, the jet-powered platform intended to demonstrate so-called loyal wingman capabilities for the U.S. Air Force (USAF). The device's name refers to the chess world where Gambit is a chess opening move in which a player risks losing a minor piece to obtain a significant advantage in position. General Atomics describes Gambit as "an Autonomous Collaborative Platform (ACP) designed through digital engineering to speed its time to market and lower acquisition cost." The platform is being built for air dominance and will heavily leverage advances in artificial intelligence and autonomous systems. Working together with other human-piloted aircraft, Gambit will enable pilots to see deeper into hostile airspace, detect threats first, and provide time and space for critical decisions and actions.